**Urban Street Networks and Sustainable Transportation**

Editor

**Moeinaddini Mehdi**

MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin

*Editor* Moeinaddini Mehdi University of Liege ` Belgium

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This is a reprint of articles from the Topical Collection published online in the open access journal *Sustainability* (ISSN 2071-1050) (available at: https://www.mdpi.com/journal/sustainability/ special issues/urban street networks sustainable transportation).

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## **Contents**

Reprinted from: *Sustainability* **2022**, *14*, 3395, doi:10.3390/su14063395 ................ **153**

### **Panyu Tang, Mahdi Aghaabbasi, Mujahid Ali, Amin Jan, Abdeliazim Mustafa Mohamed and Abdullah Mohamed**

How Sustainable Is People's Travel to Reach Public Transit Stations to Go to Work? A Machine Learning Approach to Reveal Complex Relationships

Reprinted from: *Sustainability* **2022**, *14*, 3989, doi:10.3390/su14073989 ................ **171**

## **About the Editor**

**Moeinaddini Mehdi** Before he started his academic activities, he was the head of the Design Department in his hometown municipality, where he led many urban mobility projects. He was involved in various research projects related to integrated land-use and transportation planning, with a focus on sustainable mobility. The results of these studies have been published in high-quality journals. He has written and lectured widely on urban design and sustainable mobility and has taught courses on methods of planning analysis, sustainable transportation, public transport, and quantitative analysis.

### *Article* **Hierarchical Longitudinal Control for Connected and Automated Vehicles in Mixed Traffic on a Signalized Arterial**

**Xiao Xiao 1,\*, Yunlong Zhang 1, Xiubin Bruce Wang 1, Shu Yang 2 and Tianyi Chen 3**

**Abstract:** This paper proposes a two-layer hierarchical longitudinal control approach that optimizes travel time and trajectories along multiple intersections on an arterial under mixed traffic of connected automated vehicles (CAV) and human-driven vehicles (HV). The upper layer optimizes the travel time in an optimization loop, and the lower layer formulates a longitudinal controller to optimize the movement of CAVs in each block of an urban arterial by applying optimal control. Four scenarios are considered for optimal control based on the physical constraints of vehicles and the relationship between estimated arrival times and traffic signal timing. In each scenario, the estimated minimized travel time is systematically obtained from the upper layer. As the results indicate, the proposed method significantly improves the mobility of the signalized corridor with mixed traffic by minimizing stops and smoothing trajectories, and the travel time reduction is up to 29.33% compared to the baseline when no control is applied.

**Keywords:** consecutive signalized arterials; urban street; hierarchical longitudinal control; optimal control; connected and automated vehicles

#### **1. Introduction**

Sustainable transportation in an urban area has become an important topic attracting researchers' attention [1]. In the research of sustainable transportation, there have been studies from policy aspects such as promoting public transport, demand and supply controlling, integrated land use, and transport planning [2]. Other studies include developing design methods to solve technical problems operating transport means and facilities in a more efficient way [3]. The research on pedestrians and cycling is a major part of studying sustainable transportation [4]. As for motorized trips, on one hand, controlling demand is a concern [5]. On the other hand, the movements of vehicles on urban street networks and their effects on sustainable transportation is also an important component. More efficient movement of vehicles on urban street networks means a safer, faster, and more environmentally friendly urban network. Therefore, improving mobility is crucial in building up sustainable transportation.

However, drivers often experience stop-and-go shockwaves traveling through signalized intersections when most of the surrounding vehicles are driven by humans. Traffic oscillation and queue backpropagation may result in a capacity drop, leading to an increase in travel time and a decrease in mobility [6]. On an urban street, even when the signals are well-coordinated, the travel time increases for drivers traveling through consecutive signalized intersections [7]. Systematic methods for controlling vehicles on an urban arterial are essential.

The applications of CAVs in a traffic system have been studied in the last few years. CAVs can react to, communicate with, or make cooperative decisions considering the

**Citation:** Xiao, X.; Zhang, Y.; Wang, X.B.; Yang, S.; Chen, T. Hierarchical Longitudinal Control for Connected and Automated Vehicles in Mixed Traffic on a Signalized Arterial. *Sustainability* **2021**, *13*, 8852. https:// doi.org/10.3390/su13168852

Academic Editor: Moeinaddini Mehdi

Received: 1 July 2021 Accepted: 3 August 2021 Published: 7 August 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

1

environment such as surrounding vehicles and traffic facilities with the help of vehicle-tovehicle (V2V) or vehicle-to-infrastructure (V2I) communication technologies. Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) take advantage of the V2V communications so that vehicles can drive at a harmonized speed with short headways, addressing some issues that may occur for HVs in mobility, fuel efficiency, and safety issues [8]. When only considering the longitudinal direction, the design of a CACC system is usually based on a vehicle dynamics control strategy. To achieve ACC, vehicle dynamics are modeled by an optimal control framework to maintain speed while reducing emissions. When it comes to CACC, constant longitudinal spacing or headway should also be maintained [9]. Among all the objectives, the mobility, fuel efficiency, and stability of the traffic are the major concerns [8].

The longitudinal control strategies have been developed to improve mobility to mitigate the stop-and-go waves and other adverse traffic effects on freeways [10–12]. The stability problem of the longitudinal control of a CACC system in a CAV environment has also been well studied in previous studies [13–18]. Although longitudinal control strategies in the freeway environment have been well studied, the existence of traffic signals in an urban area makes the longitudinal control strategies of CAV significantly different from those in the freeway environment. The traffic signals cut traffic streams into interrupted flows and vehicle platoons which will be cut off and reformulated.

Many previous studies concerned the strategies for vehicles approaching an isolated intersection. For instance, Rakha and Kamalanathsharma developed eco-driving strategies for vehicles at an isolated intersection by integrating microscopic fuel consumption models in objective functions to minimize environmental adverse effects [19]. They also proposed a dynamic programming-based method to control the speed of a vehicle by splitting the process of approaching a signalized intersection into three states, showing that the method can save fuel and travel time significantly for an individual vehicle [20]. Chen et al. developed an eco-driving model that achieves the minimization of a linear combination of emissions and travel time [21]. Yang et al. developed an eco-CACC system to improve the fuel efficiency of CAVs at an isolated intersection considering the existing queues. Optimal control is used to design trajectories for leading CAVs of platoons to lead vehicles smoothly approaching an isolated intersection. The performances under different market penetration rates are demonstrated, showing a throughput benefit ranging from 0.88% to 10.80% [22]. A shooting heuristic (SH) is proposed for optimal control solutions for vehicle trajectories at intersections [23,24]. Individual Variable Speed Limits with location optimization are designed to smooth the trajectories of CAVs to improve mobility at an intersection [25].

In some studies, the platoon of CAVs is usually cooperatively considered. For example, a mixed-integer linear programming (MILP) based model is used to optimize vehicle trajectories as well as the traffic signal at isolated signalized intersections. The trajectories are generated by optimal control, car-following models, and lane choice models [26]. A Predictive Cruise Control method is used to control vehicles when traveling through multiple consecutive intersections to save fuel and CO2 emissions [27]. A nonlinear-programmingbased method to control a CAV platoon is designed to pass multiple intersections to maximize throughput and comfort [28].

In addition to only considering one intersection model, more pieces of the literature studied control strategies for consecutive traffic signals since the traffic signals are usually configured consecutively along the roadway in urban areas. Mandava et al. applied a dynamic speed-advise method to drive a CAV smoothly along consecutive intersections when no surrounding vehicles are concerned [29]. The method reduced fuel consumption and CO2 emissions significantly and reduced travel time slightly (1.06%) for a single vehicle. Barth et al. developed an optimal control for a single vehicle to drive along consecutive signalized intersections, with a reduction in fuel consumption and CO2 emissions. Other than the reduction in environmental adverse effects, queue minimization is considered in the development of the optimal trajectory of one single vehicle along consecutive intersections, which leads to an additional delay for the following vehicles [30]. A mixedinteger programming sequential convex optimization is used to design an optimized speed plan of a vehicle when traveling along signalized intersections, saving travel time up to 6.00% [31]. Tang et al. incorporated a speed strategy into a car-following model for multiple vehicles to pass through multiple intersections [32].

Since the traffic stream will be in a state of having both CAVs and HVs for a long time, the control strategies for mixed traffic conditions become an important research direction. Specifically, HVs are concerned in some of the previous studies when developing the longitudinal control strategies of CAVs. The interaction of HVs and CAVs is modeled to optimize mobility [33] and emissions [34]. Wei et al. tested HVs as moving obstacles to validate their integer programming and dynamic programming models [35]. Recently, some studies also focus on the evaluation of the performance of mixed traffic. For example, the performance of lane choice for the mixed traffic with CAVs is analyzed [36]. Speed estimation is conducted in a mixed traffic condition [37]. When HVs are considered, the sequence of the mixed traffic needs to be assumed; for example, Zhao et al. used scenarios in the experiment to show the possible combination of HVs and CAVs [34].

The operation strategy of connected and automated vehicles at intersections can either be modeled in a centralized way, as the studies using dynamic programming or cooperative control mentioned before, or a decentralized way. For example, Du et al. developed a multilayer coordination strategy for CAVs at intersections without the help of signals [38]. Yao and Li proposed a decentralized control method for CAVs at an intersection to optimize their own travel time, fuel consumption, and safety risks and showed that it is more computationally efficient than a centralized control [39]. Mahbub et al. developed a coordination method for CAVs at a corridor considering multiple traffic scenarios using a two-level optimization [40].

Although the problem of the longitudinal control of connected automated vehicles has been widely studied, the control for CAVs in mixed traffic is hard when considering consecutive signalized arterials, which can lead to a problem of variable control horizon. In addition, the synchronization of the calculation of CAV travel time and trajectory is a difficulty in the proposed problem. To fill in the gap, this paper provides a new approach of hierarchical longitudinal control that can address mixed traffic, tackle the variable horizon of CAVs, and give insight into the scenarios of CAV control on a signalized corridor. A centralized method is unable to model HVs, which are uncontrolled. To tackle this issue, this paper introduces an efficient decentralized method [41]. While the studies about single lanes focus on longitudinal control, CAV-related control on multilane scenarios is also a research direction concerning lane changing and lane assignment. For example, a cooperative sorting strategy is developed for the platooning of CAVs along multiple lanes [42]. Formation controls are used for the lane assignment for CAVs [43,44]. Therefore, focusing on the longitudinal control in this paper, a dedicated lane is considered to maximize the benefits of controlling CAVs and in showing how the methods influence traffic dynamics. In addition, due to the low MPR for a long period of time, HVs should also be allowed in the "dedicated" lane. In this setting, lane changing, and overtaking are not considered. Therefore, this paper models a single lane of mixed traffic. The contributions of the paper are highlighted below:

#### **2. Problem Statement**

The problem aims to control the microscopic longitudinal behaviors of CAVs by minimizing the travel time given a fixed signal timing on an urban signalized arterial corridor. As shown in Figure 1, the mixed traffic travels through consecutive intersections on the urban street from upstream intersection 1 to intersection *i* at downstream. The traffic is a mixture of HVs and CAVs. Communication devices are installed on CAVs to ensure real-time information exchange via V2V and V2I.

**Figure 1.** Schematic representation of the problem longitudinal control of connected and automated vehicles along a signalized arterial.

The assumptions of the paper are listed as follows. The V2V communication is assumed to be active once a vehicle entering the block. Information related to the timing plan such as offset *θi*, the duration of green *Gi*, green elapse time *Gn*,*i*, and geometrical variable block length *li* can be received by CAVs with no delay. The overtaking behavior of a vehicle is not in the scope of concerns. The car following behaviors of HVs are assumed as known, and HVs slow down and stop in front of a signal when they cannot pass within the current green interval.

In Figure 1, the vehicles move forward in their longitudinal direction. The travel time of a vehicle within a block is defined as the duration between the time instant when it passes the intersection *i* − 1 and the time instant it passes intersection *i*.

The vehicle dynamics within a block for a CAV are expressed by a state-space representation, indexed by the number of vehicles and intersections. On an urban street, the vehicles are not allowed to move backward. A CAV can obtain information of vehicle status such as position, acceleration, and speed from the preceding vehicle, no matter whether the preceding vehicle is a CAV or an HV.

The research question is how to reduce the travel time for all vehicles when they are traveling from the first intersection to the final intersection and provide a suitable trajectory for each vehicle. The difficulties of this problem are that traffic signals exist along consecutive intersections, cutting off the traffic. Multiple states exist for a vehicle, in which varying control horizons can appear; HVs are uncontrolled, and HVs and CAVs are mixed with arbitrary sequences, so an integrated centralized optimization is not applicable. In addition, the control horizon for each vehicle is different.

