**1. Introduction**

Lane departure crashes are one of the most common types of road accidents. In the US alone, 51% of all fatal accidents are caused by lane departure, i.e., a vehicle crossing the edge or the centre line [1]. There is a variety of contributing factors involving the driver, the vehicle, the road and its surroundings (the environment) but it is proven that rural roads with low traffic volume and density are more likely to contribute to road departure accidents [2]. This is mainly due to higher travelling speed, distracted driving and/or fatigue. Different safety measures have shown positive results in decreasing lane departure accidents [3–5], yet the overall problem still exists.

A potentially promising solution to the aforementioned problem lies in automated driving and Advanced Driver Assistance Systems (ADAS), which perceive the static and the dynamic content of the environment around the vehicle and thus assist the human driver in driving. An important task during environment perception is lane detection needed for Lateral Support Systems (LSS), which comprise of lane departure warning and/or lane keeping assistance. The main purpose of LSS is to prevent road accidents caused by road departure or entrance in the lane of other vehicles. Due to high fatality

**Citation:** Babi´c, D.; Babi´c, D.; Fioli´c, M.; Eichberger, A.; Magosi, Z.F. A Comparison of Lane Marking Detection Quality and View Range between Daytime and Night-Time Conditions by Machine Vision. *Energies* **2021**, *14*, 4666. https:// doi.org/10.3390/en14154666

Academic Editors: Guzek Marek, Rafał Jurecki, Wojciech Wach and Thanikanti Sudhakar Babu

Received: 10 June 2021 Accepted: 30 July 2021 Published: 1 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/).

rate in such accidents, the use of different LSS could significantly improve the overall road safety [6–9].

In literature, two main technologies for LSS are reported: LIDARs (Light Detection and Ranging) and vision-based cameras. The main advantage of LIDAR is the fact that it uses an active light source and thus does not rely on the variabilities associated with external/natural lighting as do regular vision-based cameras [10]. However, LIDAR technology is usually used for adaptive cruise control, while lane detection is only partially feasible and mainly used in expensive demonstrator vehicles for highly automated driving [11]. Therefore, current market-ready systems use passive vision-based cameras and image processing to collect and analyse the data from roads [12]. In general, camera-based lane detection starts from image pre-processing which includes different corrections of the collected image (such as exposure correction and shadow removal) and feature extraction. This is then followed by feature detection and model fitting, and then time integration to keep temporal and position consistency [13].

The proper function of LSS depends on several factors [11,14,15]: the quality of the camera (focal distance and camera velocity), condition, colour, width and visibility of lane markings (daytime visibility, night-time visibility—retroreflection and contrast to pavement), lane marking configuration (full/dashed, length of dashed lines), driving speed, weather conditions, general visibility of the environment, sun direction, pavement characteristics (type, condition and texture), geometry of the road, type of road edge (structured/unstructured) and combinations of the above factors.

Several studies have investigated how lane markings' characteristics affect the accuracy of lane detection under different conditions. One of the first such studies was conducted in Sweden in 2010 with the aim of testing various types of lane markings (flat/profiled, new/existing) under different weather and lighting conditions [16]. The study concluded that in dry daytime conditions, the luminance coefficient must be at least 5 mcd/lx/m2 higher than the road surface and that it should be at least 85 mcd/lx/m2. Furthermore, the study also found that roads wider than seven meters need to have a centre line in order for LSS to become active. Finally, the study highlighted the importance of increased visibility of lane markings in wet and rainy conditions. In 2016, a research was conducted with the aim of identifying the effects of lane markings' characteristics (width, colour and retroreflectivity) on the performance of a machine-vision system [17]. The study concluded that the view range of the investigated machine-vision (Mobileye) is between 6–18 m in front of the vehicle and that, at night-time, the retroreflectivity of lane markings affected the reading quality. Namely, lane markings with higher retroreflectivity increased the reading level and confidence. Also, wider lane markings (15 cm width) were read better when compared with narrower markings (10 cm width), regardless of stripe colour. Similar results were obtained in a 2017 study [18]. The results indicated that the machine-vision (Mobileye) detection of lane markings generally increased with the increase of retroreflection and contrast ratio. However, the authors highlighted that factors such as light bloom from a low-angled sunlight or visual occlusion from rain, snow, or fog may also influence the detection and readability of machine-vision. Furthermore, such systems generally detect markings with the minimal retroreflectivity of 100 mcd/lx/m2 but do not necessarily provide the strongest detection. An extensive study, which consisted of interviews of stakeholders and on-road and off-road testing, was conducted in Australia in order to determine the implications of road markings for machine vision [11].  The authors used several vehicles and a Mobileye camera to test lane detection depending on different scenarios. Based on data analysis, it was concluded that machine-vision detection of solid lines is "better" when compared to dashed lines with