#### **3. Methodology**

The longitudinal control for CAVs follows a hierarchical structure: at the upper level, the travel time is calculated; at the lower level, the optimal control is applied to generate the trajectories.

#### *3.1. Lower-Level Control: Mathematical Formulation of Optimal Control*

When an individual vehicle is traveling within one block between two intersections, its state including position and speed is known. The problem is decomposed into different scenarios and is then scaled towards multiple vehicles along consecutive intersections. The constraints from the longitudinal position and feasible arrival moments of a vehicle with the presence of signals are mathematically described. Each scenario is explained with their transportation meaning and provided a solution of minimum travel time and trajectory.

As a solution for individual vehicles, the trajectory generates in an optimal control fashion. The state *xn*,*i* of a vehicle *n* in intersection *i* is defined as a combination of its longitudinal position *sn*,*i* within this block *i* and longitude speed *vn*,*i*:

$$\mathbf{x}\_{n,i} = (s\_{n,i\prime}v\_{n,i})^T \tag{1}$$

The system writes with a linear time-invariant system (LTI):

$$\mathbf{x}\_{n,i}(t) = A\mathbf{x}\_{n,i}(t) + Bu\_{n,i}(t),\tag{2}$$

$$\mathbf{A} = \begin{bmatrix} 0 & 1 \\ 0 & 0 \end{bmatrix} \mathbf{B} = \begin{bmatrix} 0 \\ 1 \end{bmatrix} \, \tag{3}$$

where the control variable *un*,*i* is the acceleration of the vehicle. The cost function to ensure optimal performances is defined as follows considering the comfort and terminal performances:

$$J\_{n,i} = \min \int\_{t=0}^{T\_{n,i}} L(\mathbf{x}\_{n,i}(t), \boldsymbol{u}\_{n,i}(t))dt + \Phi(T\_{n,i}, \mathbf{x}\_{n,i}(T\_{n,i})), \tag{4}$$

where the ending time or the control horizon *Tn*,*i* is a variable which is determined systematically. It is then discussed in Section 3.2, based on different scenarios. The running cost is set as an instantaneous cost showing the penalties concerning comfort. It is expressed as the quadratic term of acceleration:

$$L = \frac{1}{2} \mu\_{n,i}{}^2. \tag{5}$$

The terminal cost gives penalties so that the final states can approach desired values (terminal speed and terminal distance):

$$\Phi = w\_1 \left( \mathbf{x}\_{n,i}{}^{(1)}(T\_{n,i}) - l^\*\_{\
u,i} \right)^2 + w\_2 \left( \mathbf{x}\_{n,i}{}^{(2)}(T\_{n,i}) - \boldsymbol{\upsilon}^\*\_{\
u,i} \right)^2. \tag{6}$$

Again, *Tk*,*i* will be determined systematically. Weighing factors *w*1 and *w*2 show the penalty for the state deviation from the terminal speed and the terminal distance at the end of the horizon. The desired speed is set to the terminal speed at each intersection for each vehicle: *v*∗ *n*,*i* = *v*0. The block length between two intersections is used as terminal distance *l* ∗ *n*,*i* = *li*. The problem then writes:

$$J\_{n,i} = \sum\_{K=1}^{T} \left( u\_{n\bar{j}\_t + k - 1} \right)^2 + w\_1 \left( \mathbf{x}\_{n,i}^{(2)} \, ^2\_T - 2 \mathbf{x}\_{n,i} \, ^{(2)}\_T \mathbf{v}\_{n,i} ^\* + v\_{n,i} \, ^{\*2} \right) + w\_2 \left( \mathbf{x}\_{n,i} \, ^{(1)}\_T - 2 \mathbf{x}\_{n,i} \, ^{(1)}\_T \mathbf{l}^\* + l\_{n,i} \, ^{\*2} \right), \tag{7}$$

$$\text{s.t.}$$

$$(\mathfrak{x}\_{n,i^\prime} \mathfrak{u}\_{n,i}) \in \Omega \cap \mathfrak{U},\tag{8}$$

where *Ω* represents the constraints from vehicle dynamics, including the limitation from maximal speed, maximal acceleration, distance, etc. *U* represents the physical constraints from the preceding vehicle during the period when it follows preceding vehicle *fn*,*i*.

$$\Omega = \left\{ \mathbf{x}\_{n,i+1} = A\_d \mathbf{x}\_{n,i\uparrow} + B\_d \boldsymbol{u}\_{n\downarrow\iota}, \boldsymbol{u}\_{n\downarrow\iota} \in (\mathbf{u}\_{n,i\slash b\prime}, \boldsymbol{u}\_{n\slash,\iota\text{ib}}), \mathbf{x}\_{n,i}{}^{(1)} \in (0, l\_i), \mathbf{x}\_{n,i}{}^{(2)} \in (\mathbf{v}\_{n,i\slash b\prime}, \mathbf{v}\_{n,i\slash b\prime}) \right\},\tag{9}$$

$$\mathcal{U}I = \{ s\_{n,i} \le s\_{n-1,i} + d\_{\mathfrak{s}} + d\_{\mathfrak{v}\prime}t \in (0, f\_{n,i}) \},\tag{10}$$

where *ds* is a safe distance that can ensure safety, and *dv* is the vehicle length; *fn*,*i* is the duration of following, determined differently in different scenarios in upper-level control.

#### *3.2. Upper-Level Control: Determination of Travel Time*

Having set the variable horizon optimal control, the horizon *Tn*,*i* is to be determined systematically. Some prerequisites are provided.

#### 3.2.1. Following Behavior along Consecutive Signalized Intersections

With the availability of V2I techniques, CAV receives signal information including current state and future time phases such as *Gi* and *θi*. The arrival moments should be in a feasible region (the collection of green) and the physical constraints should always hold for safety concerns. To avoid stopping, for CAVs, the set of feasible arrival moments *Mn*,*i* should be in the collection of green time *G*:

$$M\_{n,i} \in \left[\theta\_i + \mathbb{C} \* (k-1), \theta\_i + \mathbb{G}\_i + \mathbb{C} \* (k-1)\right],\tag{11}$$

where *C* is the cycle length. If no preceding vehicle exists, *k* is the counter of the cycles after the current cycle in which the vehicle can pass. *k*∗ is the optimal *k* that minimizes the travel time. If a vehicle is not able to pass within this cycle, it is natural that it passes at the next cycle, only if the preceding vehicle has passed. Generally, k could be 0 or 1 showing whether a vehicle is able to pass at this cycle or the next:

$$k^\* = \operatorname\*{argmin}\_{n,i} T\_{n,i}.\tag{12}$$

Accumulative position *pn*,*i*(*t*) of a vehicle *n* at time *t* can be denoted as the addition of two parts: the accumulative position along previous blocks from 1 to *i* − 1, and the current position *pn*,*i*(*t*) in this block *i* for vehicle *n* is:

$$p\_{n,i}(t) = \sum\_{1}^{i-1} s\_{n,i} + s\_{n,i} \left( t - \sum\_{1}^{i-1} T\_{n,i} \right). \tag{13}$$

At time *t*, the vehicle has two state conditions which is either passed block *i* or not. When the subject vehicle has a preceding vehicle in the same block, an inequality describes the situation:

$$\sum\_{i=1} l\_i < p\_{n,i}(t) < p\_{n-1,i}(t) < \sum\_i l\_i. \tag{14}$$

Similarly, when the preceding vehicle is not in the same block, an inequality writes:

$$\sum\_{i=1} l\_i < p\_{n,i}(t) < \sum\_i l\_i < p\_{n-1,i}(t). \tag{15}$$

If the subject vehicle has a preceding vehicle in the same block, its duration is constrained by the preceding vehicle. The moments that enter or leaves a block can be calculated from the values of accumulated travel time:

$$M\_{n,i} = \sum\_{1}^{i-1} T\_{n,i\prime} \ M\_{n,i+1} = \sum\_{1}^{i} T\_{n,i}.\tag{16}$$

When a vehicle has a preceding vehicle, *fn*,*i* stands for the time duration that the subject CAV following its preceding vehicle within this block. This duration is the subtraction of the moment the preceding vehicle leaves this block and the moment when the subject vehicle enters the block:

$$f\_{n,i} = M\_{n-1,i+1} - M\_{n,i}.\tag{17}$$

To scale the problem to consecutive intersections, *Gn*,*i* shows the duration of green before the vehicle passes the intersection at the moment *Mn*,*i*. This variable links the time of trajectories between two intersections.

#### 3.2.2. Scenario Development

The continuation of position and speed are addressed by introducing variables such as the cycle length *C*, green time *Gi*, green elapse time *Gn*,*i*, and offset *θi*. Each vehicle is planned only once in a block, the moment a vehicle passes the previous intersection becomes the starting moment the vehicle enters the next intersection; the information is indicated with the help of green elapse time. The final status of a vehicle becomes the initial status in the next.

For CAVs, the arrival moments at the stop line of each intersection are estimated ahead. For HVs, the arrival moments are estimated using travel time estimation methods. According to the categories of the estimated arrival moments and whether there is a preceding vehicle, four scenarios can be defined, and they are noted as scenario 0, scenario 1, scenario 2, and scenario 3, respectively:

$$0 < s\_{n,i}(t) < l\_i < s\_{n-1,i}(t); M\_{n,i} \in \left[\theta\_i + \mathbb{C} \* (k-1), \theta\_i + \mathbb{G}\_i + \mathbb{C} \* (k-1)\right], k \le 1,\tag{18}$$

$$0 \le s\_{n,i}(t) < s\_{n-1,i}(t) \le l\_i; M\_{n,i} \in [\theta\_i + \mathcal{C} \* (k-1), \theta\_i + \mathcal{G}\_i + \mathcal{C} \* (k-1)], k > 1,\tag{19}$$

$$0 \le s\_{n,i}(t) < s\_{n-1,i}(t) \le l\_i; M\_{n,i} \in \left[\theta\_l + \mathbb{C} \* (k-1), \theta\_l + G\_l + \mathbb{C} \* (k-1)\right], k > 1,\tag{20}$$

$$0 < s\_{n,i}(t) < l\_i < s\_{n-1,i}(t); M\_{n,i} \in [\theta\_l + \mathbb{C} \* (k-1), \theta\_l + \mathbb{G}\_l + \mathbb{C} \* (k-1)], k \le 1. \tag{21}$$

When the subject CAV is the leading vehicle in the same block, the way to minimize travel time is to accelerate and maintain its desired speed to travel through the block to pass the intersection (setting the speed limit as the desired speed *v*0). The minimal travel time is obtained when the subject CAV accelerates to the desired speed and maintains the speed until it passes the signal ahead:

$$T^\*\_{\
u,i} = \{ T\_{\
u,i} | (\mu = \mu\_0 | \upsilon \le \upsilon\_0), (\mu = 0 | \upsilon = \upsilon\_0) \}. \tag{22}$$

The value of *Gn*,*i*+1 in the next intersection *i* + 1 is calculated using travel time *Tn*,*i* and the value of *Gn*,*i*, *θi* from the last intersection:

$$G\_{n,i+1} = G\_{n,i} + T\_{n,i} - \theta\_i. \tag{23}$$

For the subject CAV with no preceding vehicle in the same block, when it is not expected to pass the intersection within this cycle, it is planned to pass during the green in the next cycle, (*Mn*,*i* ∈ [*θi* + *C* ∗ (*k* − 1), *θi* + *Gi* + *C* ∗ (*k* − 1)], *k* > 1), via a smooth path without stopping. The corresponding *T*∗ *n*,*i* for both scenario 1 is calculated by:

$$T^\*\_{\
u,i} = \theta\_i + \mathcal{C} \* k^\* - G\_{\eta,i} + G\_{\eta,i+1}.\tag{24}$$

*Gn*,*i*+1 varies the arrival moments, which is set as small as possible so that the startup time can be saved compared to human driving behavior.

For scenario 2, the calculation of *T*∗ *n*,*i* and *Gn*,*i*+1 is the same as that of scenario 1. The difference is the subject vehicle has constraints from its preceding vehicle for the preceding vehicle is in the same block. *U* is active as the physical constraints of the optimal control.

Scenario 3 shows when the subject CAV follows a preceding vehicle in this intersection, and it passes within the same green window as the preceding vehicle: *Mn*,*i* ∈ [*θi* + *C* ∗ (*k* − 1), *θi* + *Gi* + *C* ∗ (*k* − 1)], *k* ≤ 1. The corresponding *T*∗ *n*,*i* is then calculated from:

$$T^\*\_{\
u,i} = \max(T\_{n-1,i} - f\_{\
u,i} + t\_{0,i\prime}\frac{l\_i}{\upsilon\_0}).\tag{25}$$

$$G\_{n,i+1} = G\_{n,i} + T\_{n,i} - \theta\_i - \mathbb{C} \* k^\*. \tag{26}$$

Note that the minimal travel time cannot be smaller than the value when the vehicle is traveling with the desired speed (in that case, the travel time from scenario 3 is no smaller than that from scenario 0). *U* is active as the physical constraints from the preceding vehicle.

Although an HV cannot respond to a CAV, a CAV can detect the position of its preceding HV. An estimation of the HV's travel time is conducted. The desired headway *t*0,*i* when a CAV following an HV is set to be larger than that an HV follows an HV to ensure safety. The travel time when a CAV follows an HV is calculated as:

$$T^\*\_{\
u,i} = \max(T\_{n-1,i} - f\_{\
u,i} + t\_{0,i(HV)'} \frac{l\_i}{\upsilon\_0}).\tag{27}$$

An HV is expected to slow down and stop if it cannot pass an intersection within the green duration. They will be modeled remaining at a standstill at the stop bars during the red phases. The subject CAV does not need to follow closely to an HV. Instead, it passes with a smooth trajectory without stopping. The calculations of *T*∗ *n*,*i* and *Gn*,*i*+1 are the same as the case when it follows a CAV. In the schematic diagrams of Figure 2, the blue line shows the estimated trajectory of an HV, and a black line shows the preceding vehicle trajectory. A magenta line represents the trajectory of a CAV.

**Figure 2.** Schematic diagram of (**a**) scenario 0; (**b**) scenario 1; (**c**) scenario 2; (**d**) scenario 3.

#### *3.3. Synthesized Algorithm*

In lower-level control, the optimal control has been set up for each vehicle to calculate their optimal trajectories. In upper-level control, the scenarios are developed. In each scenario, the way to find the minimum travel time has been introduced. The problem in this paper is to minimize the total travel time for all vehicles therefore the hierarchical control is addressed systematically in a synthesized way.

According to the analysis of scenarios, scenario 0 is designed as the vehicle that can drive with its speed limit. Scenario 3 follows preceding vehicle successfully without being hampered by a red light. Both scenarios are with no time loss. Scenario 1 and 2 experienced time losses at red. It is obvious that, at the same intersection *i*, the travel time for each scenario has the following relations:

$$T^\*\_{\
u,i}(\text{scenario}\,0) < T^\*\_{\
u,i}(\text{scenario}\,3) \le T^\*\_{\
u,i}(\text{scenario}\,1) \le T^\*\_{\
u,i}(\text{scenario}\,2).\tag{28}$$

Apparently, the travel time reaches minimal when an ideal condition can occur in which all scenarios are scenario 0. Nevertheless, a vehicle may not be able to drive with scenario 0 along all the blocks. In this case, replacing one of the scenarios into another scenario with the least cost for vehicle *n* achieves the minimal costs that are feasible. Therefore, a greedy heuristic is to try to plan scenario 0 or scenario 3 first, and then to plan scenario 1 or 2.

Define *zn*,*i* - [*un*,*i*(0) *T*,..., *un*,*i*(*t* − 1) *T*] *T* as the decision variable of vehicle *n* from the time instant 0 to *t* in each intersection *i*. Once a selection of scenarios is made, the minimal travel time *Tn*,*i* ∗ is calculated. The decision variables of the preceding vehicle *zn*−1,*i* and the constraints inputs into the next calculation. By assuming there are *N* vehicles and *I* intersections, the calculation process is listed as follows:

Start: start with intersection *i* = 1, *n* = 1

End: End by *i* = *I*, *n* = *N*.

As described in the algorithm, the controller determines each CAV individually and broadcasts its information and solutions. Information is broadcasted to the follower if it is a CAV. This proceeds until all the vehicles have solutions for trajectory profiles. The process is demonstrated in Figure 3.

**Figure 3.** The flow chart of synthesized algorithm.

#### **4. Numerical Simulations**

The proposed method was implemented in MATLAB, and the numerical simulations are demonstrated below. To test conditions under light traffic does not have much value since no traffic backpropagation will happen, so only the cases with moderate demands were considered. Two cases were presented to validate the method. Case 1 compared the method with the situation when all vehicles were HVs. HVs were assumed to slow down and stop when approaching a signalized intersection if they expected to fail to pass and remain standstill at the stop bars during the red phases. HVs were assumed to follow preceding vehicles using the intelligent driver model (IDM) model [45]. Case 2 compared the proposed method with a benchmark when all CAVs drive smoothly to avoid stopping at intersections without the consideration of minimal travel time.

Both cases comprised two examples. In one example, the initial average headway input was set as 5 s. In the other example, the initial input headway was 3 s. The desired headway for a CAV and the IDM model was set as 3 s; the desired headway for a CAV following an HV was set at 4 s for safety concerns. Multiple runs with random seeds were applied in each case to calculate the average travel time savings under each penetration rate. The parameters used in the experiment are listed in Table 1.

**Table 1.** Values of parameters in the experiments.

#### *4.1. Performance under Different Penetration of CAVs*

Case 1 compares the results when no CAVs and when some CAVs using the proposed are applied. The simulated results are presented in Figures 4 and 5.

**Figure 4.** A comparison of trajectories between HVs (blue lines) and CAVs (magenta) under varying penetration rates of CAV when the initial headway for CAVs was 5 s (x-axis —time (s), y-axis—distance (m)).

**Figure 5.** A comparison of trajectories between HVs (blue lines) and CAVs (magenta) under varying penetration rates of CAV, when the initial headway for CAVs was 3 s (x-axis—time (s), y-axis—distance (m)).

When the initial headway for CAVs was 5 s, the CAVs trajectories could lead the whole platoon to decompose and reconstruct reasonably. This led to a reduction in travel time in the first step. The results also showed that the proposed method can reduce the number of stops; as a result, the queues and backpropagation shockwaves were mitigated to reduce the startup time, which saved travel time in the second step. The method compressed the headways for CAVs when the initial headway was larger than the desired headway, which made the traffic stream compact, leading to a reduction of travel time in the third step. Compared to the situations when all vehicles are HVs (0%), the effects of mitigation of adverse phenomena became more significant with the increase of penetration rates. When the penetration rate was 100%, the stops were mostly eliminated, and no queue and backpropagation shockwave showed.

When traffic demand was higher, according to Figure 5, although the initial headways were so small that they cannot be compressed, travel time was saved from the first two steps: The whole platoon still decomposed and reconstructed in a certain manner to ensure vehicles could pass with the shortest time, and the queues and backpropagation shockwaves were also mitigated. The overall results after multiple runs are presented in Figure 6.

When the penetration rate of CAVs was as low as 20%, the methods could lead to a negative effect (−1.57% and −4.12 %). The reason was that a large desire headway (4 s) for a CAV following an HV was set to ensure safety, which was larger than the case when a CAV followed a CAV (3 s) or when an HV followed an HV (3 s). However, with the increasing penetration rates of CAVs, the travel time savings become effective. The travel time savings were significant when the penetration rate was larger than 60% for both cases. When a full penetration rate was assumed, the proposed method can provide travel time savings of 29.33 % and 26.85 % in two examples.

**Figure 6.** Travel time saving using the proposed method under different penetration rates of CAVs.

#### *4.2. Compare with a Benchmark*

A benchmark was configured with the following settings: (1) the trajectories of HVs were generated in the same way as in case 1; (2) the trajectories of CAVs were generated based on a benchmark. For case 2, only the optimal control was used to smooth the trajectories of the leading CAV at an intersection, and the others followed their leaders. Similarly, in these cases, different initial headways were demonstrated.

As seen in Figures 7 and 8, although smooth trajectories could reduce travel time by reducing time-consuming stop and startup driving behaviors at an intersection, they led to an increase in travel time if multiple intersections were involved and the local minimal travel time was not considered. This case showed the importance of the proposed method to calculate the minimal travel time locally under all possible scenarios.

**Figure 7.** The trajectories between HVs (blue lines) and CAVs (magenta) under varying penetration rates of CAV when the initial headway was 5 s (x-axis—time (s), y-axis—distance (m)) controlling CAVs using benchmark.

**Figure 8.** The trajectories between HVs (blue lines) and CAVs (magenta) under varying penetration rates of CAV when the initial headway was 3 s (x-axis—time (s), y-axis—distance (m)) controlling CAVs using benchmark.

The outputs from case 1 and case 2 showed a significant difference in Figure 9.

**Figure 9.** Travel time savings in case 1 compared to benchmark under different penetration rates of CAVs.

Comparing case 1 (using the proposed method to control CAVs) with case 2 (using a benchmark), 35.87% (shorter headway) and 39.00% (larger headway) travel time savings were shown, even when the penetration rate was as low as 20%. The percentage increased to 56.26% and 60.36% when a full penetration rate was assumed.

#### **5. Conclusions**

Traffic oscillation and queue backpropagation caused by traffic signals can interrupt traffic streams periodically and increase the travel time for drivers. To ensure sustainable transport on a signalized urban street by improving mobility, a connected automated vehicle hierarchical longitudinal control for mixed traffic on consecutive signalized arterials was proposed to control multiple vehicles along multiple intersections, considering their varying control horizons. The main aim is to focus on vehicle mobility on signalized arterials to improve sustainable urban transportation.

In the lower-level layer, mathematical formulations were developed for the relations between vehicles and signals during the time vehicles were traveling along consecutive signalized intersections. In the upper-level layer, the conditions of vehicles are decomposed into four scenarios. In each scenario, a minimal travel time is calculated. A synthesized algorithm is used to connect lower-level and upper-level layers.

Two cases were developed to validate the proposed control strategy. Case 1 concerned a non-CAV setting and Case 2 assumed all CAVs with smooth trajectory without considering the travel time. The proposed method significantly reduced the number of stops. When it came to travel time savings, when the initial headway was larger, the travel time saving ranged from −1.57% to 29.33 %. When the initial headway was smaller, the travel time saving was also significant (ranging from −4.12 % to 26.85 %). Compared to case 2 using a benchmark, the proposed method can save travel time from 35.87% to 56.26% and 39.00% to 60.36%.

The limitation of this paper was that the status of the CAVs and HVs were assumed as deterministic, and only a single lane was considered in the problem. In the future, how these scenarios are stably switched in the real world will be considered. In addition, the method is to be generalized to multilane scenarios by considering lane changing and overtaking behaviors.

**Author Contributions:** Conceptualization, X.X., Y.Z., and X.B.W.; methodology, X.X. and Y.Z.; software, X.X.; validation, X.X.; formal analysis, X.X.; investigation, X.X., Y.Z., and T.C.; resources, X.X.; data curation, X.X.; writing—original draft preparation, X.X., S.Y.; writing—review and editing, X.X., Y.Z., S.Y., T.C.; visualization, X.X.; supervision, Y.Z.; project administration, Y.Z. and X.B.W.; funding acquisition, Y.Z. and X.B.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Freight Mobility Research Institute (FMRI), grant number: 69A3551747120.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** No new data were created or analyzed in this study. Data sharing is not applicable to this article.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **Built Environment Determinants of Pedestrian Activities and Their Consideration in Urban Street Design**

**Regine Gerike 1,\*, Caroline Koszowski 1, Bettina Schröter 1, Ralph Buehler 2, Paul Schepers 3, Johannes Weber 1, Rico Wittwer 1 and Peter Jones 4**

**Abstract:** Pedestrian facilities have been regarded in urban street design as "leftover spaces" for years, but, currently, there is a growing interest in walking and improving the quality of street environments. Designing pedestrian facilities presents the challenge of simultaneously accommodating (1) pedestrians who want to move safely and comfortably from point A to B (movement function); as well as (2) users who wish to rest, communicate, shop, eat, and enjoy life in a pleasant environment (place function). The aims of this study are to provide an overview of how the task of designing pedestrian facilities is addressed in international guidance material for urban street design, to compare this with scientific evidence on determinants of pedestrian activities, and to finally develop recommendations for advancing provisions for pedestrians. The results show that urban street design guidance is well advanced in measuring space requirements for known volumes of moving pedestrians, but less in planning pleasant street environments that encourage pedestrian movement and place activities. A stronger linkage to scientific evidence could improve guidance materials and better support urban street designers in their ambition to provide safe, comfortable and attractive street spaces that invite people to walk and to stay.