same characteristics (equal width, brightness and maintenance). Weather conditions also impacted machine-vision readings differently. Namely, minimal ambient lighting (such as streetlights or low-angled sunlight) may improve the contrast ratio due to reduced specular diffusion and, thus improve line detection. On the other hand, with excessive ambient lighting, machine-vision systems can suffer from 'light bloom'. Furthermore, the contrast ratio for night-time visibility of between 5-to-1 and 10-to-1 between lane markings and the surrounding substrate is needed for proper functioning of the machine-vision system. Also, lane detection during the day was generally less effective than at night-time due to the complexity of visual clutter evident during daylight hours and the fact that retroreflective properties of well-maintained lane markings provide greater contrast during night-time. In addition, the study found that several other factors, such as driving speed, marking width, maintenance practices etc. influence the accuracy of machine-vision.

Most recently, a researcher at the Department of Civil Engineering and Architecture at the University of Catania used Automatic Road Analyzer (ARAN) and Mobileye 6.0 system to investigate how different road factors (road characteristics and conditions) impact the performance of the LSS system [19]. The ARAN was used to obtain measures of road geometric characteristics (cross section, gradients, horizontal and vertical alignment) which were then synchronised with the Mobileye. In addition, the luminance coefficient of the lane marking in diffuse lighting conditions (Qd) was detected with a portable retroreflectometer. Based on the data analysis using a Decision Tree Method, authors concluded that when daytime visibility (Qd) of road markings is lower than 153 mcd/lx/m2, the probability of LSS failing rises to 11.4% for the calibration sample and 14.35% for the validation sample. Also, curved road sections (with R < 141 m) showed a higher percentage of faults than the average 3% in the test conditions. On the other hand, the average driving speed did not result in any significant changes in LSS accuracy. Overall, the results suggest that a Qd higher than 153 mcd/lx/m2 improves the detection of lane markings using a Mobileye lane detection system.

Based on literature findings, one can conclude that the function of LSS is influenced by a number of factors and their interaction. However, it is still largely unknown to what extent each factor influences LSS, precisely due to their high number and their interaction (one factor may significantly influence another one in certain conditions). The aforementioned can be seen from the example of "visibility factor", i.e., lane detection between daytime and night-time. Several studies indicated that the accuracy of lane detection varies between day and night-time, however it is still largely unknown to what extent these differences go. For this reason, the aim of this study is to conduct on-road tests in order to determine and compare the detection quality and view range of the machine-vision system during dry daytime and night-time conditions. Based on the aforementioned aim and literature review, the hypotheses of the study are as follows:

The results of the study are important for two reasons. First, they provide a valuable input to researchers and developers regarding the "real-world" functioning of machinevision lane detection. The insight into the variations of lane detection accuracy in different visibility conditions may help further development of such systems. Second, the results may help road authorities in optimizing the quality performance of road markings. Namely, it is still not entirely clear what the minimal quality requirements for road markings are in order to provide adequate accuracy of machine-vision. However, knowing which visibility conditions are more problematic for machine-vision may help road authorities in prioritizing maintenance activities as well as defining minimal visibility levels of road markings.

The manuscript is structured in five main sections. Section 1 presents the research problem and literature findings related to the impact of road markings quality on LSS. Section 2 describes the research equipment, testing procedure, road sections chosen for the purpose of this research and data analysis. The results of on-road tests are divided into two subsections presented in Section 3: Quality of lane markings' detection and view range of lane markings. In Section 4 the obtained results are discussed and compared to findings from previous studies, including limitations and suggestions for future studies. The last section (Section 5) presents the conclusion of the study and provides potential practical application for the obtained results.