**Keywords:** walking; pedestrians; urban street design; pedestrian facilities; link and place functions; sidewalk; walkability

#### **1. Introduction**

For many years, spaces for pedestrians were treated as "leftover spaces" in urban street design. In regard to technical geometrical street design, motorised vehicle size was the main determinant for minimum lane widths. The provision of dedicated lanes for public transport depended on space availability and its level of prioritisation in local transport policy; defined target values for traffic quality for motorised vehicles, e.g., in terms of level of service for the forecasted traffic volumes, determined the number of lanes in street sections and at junctions. Additionally, the recent rise in the popularity of cycling has resulted in the increase in both the quality and quantity of cycling facilities. Yet the accommodation for pedestrian needs or place functions has fallen by the wayside, particularly in areas with limited street space availability. Furthermore, seen from an engineering perspective, with a width of about 0.75 m to 1.00 m, a "standard" pedestrian does not typically occupy much space, thus causing pedestrians to be perceived and treated as a more flexible user group compared to motorised vehicles and bicycles.

**Citation:** Gerike, R.; Koszowski, C.; Schröter, B.; Buehler, R.; Schepers, P.; Weber, J.; Wittwer, R.; Jones, P. Built Environment Determinants of Pedestrian Activities and Their Consideration in Urban Street Design. *Sustainability* **2021**, *13*, 9362. https:// doi.org/10.3390/su13169362

Academic Editor: Moeinaddini Mehdi

Received: 30 June 2021 Accepted: 11 August 2021 Published: 20 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Two additional problems hamper the efforts of transport planners in providing for pedestrians: (1) Apart from the quality of the street environment, spatial structures and land use are also strong incentives for walking; thus, despite poor conditions, pedestrians will still walk if spatial structures and land use are supportive. (2) Planners rarely have reliable information about existing or expected pedestrian volumes. Even in the current era of digitalisation, pedestrians are still counted by hand in most cases, which is burdensome, time-consuming and rarely done.

Various combinations of the above-described issues have been the focus of many discussions concerning urban street design tasks, which has led to street layouts with overly narrow sidewalks. Those narrow sidewalks rarely accommodate pedestrians' movement functions and often do not encourage place activities such as resting, waiting, communicating, shopping, eating, and enjoying life in a pleasant environment.

At the same time, research interest in walking and in walkability has sharply increased, and new insights have surfaced about why people walk and about the various benefits of walking [1,2]. For example, the Health Economic Assessment Tool (HEAT-Tool, https://www.heatwalkingcycling.org/ (accessed on 14 August 2021), provided by the WHO/Europe, allows cities to compute in advance the monetised health effects of anticipated behavioural change as well as increased walking and cycling levels. It is consensus that walking is a key ingredient of liveable cities, and contributes to a healthier population as well as to more environmentally friendly travel behaviours.

Cities and stakeholders are increasingly aware of these positive effects. Thus, there is increasing interest around the world in walking and in improving the quality of street environments to be more walkable. Cities such as New York are redesigning parts of their street networks and urban spaces with a primary focus on an increased quality of space for pedestrian and dense urban areas. The City of Malmö places pedestrians at the highest level of their street-user hierarchy [3]. In London, the healthy street approach takes highest priority in the Mayor's Transport Strategy [4], and also at the national level, more and more pedestrian strategies are being put in place (see e.g., [5]). The current COVID-19 pandemic and related physical distancing requirements bring new challenges and opportunities for efforts to provide for pedestrians [6].

Seeing the scientific evidence on the positive effects of pedestrian activities and the increasing interest in encouraging walking and lively streets, it becomes clear that spaces for pedestrians must not be treated as "leftover spaces". They should be the focus of attention.

This study focuses on the design of streets and pedestrian facilities as one important determinant of pedestrian activities, as well as one main field in policy-making for promoting walking. This study compiles standards for pedestrian facilities, including both movement and place functions, from international guidelines on urban street design from five European cities and six nationwide guides from European countries and the USA (NACTO). It compares these with empirical evidence from the scientific literature on infrastructure-based determinants of pedestrian activity in urban streets.

Two goals are pursued with this approach: Our comparison of standards can be used separately by researchers who analyse covariates of pedestrian activities. Our overview of scientific evidence provides a concise summary of infrastructure-based determinants of pedestrian activities. Our comparison of scientific evidence and standards highlights how the transfer from research to practice works, and simultaneously allows us to derive recommendations for advancing the guidelines based on insights gained in research. These insights should help address the above-described tensions and challenges, and give urban street designers optimal guidance for reliably providing for pedestrian movement and place activities, while at the same time leaving flexibility for finding tailor-made solutions that fit to the local context and that overall contribute to the final goal of advancing provision for pedestrians.

The remainder of this paper is organised as follows: Section 2 presents scientific evidence on determinants of pedestrian activities related to street characteristics and the built environment. It is followed by the summary of guidance material on pedestrian facilities in Section 3. Section 4 compares scientific evidence and guidance material in order to show how the transfer between research and practice works. Recommendations on providing for pedestrians in future guidelines on urban street design are developed in Section 5. The final Section 6 summarises main findings and gives an outlook to further research.

#### **2. Determinants of Walking and Place Activities**

Research on determinants of walking and place activities is as interdisciplinary as the research topic itself [1,7]. Public health researchers focus on minutes of walking as one part of overall physical activity, and particularly include person-related variables such as socio-psychological variables, body mass index, or physical activity at work and for leisure purposes into their analyses [8]. Transport planners try to understand, above all, the influence of network and street characteristics on pedestrian volumes [9–11]. Urban planning literature also considers the characteristics of street networks, but takes a much broader view, including variables describing land use and other neighbourhood and city characteristics [12–14]. Three main groups of determinants of pedestrian movement and place activities related to street characteristics and the built environment could be identified in the analysis of the scientific literature:

In what follows, the main findings from the literature are summarised for each of these three groups of determinants.

#### *2.1. Urban Design and Land Use*

The "5 Ds" (Density, Diversity, Design, Distance to public transport, Destination accessibility) are consistently significant and influential for pedestrian activities in the researched literature [8,11,15–19]. Ewing et al. [9,20] demonstrate that Density is particularly important, measured in their example as floor area ratio and population density within a quarter mile of the investigated commercial streets. Diversity is often captured by entropy measures describing the number and variety of different land use types in a given area [15,19,21]. Ewing et al. found it to be statistically significant in one study [20], but not another study [9]. Shorter Distances, particularly to rail-based public transport, consistently and significantly increase pedestrian volumes [9,22]. Design-variables describe the characteristics, and more specifically the connectivity, of the street network, measured, e.g., as intersection density or as proportion of four-way intersections [15,23]. Mixed findings exist for these Design variables, which are significant in some studies, and not in others [9]. Destination accessibility describes the level to which relevant activities can be reached [15,24]. Destinations are operationalised, e.g., by the number of nearby stores and amenities weighted by their distance; these are hardly significant in Ewing et al. [9,20] and show an overlap with Diversity.

Some authors work with Cs instead of the Ds described above in order to investigate the influence of the built environment on pedestrian volumes: Connectivity, Convenience, Comfort, Conviviality, Conspicuousness, Coexistence, Commitment [25–28].  Streetscape*

The Ds also apply to the streetscape itself. This holds particularly for Design, but also for the other Ds. Ewing et al. [9] show the significant influence of floor area ratios along the streets themselves (computed as the total building floor area for parcels abutting the street, divided by the total area of tax lots) and of the proportion of retail frontage along the block face on pedestrian volumes. In their pioneering work on the Design variable on the street level, Ewing and Handy [11] measured more than 100 features of selected streetscapes. Based on expert rankings as the dependent variable, the following five urban design qualities were identified as the most important:

These criteria have been validated against counted pedestrian volumes in subsequent studies [11,20]. Controlling for the D variables as introduced above, on the street level, only transparency was found to significantly influence pedestrian volumes. This is consistent with findings from other studies [29,30]. The only exemption is imageability, which was identified in one study as a variable that significantly increases pedestrian volumes [29]. Ewing et al. [9] refined the above concepts and analysed the influence of around 20 variables measuring the physical features of streetscapes on pedestrian volumes separately, resulting in three significant variables: proportion of windows, street furniture, and active uses. Overall, the three streetscape design features added significantly to the explanatory power of the statistical models on pedestrian volumes, compared to models with only the D variables on the neighbourhood and street levels. Street furniture was defined as a variety of signs, benches, parking meters, trash cans, newspaper boxes, bollards, and street lights, and includes anything at the human scale that increases the complexity of the street. Public seating was found to be of special importance. The proportion of active uses was defined as shops, restaurants, public parks, and other uses that generate significant pedestrian traffic. Inactive uses include blank walls, driveways, parking lots, vacant lots, abandoned buildings, and offices with no apparent activity.

Kang [31] and Kim et al. [22] focus on the street layout itself. They find significant positive impacts of sidewalk widths, crosswalks and trees, and negative impacts of slopes, on pedestrian volumes. The number of traffic lanes is positively associated with pedestrian volume, but highly correlated with the distance to public transport. Lai and Kontokosta [19] computed a composite variable called "streetscape" as the combination of sidewalk coverage, pavement quality, and street amenity. This variable significantly increases pedestrian volumes on weekends but not on workdays.

While a large number of studies analyse pedestrian volume, only few research groups and studies focus on place activities [13,14,32–34]. These are operationalised either by the number of people in a place [33,34], or by the liveliness index, as the product of people undertaking place activities times the duration of these activities (15 s to <1 min, 1 min to <5 min, 5 min to <10 min, 10 min to <15 min, ≥15 min) [13,14,32,35]. Mehta and Bosson [14] distinguish various activity types and the following physical human postures for their studies: standing, sitting, lying, sleeping. The determinants of place activities show substantial similarities with those of pedestrian volumes, and add further

valuable insights to how to achieve lively streets, including both pedestrian movement and place activities. The existence of community places, such as stores, that are places to meet neighbours, friends, strangers, etc., are most important for the liveliness index, followed by the provision of seating, both commercial and public. Personalisation is also statistically significant and describes how the interface of businesses with the street (building façade, entrances, shop windows) is embellished with personal touches, such as displays, decorations, signs, banners, planters, flowerboxes, and other wares. The variables permeability and variety of businesses are only significant in one study each [14,32]. Sidewalk widths are only significant in a study by Metha [32], and seem to be more of a mediating variable that is less relevant on its own but allows for facilities, such as seating, on the sidewalk that foster place activities. No significant influences on the liveliness index have been identified for shade provided, the existence of street furniture besides seating, the articulation of façades, and the degree of independence of the adjacent stores.

In addition to these empirical analyses of the influence of streetscape, urban design, and land use on pedestrian activities, various schemes for assessing walkability exist, e.g., the Pedestrian Environment Review System (PERS) [36], the Microscale Audit of Pedestrian Streetscapes (MAPS) [37] or the Healthy Street Checks applied by Transport for London [38]. These studies mainly rely on expert knowledge. They formulate recommendations for how to check the friendliness and suitability of street network elements for walking and place activities, and for how to improve walkability. The street characteristics included in these walkability assessments correspond well with the significant variables identified in the literature as described above, but go beyond this empirical evidence based on expert knowledge. Various street characteristics are investigated in walkability assessments, and these can be grouped along (1) destinations and land use, (2) street scape, and (3) aesthetics and social aspects [37].

Gehl [12] distinguished twelve quality criteria for high-quality street spaces for pedestrians. The criteria are grouped into the following categories:

Gehl [12] does not provide any quantitative validation for these twelve criteria, such as a comparison with empirically measured volumes of pedestrian movement or place activities. However, he lists various examples for the successful application of these criteria in projects for redesigning streets and public spaces all over the world [39].

#### *2.3. Governance and Stakeholder Engagement*

Studies in urban design, and particularly the projects published by the groups around Mehta et al. [13,14,32,35,40] and Gehl et al. [12,39], clearly show that successful provision for pedestrians needs more than tailor-made and pedestrian-focused designs. Designing and managing liveable streets is an interdisciplinary task that can only be achieved if far more stakeholders collaborate than only urban and transport designers.

Cities have a prominent role in initiating and coordinating such collaboration and in developing policies that support the various community-based stakeholders to engage in improving and actively using the streets in their neighbourhood. Incentive schemes might be set up that create or strengthen small independent businesses, especially those that are perceived as community places. Longer and more flexible opening hours for local businesses might be considered and encouraged, contributing to active street usage over the whole day, week, and year. Cities might transfer some level of control to businesses and users so that these local stakeholders are enabled and feel invited to claim street space, e.g., by providing movable street furniture or by allowing businesses to use parts of the street for their activities and facilities. Incentives might also be given for the organisation of events such as street closures, festivals, open classroom projects, or other activities that strengthen the community. Temporary changes in the use of parts of the streets, e.g., by allowing parklets in summer, by closing lanes or taking out parking lots, e.g., on selected weekends, might also encourage pedestrian activities and give a different perspective on the potential of streets and possible perspectives.

Local building codes might support permeable and articulated façades at the street level. Nooks, alcoves, small setbacks, steps and ledges serve multiple purposes, e.g., people might seek shelter, get out of pedestrian flow, or stop and rearrange their belongings.

Streets are ecosystems; their users and usages constantly evolve. Streetscapes that are perfect for today might not be suitable in the near future. In addition, successful, liveable streets are well maintained streets; therefore, street management should be treated as equally important as the design. Regular evaluations of users and usages are needed in order to modify the street accordingly if change happens. Regular street management includes the operation of removing trash, sweeping and keeping the sidewalk clean, repairing and replacing furniture, maintaining trees and plants, etc. Local stakeholders might engage in some of these activities, and they might be supported by small and flexible funding schemes provided, e.g., on the city level.

#### **3. Recommendations of Facilities for Walking and Place Activities in Guidance Material on Urban Street Design**

#### *3.1. Methodology for Collating and Synthesising Guidance Material*

Data on guidance material for facilities for walking and place activities were gathered based on the MORE project (Multimodal Optimisation of Roadspace in Europe, https://www.roadspace.eu/ (accessed on 14 August 2021), which brings together urban street designers from all over Europe. This project provides the unique opportunity to assemble guidance material on urban street design in local languages, to combine it into a standardized, approach as well as to gather background information about how this material is generated and used in daily planning practice. Guidelines and additional material in English—but also in various local languages—could therefore be synthesised for various European countries and, in particular detail, for the MORE city and corresponding country partners of Budapest, Constanta, Lisbon, London, and Malmö. Questionnaires with the following blocks of questions have been sent out to partners as the basis for collating relevant material: genesis and responsibilities for developing guidance, systems of road function classification, objectives and performance indicators for urban street design, specific recommendations for each street user group (pedestrians, cyclists, public transport, private motorised traffic, kerbside activities, etc.), and safety issues.

Partners from the MORE project filled in the questionnaires and provided relevant material. Intense discussions and feedback loops for translating materials and for compiling consistent information for all cities and countries followed and led to standardised comparisons for all street user groups. Further materials from other countries beyond the MORE partners have been included in order to get a broad picture of international practice in urban street design. Gerike et al. [6] have provided further information on this methodological approach.

The focus of this paper is on pedestrians and place activities. For these user groups, we analysed and summarised the following aspects in Table 1:

• Space requirements for moving pedestrians (movement function)—What width is assumed for "standard" pedestrians and for pedestrians with increased space requirements such as wheelchair users? Space requirements for two or more pedestrians are also provided in some references and included in Table 1. The reason for this is that sidewalks are never used in only one direction. Pedestrians are free to move in any direction on either side of the street and they extensively make use of this capability. This must be considered when designing pedestrian facilities;

#### *3.2. Summary of Recommendations Provided from Guidance Material*

Table 1 combines the information taken from the researched guidance material on urban street design to provide an easily accessible comparative overview of the standards in the different countries and cities.

The combined research material shows that standards for space requirements of pedestrians are provided in most references and are comparable to one another. The width of a standard pedestrian varies between 0.55 m and 1.00 m. The main reason for this range seems to be the different definitions, as some references include (and others exclude) buffer space in the provided dimensions for standard pedestrians. Values for two pedestrians are given with few exceptions, and vary between 1.50 m and 2.00 m. Only the German guidelines on urban street design are clear and exacting, specifying that sidewalks should generally be scaled based on space requirements for two pedestrians. This specification is based on the fact that pedestrians walk in either direction on a sidewalk and that sidewalks should be generally designed in a way that allows two pedestrians walking in opposite directions to meet and pass each other.

Measurable differences were identified among buffer zones; these ranged from 0.00 m to 1.00 m. The criteria used for choosing buffer zone widths for each design task are consistent across locations. Buffers to the carriageway depend on speed and volume of motorised traffic. Buffers to the edge of the street depend on the type and size of adjacent buildings. However, the values themselves differ greatly.

The fairly similar space requirements for pedestrians summarised above translate within the researched guidance material into very different recommended sidewalk widths ranging from 1.00 m upwards. This wide range shows the difficulty of integrating adequate sidewalk widths into urban street layouts. A sidewalk of 1.00 m means that one standard pedestrian with an assumed width of 0.75 m can walk on this sidewalk with about 0.12 m buffer on both sides. One pedestrian needs to leave the sidewalk if two pedestrians walking in opposite directions meet each other. A wheelchair user with a width of 0.90 m can use this sidewalk with a 0.05 m buffer to each side. On the one hand, this is not very comfortable, and, on the other hand, it is also a safety issue when pedestrians use the carriageway when meeting each other. The authors of the guidance material are definitely aware of pedestrian space requirements and of the problems that might result from very narrow sidewalks. Nevertheless, they include these low values for sidewalk widths into their recommendations. The main reason for this is space scarcity. Particularly in historic city centres, it is rarely possible to accommodate all user requirements into the limited available street space. Low minimum values, e.g., for sidewalk widths, could help with

finding compromises for such challenging design tasks, and in the minds of the authors of the guidance material, these low values can be applied for pedestrians more easily than, e.g., for buses, which simply cannot pass a cross-section when lanes are too narrow.

Some references provide specific guidance for bottlenecks; these might help in such cases. For example, Transport for London [50] allows for a minimum width of the footway clear zone of 1.00 m, and for a maximum length of 6 m. Two pedestrians cannot meet each other here, but they might wait at a passing point until the bottleneck is cleared and can be passed. The Municipal Chamber of Lisbon [47] recommends coexistence streets (shared spaces) in situations of limited space availability; further references recommend taking out selected functions completely (such as parking), and thus allowing for regular widths for the remaining elements in the street [45].

The criteria for choosing sidewalk widths beyond minimum values are (1) the street type (Budapest/Hungary, Lisbon, London, Madrid, Malmö, Germany, Spain, The Netherlands), (2) speeds and volumes of motorised traffic (Austria, Germany, NACTO), (3) pedestrian volumes (Budapest/Hungary, Constanta, London, Switzerland), (4) the existence of parking or cycling facilities (Austria), (5) or proximity to specific destinations such as schools or retirement homes (Germany, Malmö).

The criteria for distinguishing street types for criterion (1) are based on road function classification, using mainly one-dimensional systems such as urban and district roads/local collector roads/local access roads in Madrid, or residential streets/major streets/commercial streets in Budapest. London's [70] approach to movement and place functions is a two-dimensional system for road function classification that disentangles user requirements in terms of pedestrian movement (walking) and place activities (staying). It is thus more detailed and better suitable for designing sidewalks that fit specific user needs in each of the two dimensions. Some references describe street types based on specific street characteristics, such as the location of the street section (e.g., inner versus outer city, proximity to specific destinations such as schools or retirement homes), characteristics and usage of adjacent buildings or traffic (e.g., volumes of motorised vehicles); these characteristics show an overlap with the more specific criteria (2) to (5).

The second criterion of speeds and volumes of motorised traffic focusses on safety and buffer zones. The third criterion (pedestrian volumes) seems to be very suitable for optimally matching sidewalk design and user needs. The disadvantage of this criterion is that it is based on the status quo and not on anticipated or desired pedestrian volumes. In addition, it is difficult to apply because of insufficient knowledge on pedestrian volumes. Discussions with city partners in the MORE project revealed that pedestrian volumes are hardly considered for sidewalk design, even when these are listed as criteria in the local or national guidance material, mainly because of a lack of data availability. Criterion (4) again focusses on safety and buffer zones, while criterion (5) is a suitable input for deciding on sidewalk width and is frequently applied.

More sophisticated references provide not only recommendations for the overall sidewalk width, but also give additional recommendations for different zones of the sidewalk [45,47,50,54,67]. This approach allows for a clear separation of movement and place functions. The footway clear zone (also called pedestrian through zone) is the part of the sidewalk that should be kept clear from any obstacles and that is dedicated to the movement function; it should allow pedestrians to move safely and comfortably. The recommended minimum width for footway clear zones is 1.20 m in Lisbon (on existing 4th or 5th level streets); 1.50 m in Budapest, Constanta (street category III), London (acceptable minimum) and the U.S.; 1.80 m in Germany, Madrid, Lisbon (for new streets), Spain and The Netherlands, and 2.00 m in Austria, London and Switzerland 2.00 m as the preferred minimum.

**Table 1.** Recommendations for Pedestrian Facilities in Guidance Material on Urban Street Design.

*Sustainability* **2021** , *13*, 9362

#### *Sustainability* **2021**, *13*, 9362

**Table 1.** *Cont.*

The frontage zones, furniture zones, and kerb zones are spaces that are dedicated to place functions or that serve as buffer zones, as described above. Recommendations for place functions are very technical in the researched guidance material, and include mainly space requirements for street furniture such as benches, parklets, terraces, gastronomy tables/seating, waiting areas at public transport stops, or parking facilities for bicycles. Malmö is the most advanced in providing space requirements for greenery. Transport for London [50,59] lists possible place activities for different widths of the furniture zone. Some references work with pictograms to visualise possible sidewalk usages for specific sidewalk widths; for example, they provide a pictogram showing a group of pedestrians who chat and give the necessary sidewalk width for this scenario [6]. Provision for place functions is additionally included in the increased sidewalk width for specific street types, as described above.

Overall, the focus of the researched guidance material is clearly on the movement function for pedestrians; rarely is any information given about how to design pleasant spaces for place users that fit to the human dimension and that encourage users to stay, sit, chat, etc.

#### **4. Comparison of Empirical Evidence and Guidance Material in Urban Street Design**

Empirical evidence in the researched literature consistently shows the dominance of the D variables for pedestrian volumes, including pedestrian movement and place activities. Density, Diversity of land uses and Distance to public transport are significant determinants of walking and, with less comprehensive empirical evidence, also for place activities in all the studies identified in the literature research. Streetscape also matters, but with less importance compared to the D variables at the neigbourhood level. Floor area ratios, the proportion of retail frontage or other active uses of the adjacent buildings, as well as faҫade design, are the most important variables at the street level. Transparency at the ground floor level is of particular relevance; people like to see what happens inside the buildings next to the street. These street characteristics, as well as the D variables on the neighbourhood level, are shaped by urban planning rather than by transport engineering.

Sidewalk width, street furniture and amenities are the relevant variables related to actual street design. Sidewalk width shows ambiguous causality: wider sidewalks are implemented in locations with observed or anticipated high pedestrian volumes, and they allow the placing of (more) street furniture and amenities, thus inviting pedestrian activities. Empirical evidence clearly shows that street furniture and particularly seating increase pedestrian volumes, and the relationship between sidewalk width (other things being equal) and pedestrian volumes is thus clear.

The comparison of this empirical evidence in the scientific literature with the compiled guidance material shows that they are not well linked. Guidance material for pedestrian facilities focusses on space requirements for specific furniture and usages of sidewalks. Recommendations on which sidewalk design to choose in a specific location are based on criteria that focus on safety and buffer zones (e.g., existence of parking), pedestrian volume (a criterion that is hardly measured and only represents the current situation), or street types, without good support from scientific evidence. The street type approach as such, in combination with the proximity to relevant destinations, seems to be the most suitable criterion for deciding on sidewalk width and design. However, it should make use of the determinants for pedestrian movement and place activities, as these have been identified in the literature. These are the D variables, particularly Density, Diversity and Distance to public transport. In terms of classification, the characteristics of adjacent buildings, particularly at street level, should be considered as one criterion for defining the street type. Based on street type classification, recommendations should be given for sidewalk widths, design and equipment. These should cover both the movement function for pedestrians (walking) and place activities.

#### **5. Recommendations for Advancing Guidance on Urban Street Design**

Based on the findings so far, this section develops recommendations for pedestrian facilities in future guidelines on urban street design.

Movement Function:

Place Function:

#### Bottlenecks:

Bottlenecks are a major problem in planning for pedestrians. Guidance should be provided about how to deal with bottlenecks. Examples of such guidance are given above in Section 3. For example, selected functions such as parking might be taken out completely in narrow parts of a street in order to gain space for pedestrians. Shared space concepts might be a solution, as proposed for Lisbon. Low speeds and volumes of motorised traffic are necessary for successfully implementing such concepts. Gehl [12] concludes from his practical work and research that these shared space concepts only work if, firstly, priority is legally given to pedestrians. Narrow sidewalks for limited and clearly defined distances, as suggested in London and in the Netherlands, are another opportunity for dealing with bottlenecks. Narrow values such as 1.00 m should be limited in their application, as otherwise, there is the risk that these become the standard values commonly used. These standard values for sidewalk width should instead be values that allow pedestrians to at least move safely and comfortably in both directions and to meet each other.