### **2. Materials and Methods**

#### *2.1. Apparatus*

The data related to lane detection was recorded using Mobileye 630 system implemented in the testing vehicle (BMW640i) of the Institute of Automotive Engineering, Graz University of Technology (Figure 1). The system is developed by a leading supplier of camera systems for ADAS and it was previously used in several studies [11,14,17,19]. The Mobileye 630 system uses a digital camera with the 38 degrees horizontal and 28 degrees vertical field of view located behind the front windshield inside the vehicle. Using image processing chips, the camera enables high-performance real-time image processing (15 frames per second) of different objects on roads such as lane markings, pedestrians etc. The system, among others, conforms to the Directive 72/245/EEC for electronic equipment which can be built in road vehicles and enables extraction of recorded data for further processing. For the purpose of this study, we recorded the data related to the type of detected longitudinal marking (continuous or dashed), approximate marking width, view range and the quality of the marking both for middle and edge lines. The vehicle was also equipped with a precise measurement system to record the vehicle's trajectory by a combination of GPS localization (Novatel OEM-6–RT2 receiver) and inertial measurement unit (GENESYS ADMA G-III).

**Figure 1.** Testing vehicle with Mobileye 360 implemented behind the front windshield inside the vehicle.

#### *2.2. Test Road Sections and Procedure*

The study was conducted on four rural road sections in Croatia in total length of 120.8 km. The roads were two-way roads with 3.5 m lane width and low traffic volumes. Three road sections were marked with the middle line and partially with edge lines while the fourth road had only the middle line. All markings were white, 15 cm wide and made from solventborne paint (Type I). The main characteristics of the road sections are presented in Table 1.

**Table 1.** Characteristics of test road sections.

The roads were selected based on the fact that they are rural with low traffic volumes. Rural roads with low traffic volumes have higher risk of road departure accidents [2] and thus the importance of LSS is increased. Also, roads were selected since they have the recommended width of lane markings for LSS [20–22] and on the majority of their length, there is no road lighting. Road lighting was present only on short sections located in populated areas. However, these sections were excluded from the analysis (see Section 2.3).

Each road was "measured" twice: once during daytime and once during night-time. The measurements for night-time conditions were conducted on 21 September 2020 and on 22 September 2020 for daytime conditions. The measurements were done between 10:15 h and 13:00 h during daytime and between 19:20 h and 22:20 h during night-time. In both conditions, the weather was dry and the sky clear. The driving speed was in accordance with the speed limit and differed between 60 km/h and 80 km/h. In this way, we tried to control the impact of speed on the detection of markings since literature suggests that speed has a varying impact on machine-vision (some improve at higher speeds, some degrade) [11].


**1. Introduction**

The cation-independent mannose 6-phosphate/insulin-like growth factor 2 receptor (CI-M6P/IGF2R, hereafter IGF2R) is a type-1 transmembrane glycoprotein consisting of a large N-terminal extracytoplasmic domain, which allows it to bind to a wide variety of ligands [1,2]. The IGF2 and M6P ligands [3–5] of IGF2R have distinct but important roles in normal development and mesoderm differentiation [6]. Many studies have demonstrated the suppression action of IGF2R on insulin-like growth factor 1 receptor (IGF1R) signaling by scavenging extracellular IGF2 [7]. Furthermore, several lines of evidence demonstrate that IGF2 is highly expressed in rodent embryos, where it functions as an embryonic growth factor, while its amount is diminished at birth [8]. Smith et al. recently showed that a transgene-induced overexpression of IGF2 blocked programmed cell death, one of the main pathological features of cancer [9]. Furthermore, in some cancers such as mammary tumors, IGF2R behaves as a tumor suppressor gene [10], whereas in other cancers such as cervical tumors or glioblastomas, IGF2R acts as an oncogene [11,12]. Thus, these two traits of IGF2R might depend on cell type. Interestingly, cervical tumors and glioblastomas have common mesenchymal founders, namely myofibroblasts [13], which are also involved in muscle disease. Muscle repair is a complex and tightly regulated event that recruits different cell types, starting from macrophage and lymphocyte consecutive involvement and terminating with satellite cell (SC) activation and differentiation [14]. Among the common hallmarks of muscular dystrophy are the infiltration of immune cells into skeletal muscle fibers, and fibrotic cell proliferation [15–18].