#### Streets as ecosystems:

Streets are vital parts of urban ecosystems. They are places where man-made infrastructure interferes with natural systems. Street design is a significant determinant for various aspects of environmental quality at the street level itself, as well as beyond. It influences the micro-climate, as well as the exposure of street users and residents in the adjacent properties to noise and air pollution, and it is one core component of water management at the city level. Designing for streets as ecosystems is an interdisciplinary task that requires collaboration between urban, transport and environmental planning, including, e.g., public works and water departments. These aspects regarding how to provide for ecosystem services and how to maximise synergies between all the different street functions are hardly covered at all in the researched guidance material on urban street design. They should be included in future guidelines with the final goal of designing streets and cities that are resilient, efficient in moving people and goods, sustainable, and enjoyable.

The NACTO guides can be seen as a best practice example for including environmental aspects into guidance on urban street design. The Urban Street Design Guide [54] stresses the importance of planning for streets as ecosystems, and gives brief guidance on important design elements, such as stormwater management, bioswales or flow-through planters. The Urban Street Stormwater Guide [71] details these aspects with a particular focus on the important aspect of stormwater management.

#### **6. Conclusions, Summary and Outlook for Further Research**

Planning for pedestrians is an interdisciplinary task that requires contributions from (1) transport planning, (2) urban planning, and (3) environmental planning, as well as (4) commitment from the city, local businesses and communities, and from other local stakeholders. Our review of scientific literature has shown that all four of these aspects are important, and that no clear priorities can be identified. Some level of trade-off seems to be possible between the four criteria. For example, one weak element, e.g., in transport planning/street design, might be compensated by strong urban design and stakeholder engagement. However, none of these four aspects can fail entirely when the goal of lively streets must be achieved.

The review of guidance material on urban street design shows that urban street designers are well advanced in measuring space requirements for pedestrians and for pedestrian facilities, but less in planning pleasant urban environments that fit the human dimension and invite pedestrian movement and place activities.

It will be neither possible nor meaningful to integrate all relevant aspects of successfully providing for pedestrian activities as identified in the scientific literature into guidelines on urban street design. However, a better linkage with scientific evidence can greatly improve the guidance material. The recommendations given in guidelines on urban street design could be far more focused on the significant aspects as identified in scientific literature, with two types of possible positive effects: In a supply-oriented approach, sidewalk width and design match with pedestrian needs and activities at each specific location. In a demand-oriented approach, wider and more attractive sidewalks including space for pedestrian movement and place activities can be provided at the most suitable locations based on scientific evidence, thus inviting people to come and stay in the streets and to support lively cities and streets, with various positive side effects.

The suggestions of more targeted recommendations for pedestrian facilities, and particularly for place functions, in future guidelines on urban street design hopefully contribute beneficially to the discussion on how to promote walking and lively streets. This could contribute to various positive side effects in overall travel behaviour, the economy and the environment. Planning for walking and place activities will only be successful if this is done in the context of all street functions and user needs. The challenge is to find the right balance between movement and place functions for all the different user groups anew for each design task.

The current COVID-19 pandemic brings new challenges, but also opportunities. Walking is one essential aspect of resilient transport systems, and has substantially increased in importance in the last few months. Insights into behavioural changes due to COVID-19 restrictions, and also into the effects of policy measures implemented in various cities all over the world for supporting social distancing and for generally promoting walking and place activities (see e.g., [6]), should feed into future guidelines.

Sufficient evidence exists in the literature that can reliably be translated into recommendations for planners and urban street designers. Further research on the determinants of walking and pedestrian place activities would help to additionally validate the findings from the studies published so far, and to elaborate on issues that have not been addressed in detail in the existing studies.

**Author Contributions:** Conceptualisation and methodology, R.G., P.J. and R.W.; data collection and curation, R.G., C.K., B.S., R.B., P.S. and J.W.; writing—original draft preparation, R.G. and C.K.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the European project Multimodal Optimisation of Roadspace in Europe (MORE), which has partners in Budapest, Constanta, Lisbon, London, and Malmö. MORE (https://www.roadspace.eu/ [accessed on 14 August 2021]) is a 3-year project, which receives funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 769276.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.

**Acknowledgments:** The authors acknowledge the MORE partners' support in all steps of the project.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**

### *Article* **Guidance and Practice in Planning Cycling Facilities in Europe—An Overview**

**Bettina Schröter 1,\*, Sebastian Hantschel 1, Caroline Koszowski 1, Ralph Buehler 2, Paul Schepers 3, Johannes Weber 1, Rico Wittwer 1 and Regine Gerike 1**

**Abstract:** The provision of convenient, safe and seamless facilities for cyclists is one core success factor in promoting cycling as a mode of transport. Cycling infrastructures and planning philosophies differ greatly between countries, but there is no systematic overview or comparison of similarities and dissimilarities. The aim of this study is to provide an in-depth international overview of guidance material for cycling facilities in European countries and to develop recommendations for advancing provisions for cyclists. International guidance materials for cycling facilities along street sections are collated, systemised and compared. For researchers, the findings provide background information to better understand cycling behaviour and safety. For planners, the findings support their efforts to support cycling and to improve guidance materials. The results show that, in general, countries that are just beginning to promote cycling tend to offer a greater variety of cycling infrastructures in their guidance materials than more mature cycling countries. Countries differ in whether they prefer to put cyclists on the street level or on the sidewalk and whether they mix cyclists with other user groups in the same space. There was even greater variability among countries in the criteria for selecting types of cycling facilities than in the design characteristics (width, buffer zones, etc.).

**Keywords:** cycling; urban street design; cycling facilities; bike lanes

#### **1. Introduction**

Cycling is trending in research and in practice. The dynamically growing literature on cycling demonstrates how integral the establishment of safe and convenient cycling facilities is for increasing cycling levels [1], besides socio-demographic/-economic/ psychological variables, land-use and external factors such as climate and topography [2,3]. Cycling infrastructures need to be seamless and perceived as safe as well as provide appropriate levels of objective safety, e.g., in terms of crashes or conflicts. Literature also consistently shows that cycling is associated with various positive effects on the efficiency and environmental performance of transport systems as well as on the health and wellbeing of individuals [3].

Cyclist volumes are increasing in many cities and countries all over the world [4–6]. Many stakeholders agree that cycling, along with other active modes such as walking, should be regarded as a vital feature of transport systems to create attractive, comfortable, safe and healthy communities. They are working hard to promote cycling as a mode of transport and to improve cycling conditions; ambitious goals are being established in strategic urban and transport planning—for example the Sustainable Urban Mobility

**Citation:** Schröter, B.; Hantschel, S.; Koszowski, C.; Buehler, R.; Schepers, P.; Weber, J.; Wittwer, R.; Gerike, R. Guidance and Practice in Planning Cycling Facilities in Europe—An Overview. *Sustainability* **2021**, *13*, 9560. https://doi.org/ 10.3390/su13179560

Academic Editor: Moeinaddini Mehdi

Received: 30 June 2021 Accepted: 13 August 2021 Published: 25 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Plans (SUMPs)—which target cycling either as a sole means of transport or in combination with walking and public transport. Examples for the latter are the cities of London and Vienna which aim for modal split proportions of 80 to 20 percent (walking/cycling/public transport vs. car) [7,8]. Lobby groups, such as national cycling associations or the European Cyclists' Federation (ECF) have increased their activities and influence substantially in the last decades and are today stronger in terms of membership and political influence for cycling than ever before. In summary, there is a pressure on planners to pay particular attention to cycling, both from the demand side (as a result of increasing cycling volumes) and from the policy side (resulting from the positive image of cycling).

These developing and multifaceted incentives toward an increase in the use and awareness of cycling have led to a variety in cycling facilities between countries and cities, and also to a dynamic collection of guidance material for cycling provision [9]. The aim of this study is to provide an in-depth international overview of this guidance material for cycling facilities and to develop on this basis recommendations for advancing provisions for cyclists. To our best knowledge, such a systematic overview is missing so far, only few and often non-scientific collations could be identified [10–13]. These are not very detailed and fragmented, and thus do not allow for systematic comparisons of standards for cycling facilities.

International guidance materials are therefore collated in this study, systemised and compared to each other and also with findings on infrastructure-based determinants of cycling safety from the scientific literature. The findings provide background information for researchers to better understand cycling behaviour and safety; they should support policy makers and planners in their efforts to support cycling and to advance and apply guidance material in a way that actually improves cycling conditions in terms of comfort, perceived and actual safety.

This paper focusses on the design of cycle facilities on sections in urban areas. It first describes the methodology used for researching the various materials including the development of a scheme for classifying cycling facilities in Section 2. Results are presented in Section 3 for the widths of cycling facilities and in Section 4 for the criteria used for selecting specific types of cycling facilities in the different countries. The summarised information in Section 5 and the comparison with the literature on determinants of cycling behaviour and safety in Section 6 lead to recommendations in providing for cycling in future guidelines on urban street design in Section 7. The paper ends with a summary in Section 8.

#### **2. Methodology and Classification of Cycling Infrastructure**

The basis of this study is a comprehensive research of guidance material on urban street design in European countries with a focus on the partner countries and cities in the MORE project (Multi-Modal Optimisation of Road-Space in Europe, https://www. roadspace.eu/ accessed on 13 July 2021). A questionnaire was sent to the MORE partner cities Budapest, Lisbon, London and Malmö and further technical partners (ECF, International Federation of Pedestrians (IFP), International Road Union (IRU), POLIS, PTV Group, International Association of Public Transport (UITP)) asking for material and information with relevance for urban street design in their city or from their specific perspective (technical partners). Partners were highly engaged in providing insights and references including their partial translation if necessary. Various feedback loops with discussions in teleconferences and personal meetings followed, gave background information and helped to better understand the material provided in local languages. As a result, the scope of this paper focuses on the MORE partner cities and countries. Material on other countries, for which there were no local partners in place, was added if information could be identified via desk research only. The guides published by the National Association of City Transportation Officials (NACTO) have been included as it is widely used [14–16].

In summary, recommendations for cycling infrastructure from Budapest, Lisbon, London, Malmö, Germany and the Netherlands are included in this study. Recommendations are valid on national level for Budapest (Hungary), Germany and the Netherlands. Information given in Lisbon, London and Malmö is valid on the municipal level.

Researched guidance material on cycling is, in most cases, more recently updated than for other street user groups (e.g., for motorised traffic or pedestrians) and it is more often in the active process of being updated (e.g., in Budapest, Germany, London, Malmö). This shows the high dynamics in cycling provision that is currently ongoing in all the researched countries across Europe. In addition, heterogeneity in types and range of application of cycling infrastructures are much greater compared to other user groups. One possible reason for this might be the relatively recent developments and changes in this area as described above. Another reason might be that cycling is (besides the other micro modes such as scooters) the only transport mode that can share the same space with other street users in the carriageway or on the sidewalks or that can be accommodated in dedicated cycling facilities, again either in the carriageway or on the sidewalks.

Terminology and also types of cycling facilities differ greatly between the researched references. To compare standards and their range of application, a consistent classification of cycling infrastructures is developed for this study as shown in Table 1.

**Table 1.** Types of cycling provision as identified in the guidance material.

Advisory cycle lanes are defined in the above Table 1 as one type of cycling infrastructure but, technically, they are a sub-type of mixed traffic because the advisory cycle lane is not exclusively dedicated to cyclists. It might also be used by general traffic. In contrast, mandatory cycle lanes are on-carriageway facilities and exclusively dedicated to cyclists. They can be separated by a striped or solid line or even have light segregation to motorised traffic.

The greatest variety in design is found for cycle lanes and cycle tracks. The standard design option for cycle lanes is a dedicated lane for cyclists on carriageway level. Cycle tracks are usually on sidewalk level. Additionally, separated cycle lanes as well as stepped cycle tracks are recommended in the researched guidance material [17,18,20]. Those cycling facilities provide higher comfort and safety for cyclists compared to mandatory cycle lanes. Transport for London [20] recommends cycle lanes with either light or full segregation from motorised traffic. Light separation is designed with discontinuous pre-formed separators such as planters or flexible posts along the cycle lane and has buffer markings in some cases. Fully separated cycle lanes have a raised curb, separating strips, islands, grass verges or lines of planting which all create a continuous physical barrier between motorised traffic and cyclists. Stepped cycle tracks are located on an intermediate level between the carriageway and the sidewalk.

Cycle paths are always on sidewalk level as they are shared with pedestrians. Cycle ways are away from motorised traffic, e.g., in parks and may be dedicated to cyclists or shared with pedestrians.

#### **3. Width of Cycling Infrastructure**

The different types of cycling facilities are classified along their horizontal and vertical location relative to the carriageway and to the sidewalk: The horizontal location describes whether the cycling facility is on or off the carriageway, whereas the vertical location describes whether or not there is a difference in height between the carriageway/sidewalk and the cycling facility. In addition, information is given about whether or not the cycling facility can be used by other street users and whether or not (and how) it is separated from motorised traffic and pedestrians.

The degree of separation from pedestrians on off-carriageway cycling facilities on sidewalk level can differ. There might be a marking or a physical barrier (e.g., change in pavement or greenspace) separating cyclists and pedestrians or both might use the same space.

Mixed traffic does not require any provision for cyclists, but can be complemented by sharrows. Sharrows (also called pictograms) are defined in this context as non-contiguous lane markings and aim to make clear that cyclists are allowed and welcome in the carriageway. They also give direction about where to cycle in the carriageway, support cyclists in maintaining safe distances from parked cars and discourage overtaking by cars in narrow sections. Sharrows are mainly used where space is too narrow to provide a dedicated cycling facility [17,18] and should only be used if all conditions for mixing cyclists and motorised traffic on the carriageway are guaranteed (see Section 4).

Bicycle streets are a cycle-friendly design option for mixed traffic and are frequently used in the Netherlands [19]. These are residential streets with low link function for motorised traffic but with high link function for bicycle traffic. Bicycle traffic should be dominant in bicycle streets and should have higher volumes than car traffic. Bicycle streets might be also planned if current volumes of bicycles are lower than volumes of motorised traffic but an increase is expected or should be supported by providing a high-quality facility for cyclists. Service roads are small lower speed streets parallel to main streets with high speed or volumes of motorised traffic. Cyclists and local motorised traffic share the space in the service road. Cycling is often prohibited in the main street in these cases. Service roads often come in combination with sharrows or the dedication as a bicycle street.

Shared bus and cycle lanes where buses and cyclists are allowed to use the same lane and service roads are other design options in the category of mixed traffic. Recommendations on the width of specific types of cycling infrastructure are based on assumptions or measurements for the space needed by individual cyclists, the number of cyclists that is supposed to use the infrastructure, the allowed movements (passing, meeting) and the adjacent infrastructures. The basis for determining the space for cycling facilities is in most cases the definition of the space requirements of a standard cyclist in combination with buffer zones. All these aspects were therefore included in the analysis of the guidance material. Table 2 presents the space requirement of a standard cyclist and the recommended

widths of buffer zones in the researched guidance material. Table 3 gives an overview of the recommended widths of cycle facilities.

The space requirement of a standard cyclist is either 0.75 m (Lisbon, Malmö, the Netherlands) or 1.00 m (Budapest, London, Germany). The 1.00 m-value appears to already include a certain buffer zone, while the 0.75 m does not. For example, in Germany and Budapest Table 3 shows that there is no buffer zone needed between two cyclists in contrast to most other countries.

In addition to the various possible types and locations of cycling infrastructures as introduced in Section 2, there is also a wide variety of possible adjacent users and usages. Providing sufficient space between cyclists and these adjacent usages is of highest relevance for both the objective and perceived safety of cyclists. These buffer zones between two cyclists, or cyclists and other users describe the required space for safe overtaking or passing events. The recommended widths of the different buffer zones in the researched guidance material are presented in Table 2.

Buffer zones between two cyclists range from 0.00 m to 0.50 m and are, together with the cyclist' space requirements, highest in London with 2.50 m for two cyclists and a buffer zone in between.

Buffer zones for the general traffic are given as approximate values which are to be applied in all cases or are dependent on speed. These buffer zones vary between 0.00 m for on-carriageway cycling facilities in Germany and 2.50 m for streets with speed limits above 50 km/h in Lisbon. Having no buffer zones particularly between cycling facilities on the carriageway and motorised traffic might lead to low distances between cyclists and the car overtaking the cyclist with negative impacts on objective and perceived safety.

Buffer zones to static obstacles describe the space required to manoeuvre along high kerbstones or other objects and are recommended in most researched guidance material; their size differs with the type and height of these obstacles. The minimum as well as the maximum value is given in Lisbon with 0.20 m to obstacles of low height and up to 1.20 m to built elements. Medium buffer zones to static elements seem to be 0.25 m to 0.50 m.

Buffer zones to parking/loading facilities are recommended in order to avoid dooring crashes with cars opening their doors while being passed by a bicycle. These vary between 0.25 m and 1.00 m with medium values of around 0.75 m which are applied most frequently.

Space requirements for the different street users taken together with the buffer zones result in the recommendations for the width of cycling facilities. In general, dedicated cycling facilities need to fit to the space requirements of minimum one cyclist and buffer zones to adjacent traffic or objects and must ensure sufficient space to allow passing events (one-way) or meeting events (two-way).

**Table 2.** Space requirement standard cyclist, recommended widths of buffer zones for cyclists in selected countries

and

cities.

**Table 3.**Recommended widths of cycle facilities in selected countries and

 cities.

*Sustainability* **2021**, *13*, 9560

Carriageway widths for bicycles in mixed traffic should be kept either low so as to cause cars to remain behind a bicycle when faced with oncoming traffic or kept wide so that cars can safely overtake cyclists even in the face of oncoming traffic. Intermediate carriageway widths that might lead to situations of doubt for car drivers on whether or not to overtake a bicycle should be avoided. This principle of either narrow or wide lanes (technically called profiles) for mixed traffic is recommended in references from London, the Netherlands and Germany. Transport for London [20] recommends avoiding carriageway width of 6.40 m to 8.00 m (doubled lane width) and FGSV in Germany [21–23] does not recommend values of around 6.00 m to 7.00 m. The differences in width result from different space requirements of standard cyclists, motorised vehicles and buffer zones. For example, and as mentioned above, in London the buffer zone between cyclists and general traffic is 0.50 m whilst there is no buffer zone in Germany (both countries consider 1.00 m as space requirement for one cyclist). CROW [19] recommends a narrow profile of 4.80 m and a wide profile of 5.80 m, which both are narrower than the recommendations in Germany and London; Budapest only recommends the wide profile. Lisbon recommends different carriageway widths for cycling in mixed traffic depending on the height of the adjacent buildings. Narrow profiles only work with low volumes of motorised traffic; higher volumes cause irritation and might eventually result in risky overtaking manoeuvres.

A similar approach is used for shared bus and cycle lanes in London and Germany as described in Table 3. London recommends the profile dependent on the number of buses or buses plus taxis per hour. In Germany, the width of bus/cycle lanes depends on the volume of cyclists. Budapest and Lisbon recommend general width of shared bus and cycle lanes.

The variety of recommended widths for dedicated cycling facilities is quite low in the researched guidance material. Widths range from 1.25 m to 2.25 m for one-way cycling facilities and are ≥2.00 m (London) or ≥2.50 m for two-way-facilities (Budapest, Lisbon, Malmö, The Netherlands, Germany).

Advisory cycle lanes are usually narrower than mandatory cycle lanes or cycle tracks/paths, because they are used if space is too narrow to provide a dedicated cycling facility, and in addition, cyclists are allowed to leave the advisory lane and to cycle in the carriageway, e.g., when overtaking other cyclists. Recommendations are given for the remaining carriageway width between two advisory cycle lanes because enough space has to be provided for motorised traffic to pass vehicles in meeting events.

Shared paths for cyclists and pedestrians are wider than dedicated cycling facilities because they have to accommodate the two user groups with substantial differences in their velocity.

#### **4. Operational Criteria for Selecting Suitable Types of Cycling Infrastructure**

Similarities were identified in recommended types and widths of cycling infrastructure in Sections 2 and 3. However, the criteria for their application differ greatly; specific criteria and thresholds are provided to select the type of cycling infrastructure for each application with substantial differences particularly in the used thresholds. In what follows, the approaches of each city/country are presented individually. At the end of this Section, Table 4 gives and overview of the selection criteria for all the researched guidance material.

Malmö only verbally explains the operational criteria for selecting suitable types of cycling infrastructure and gives the general recommendation for main streets to provide separated cycling infrastructure (cycle tracks/paths; usually two-way). Outside the main street network, cyclists cycle in mixed traffic. This distinction of main/lower level streets mainly refers to volumes of motorised traffic (max. 3000 vehicles/24 h), the speed of motorised traffic is not considered because speed limits in Malmö are generally low (max. 40 km/h).

**Table 4.** Speed and volume criteria for selecting cycle facilities in selected countries and cities.

\* may be supplemented by bike lane or advisory bike lane.

Volume and speed of motorised traffic are used as operational criteria for selecting a suitable provision for cyclists in all cities/countries using operational criteria. For example, Hungary and Germany use these two criteria and give recommendations for mixed traffic, advisory cycle lanes, mandatory cycle lanes and cycle lanes/tracks depending on volumes and speed of motorised traffic as shown below in Figure 1; Figure 2 show the approach for selecting cycle facilities in Hungary and Germany. The green box in Figure 1 describes situations with low speeds (≤30 km/h) and low volumes (≤10,000 vehicles/day) of motorised traffic where cyclists are guided in mixed traffic. The white area (described as joint traffic zone) is a sub-type of mixed traffic and is recommended up to speeds of 50 km/h.

The blue section describes provisions for cyclists on the carriageway with speed limits between 40 km/h and 60 km/h. Mandatory cycle lanes are recommended with volumes <15,000 vehicles/day and speed limits of 50 km/h. With higher volumes, a vertical or horizontal segregation is recommended (protected or raised cycle lane).

**Figure 1.** Selection plan for cycle facilities in Budapest ([17], p. 14).

**Figure 2.** Selection plan for bicycle facilities in Germany ([23], p. 1.9).

Separation (orange section) is clearly required with speed limits of 70 km/h. The standard solution for separation is bike paths—protected or raised cycle lanes are possible with low or medium volumes and high speeds.

The German guidelines use a similar approach (see Figure 2). Mixed traffic (denoted as Area I) is possible with a speed limit of 30 km/h and with maximum 8000 vehicles/24 h or with a speed limit of 50 km/h and with maximum 4000 vehicles/24 h without any additional measures.

Area II denotes the combinations of traffic volumes and speed that are suitable for advisory lanes or solutions where cyclists are allowed to cycle either on the carriageway or the sidewalk. These still shared cycling facilities are recommended up to 18,000 vehicles/24 h combined with speed limits of 30 km/h or 8000 vehicles/24 h combined with speed limits of 50 km/h. The allowed volumes of motorised traffic at specific speed limits are almost twice as high as the allowed volumes in Hungary.

A clear recommendation to physically separate cyclists from motorised traffic does not exist in Germany as both, cycle lanes and cycle tracks/paths, are recommended in Area III and Area IV.

The Lisbon guidelines also consider volumes and speed limits of motorised traffic but add the street category as third criterion as shown in Figure 3. Lisbon gives the strictest recommendation on guiding cyclists in mixed traffic with maximum speed limits of 30 km/h and volumes up to 3000 vehicles/24 h on local streets. Alternatively, contra-flow cycle lanes in one-way streets may be implemented. Mandatory cycle lanes are recommended on local streets with 50 km/h speed limit. If the volumes exceed 5000 vehicles/24 h, cycle tracks are required.

**Figure 3.** Selection plan for bicycle facilities in Lisbon ([18], p. 12.5).

On distributional streets, elevated lanes (optionally on intermediate level between carriageway and sidewalk) are recommended with speed limits of 50 km/h and volumes up to 10,000 vehicles/24 h. Higher volumes require the implementation of cycle tracks.

At higher level streets (with speed limits ≥50 km/h), cycle tracks are generally recommended. CROW [19] recommends cycling facilities according to the volume and speed of motorised traffic, the road category and the cycle network category which represents the volumes of cyclists (see Figure 4). Recommendations for mixed traffic in the Netherlands are with maximum 30 km/h and 5000 vehicles/24 h almost as strict as in Lisbon. With high volumes of cyclists (>2000 cyclists/24 h) and low volumes of motorised traffic, a cycle street is preferred over standard mixed traffic solutions to emphasise the dominance of cyclists. Cycle paths as separated facilities are recommended for speed limits of 50 km/h onwards (independent of volumes of motorised traffic) or with lower speed limits and high volumes of motorised traffic or high volumes of cyclists.

**Figure 4.** Selection plan for bicycle facilities in built-up areas in the Netherlands ([19], p. 102).

Transport for London (TfL) developed recently a new approach to decide whether or not cyclists can be mixed with motorised traffic [24]. TfL defines target green levels and minimal requirements for six criteria and a scheme to decide which level has to be met for each of these criteria in different combinations, these are summarised in 4 scenarios. Target green levels are defined as:

The scheme in Figure 5 illustrates scenarios that are suitable for guiding cyclists in mixed traffic. Scenario 1 is the preferred one when all target green levels are met. Higher volumes of motorised traffic or higher speed can both be compensated by defined combinations of criteria for which the target green levels have to be met as the minimum. In Scenario 2, too high volumes of motorised traffic are compensated by sufficiently low speed and proportions of HGV combined with at least two out of three of the remaining criteria meeting target green levels. Scenario 3 describes how too high speed can be compensated. When volumes and speed of motorised traffic meet target green levels, two out of four of the other criteria have to meet the target green level. Safety at junction has to be ensured in in all cases (turning risk): Measures for mitigating turning risks are required if safety issues exist.

**Figure 5.** Scenarios for guiding cyclists in mixed traffic in London ([16], p. 6).

Table 4 summarises the identified operational criteria and target values for deciding on suitable types of cycling facilities in the form of a table the crosses the two criteria that are consistently applied in all references, this is volumes and speed of motorised traffic. Volume of cyclists is also included in the table as this is a speed limit concerned criterion (even though is just applies in the Netherlands). Further criteria are only used in some of the references and are not included in the table; these are explained in the descriptions and figures above. NACTO [15] does only give one operational criterion on the suitability of mixed traffic solutions, this is maximum 3000 vehicles/24 h and 30 km/h and is therefore not included in the table.

#### **5. Summary of Practices in Providing for Cyclists**

The researched material shows a high variety in cycling facilities and criteria for their operation. Infrastructure for cyclists ranges from integrated solutions with cyclists in mixed traffic or on cycle streets to fully separated cycling facilities off the carriageway, e.g., on cycle paths. Overall, more than 10 variations of infrastructure for cyclists were identified within the seven countries/cities.

As mixed traffic and cycle tracks/paths are defined in all cities and mandatory cycle lanes are recommended in all guidance material besides Malmö, these three provisions can be summarised as standard cycling infrastructure types within the researched countries and cities. Within these types the application of mixed traffic is typically used for streets with low volumes and speed of motorised traffic, cycle lanes and tracks/paths are more likely on streets with higher volumes and speed of motorised traffic.

Recommendations for accommodating cyclists in mixed traffic together with motorised vehicles in the carriageway are the most stringent in the Netherlands and Lisbon who only allow mixed traffic with speed limits below 30 km/h [18,19]. In Budapest and Germany, mixed traffic (including advisory cycle lanes) is possible up to speed limits of 50 km/h [17] or 70 km/h [23].

Bicycle streets are a special type of mixed traffic and recommended in the Netherlands for streets with high cycling volumes to emphasise the dominance of cyclists [19]. Carriageways with cyclists riding in mixed traffic should either be narrow so as to force cars to remain behind a bicycle when faced with oncoming traffic, or kept wide so that cars can safely overtake cyclists even in the face of oncoming traffic.

Dedicated cycling facilities are recommended for high volumes of motorised traffic and high speed limits. Cycle tracks/paths and cycle lanes bring vertical and/or horizontal separation. Budapest and Lisbon recommend mandatory cycle lanes with intermediate volumes/speed of motorised traffic and cycle tracks/paths with higher volumes/speed of motorised traffic [17,18]. The Netherlands and Malmö generally recommend off-carriageway cycle tracks/paths for main streets [19,21]. The German recommendations equally recommend cycle lanes and cycle tracks/paths for streets with high volumes of motorised traffic and speed limits [23].

The recommended widths for dedicated cycling facilities range from 1.25 m to 2.25 m for one-way cycling facilities and are ≥2 m for two-way-facilities. It tends to be higher in countries with a well-established cycling culture such as the Netherlands and Sweden compared to starter countries such as Lisbon/Portugal.

#### **6. Comparison of Guidance on Cycling Facilities with Literature on Determinants of Cyclist Safety and Comfort**

The assessment of this diversity in recommendations for types of cycling infrastructures and criteria for their selection against the relevant criteria of (objective and perceived) safety and comfort proves to be difficult for at least two reasons: (1) The cause-effect chain from the characteristics of cycling facilities in individual street sections to travel behaviour and cycling choices is complex. Decisions about travel behaviour are shaped by various influences and the characteristics of single street sections is only one of them (see, e.g., [24] for the relevance of seamless cycling networks and safe intersections for successfully providing for cyclists). (2) The literature on the influence of the type of cycling infrastructure at street sections on safety is fragmented and hardly allows to draw general conclusions.

Mueller et al. [1] demonstrate the relationship between the length of cycling facilities in a city and the modal share of cycling without any consideration of the type of cycling facilities. Le et al. [25] report similar findings and Buehler and Pucher [26] find comparably high influences of cycle lanes and cycle paths on bicycle commuting in American cities. The TEMS tool (http://tems.epomm.eu/ accessed on 13 July 2021) shows that cycling shares are highest in Dutch and Swedish cities—two countries that favour separating cyclists from motorised traffic. At the same time, the TEMS tool shows substantial differences in modal shares of cycling within countries even when these have guidelines that are valid at national level such as Germany or Hungary.

Literature on infrastructural determinants of cycling safety consistently shows that higher speed (allowed or driven) leads to higher severity of crashes and in some studies also to higher crash numbers [27–30] and presence of parking increases crash risk [30–32].

Crash numbers are higher for streets with cycling facilities [33]. The main reason for this is higher car and cycle traffic volumes and speed in such streets. Differences in crash risks per car volumes are less consistent in the researched references. Lusk et al. ([34] see also [35]) find higher risks for on-carriageway cycling facilities compared to cycle tracks. Teschke et al. [31] find higher risks for sections without any cycling facility compared to sections with cycle lanes. Harris et al. [29] find lower risks for sections with cycle tracks compared to advisory lanes and mixed traffic. Canadian studies find higher risks for cycle tracks compared to cycle lanes [36,37].

The literature review on perceived safety supplements the findings of the risk analysis. User surveys show that perceived safety is very low when cyclists are guided in mixed traffic [38–41]. The safety perception is even lower with high speed limits [38,41], the presence of parking [38–40], high volumes of motorists or a high proportion of heavy vehicles or presence of buses [38,41].

On streets with cycling infrastructure, users generally prefer facilities off-carriageway over on carriageway facilities [38,39,41]. However, well-designed and protected cycle lanes (with coloured surface, buffer elements and sufficient width) can achieve a similarly high level of perceived safety as cycle tracks [38]. In a mental mapping study in Ireland, separation of cyclists was found to have the greatest impact on perceived safety (compared to motorists' volumes, width of infrastructure, number of junctions and parking) [42].

Some general conclusions can be drawn besides the fragmented character of the literature. Slow speed increases safety and also the willingness of people to cycle in the streets. Study design, specific location and infrastructure design matter when comparing the safety of on- and off-carriageway facilities. Cycling facilities are safer and perceived safer than no cycling facilities and there is the tendency of better safety for separated cycling facilities compared to unprotected on-carriageway facilities such as cycle lanes. The number of cars and also cyclists consistently matters [43]. Higher car volumes increase crash risk for cyclists, the safety-in-numbers effect leads to relatively lower risks for cyclists with increasing cycling volumes.

#### **7. Recommendations on Providing for Cyclists in Future Guidelines on Urban Street Design**

Based on the insights gained from summarising the various guidance materials on cycling provision, the following recommendations were developed:

Keep it simple: "Starter countries" in terms of cycling tend to offer many more types of cycling facilities in their guidance materials than countries with a longer history in cycling provision. A variety of solutions might be necessary in starter countries because the optimal solutions might not have enough political support (e.g., would require taking too much space from cars). This is a critical point because (potential) cyclists are not familiar with participating in traffic as cyclists nor are car drivers and other street users used to cycling infrastructure or expect cyclists in the streets. With this in mind, the first recommendation is to keep cycling provision simple, wherever possible. The three basic options for accommodating cyclists in the streets are a solid basis and, in most cases, sufficient; these are (1) mixed traffic, (2) on-carriageway mandatory cycle lanes and (3) off-carriageway cycle tracks/paths. Too many types of cycling infrastructure might cause confusion for users. Even though there are many different types of cycling infrastructure available, this disadvantage might outweigh the advantage of having the opportunity to provide tailor-made solutions for each design task.

Mixed traffic or dedicated cycling facilities: The decision between accommodating cyclists in mixed traffic with motorised vehicles on the one hand and dedicated cycling facilities on the other is of special importance. Speed of motorised cars of maximum 30 km/h and low volumes of motorised vehicles appear to be the two key deciding factors. Dedicated cycling facilities should be provided if either of these two is exceeded. Bicycle volumes should also be considered if these reach relevant levels. Lane widths (profiles) for cycling in mixed traffic should be either narrow or wide in order to clearly indicate whether or not the overtaking of bicycles is safely possible for cars. Narrow lane widths

seem to be more suitable as these support low speed for all street users. Bicycles should be prioritised over motorised traffic, particularly if their current or expected number exceeds car volumes, e.g., by providing bicycle streets.

Dedicated cycling facilities on or off the carriageway: Once the decision for a dedicated cycling facility has been made, these might be placed on the carriageway as cycle lanes or off the carriageway as cycle tracks/paths. Both of these options have pros and cons which can be evaluated on a case-by-case basis or addressed in a general manner as is carried out in Malmö and the Netherlands for off-carriageway cycle tracks/paths. Both options are good choices for objectively safe and convenient cycling networks if these are sufficiently wide and well designed. Cyclists feel safer on off-carriageway or at least protected facilities and although the scientific literature does not indicate a clear risk reduction for cycle tracks, elevated or protected design solutions are recommended when traffic volumes or speed limits are high. Solutions for street sections always need to fit with the solutions at the adjacent junctions as these are very important for cyclists' safety and comfort.

Mixing pedestrians and cyclists: This is a popular solution for limited space and high volumes (and speed) of motorised traffic but might lead to conflicts between pedestrian movement and place activities and cyclists. Dedicated and separated facilities for cyclists and pedestrians should therefore be implemented whenever possible, even if that requires taking space from motorised traffic.

Width of cycle lanes and tracks/paths: With high cycle volumes, it is desirable to offer a width of minimum 2.00 m in one direction to allow passing events without leaving the cycle lane/track. Narrower facilities should only be provided where a low number of cyclists is expected (e.g., due to alternative attractive routes in the network). Wide facilities might demand physical separation to discourage other road users from driving or parking within the cycle infrastructure. Buffer zones to adjacent usages particularly for parking are paramount for safe cycling.

Future needs: In general, cycling infrastructure should cover current and future needs. Due to an increasing number of cargo bicycles (higher space requirements) and electric bicycles (higher speeds) and the fast developments in Personal Light Electric Vehicles (PLEV), cycling infrastructure should provide enough space for non-standard and standard users. One such example would be the provision of lane widths which make is easy for faster cyclists to pass slower cyclists even though the slower bike has extended dimensions. Cycle Highways are another example as a new trend in cycling practice in planning [44].

#### **8. Summary and Conclusions**

This study provides a comprehensive international overview of guidance material for cycling facilities. It shows similarities and differences in the practice of cycling provision. Some general trends could be identified. "Cycling countries" such as the Netherlands and Malmö/Sweden use fewer types of cycling facilities, are strict in mixing cyclists and motorised traffic only in streets with low speed and volumes of motorised traffic and recommend greater widths for dedicated cycling facilities. At the same time, also substantial differences emerged. For example, Germany treats mandatory cycle lanes in the carriageway equally in terms of operational criteria as separated cycle tracks/paths. Malmö uses mainly two-way cycle tracks/paths on their main roads, these cycling facilities should be avoided following the recommendations in German guidelines for cycling facilities. More empirical evidence on the effects of the different types of cycling facilities would help to advance guidance material towards safe and comfortable solutions in each specific case study. These investigations should include both street sections and junctions as the latter are even more decisive for cyclists' safety compared to street sections.

**Author Contributions:** Conceptualisation and methodology, B.S., R.G. and R.W.; data collection and curation, B.S., R.G., C.K., R.B., P.S., J.W. and S.H.; writing—original draft preparation, B.S. and R.G.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was also supported by the European project Multimodal Optimisation of Roadspace in Europe (MORE), which has partners in Budapest, Constanta, Lisbon, London and Malmö. MORE (https://www.roadspace.eu/ accessed on 13 July 2021) is a 3-year project, which receives funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 769276.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.

**Acknowledgments:** The authors acknowledge the MORE partners' support in all steps of the project. Figure 2 is taken from FGSV, 2006. It is quoted with permission of Forschungsgesellschaft für Straßenund Verkehrswesen e.V. (Road and Transportation Research Association). Decisive for the use of FGSV books is the latest edition, which is available from FGSV Verlag (FGSV Publishing House), Wesselinger Str. 15-17, 50999 Köln, www.fgsv-verlag.de (accessed on 13 July 2021). Figure 4 is taken from CROW, 2016 and is quoted with permission of CROW.