Impaired muscle regeneration with SC pool exhaustion is considered an additional pathological feature of Duchenne muscular dystrophy (DMD) [19]. The main biological function of IGF2R is the suppression of IGF1R signaling via the deprivation of extracellular IGF2 ligands. Some studies have explained the tumor suppressive functions of IGF2R by its negative regulation of the oncogenic IGF2–IGF1R signal axis [2]. However, in muscle tissues, the IGFs bind to the IGF1R leading to conformational changes and activation of its tyrosine kinase activity, promoting muscle regeneration [20]. In injured tissues, IGF1 is secreted by SCs and mediates muscle-derived stem cell proliferation and differentiation into myoblasts, which contribute to myofiber formation for restoring normal tissue structures [21]. It has been demonstrated that prolonged expression of IGF1 causes an exaggerated protein synthesis and is responsible for muscular hypertrophy, by increasing myofiber diameter [22–25], and also preventing muscle atrophy in cases of cachexia or chronic inflammation [26]. Thus, tissue-specific IGF1 upregulation rises to the challenge of counteracting the development of muscular dystrophy.

Similar to IGF1, autocrine IGF2 is fundamental to mediate the differentiation of SCs in vitro, but little is known about its role in skeletal muscle development and regeneration in vivo [27]. The expression profile of *IGF2* is quite complicated as it depends on multiple-promoter activation, alternative translation initiation and messenger RNA (mRNA) stability. IGF2R functions as a negative regulator of IGF2 in embryonic skeletal muscles and modulates the amount of systemic IGF2 by inducing its degradation through lysosomes and clearance from the circulation [28,29].

Even if the signaling cascade that regulates the activation of IGF2 at muscular level is not determined, it has been shown that the phosphatidylinositol 3-kinase (PI3K)–the serine/threonine protein kinase B (AKT) pathway is the IGF2 downstream pathway contributing to mammalian target of rapamycin (mTOR) functions [30]. A study by Ge et al. [31] showed that the synergic activity of mTOR with miR-125b regulated *IGF2* production both transcriptionally and post-transcriptionally, and that these events positively influence myogenesis.

In muscle pathology and ageing contexts, where there is a predominant switch of the fiber phenotype from fast to slow [32,33], IGF2 was also able to orchestrate the development of fast myofibers by acting as a twitch motor unit during secondary myogenesis. The modulation of IGF2 expression had a dramatic impact on the amount of fast myofibers in the respiratory (intercostal and diaphragmatic) muscles, likely lessening cardio-respiratory dysfunction related to DMD. IGF2 targeting was suggested as a feasible therapeutic strategy, since IGF2 has a small size and consequently it could be easily distributed to a skeletal muscle target [34]. However, the IGF2R signaling pathways involved in muscle repair and disease remain to be identified.

#### **2. Structure, Genomic Organization and Gene Imprinting of IGF2R**

Imprinting genes are those whose expression is determined by one's parents. They occur in discrete clusters that are regulated by DNA elements called imprinting control regions (ICR). The two copies of one imprinted gene are characterized by methylation of cytosine–guanine base pairs. This modification originates in the paternal germ cells—after adding a methyl group, the chromatin becomes inaccessible to transcription machinery, so the gene is silenced. The IGF2/H19 locus is one of the imprinted gene clusters in human chromosome 11p15.5 or mouse distal chromosome 7 and plays a primary role in muscle cell development [35]. The expression of this cluster is regulated by a distant enhancer downstream of the H19 coding region. A recent study presents paxillin (PXN), a focal adhesion protein, as a transcriptional regulator of the IGF2 and H19 genes; in particular, it has the opposite effect on the activity of the IGF2 and H19 promoters [36]. The knockdown of PXN in human HepG2 cells allows for an increase in the activity of the H19 promoter and at the same time a decrease in the activity of the IGF2 promoter [36]. In a recent study, it was demonstrated that the loss of imprinting (LOI) in a mouse model of Beckwith–Wiedemann syndrome (BWS) results in impaired muscle differentiation and hypertrophy. It was also proposed that there is a signaling pathway in which IGF2 overexpression allows for an overactivation of mitogen-activated protein kinase (MAPK) signaling, while a loss of H19 long non-coding RNA (lncRNA) prevents the regulation of p53 levels, resulting in reduced AKT/mTOR signaling [35].

The *IGF2R* is an example of differential imprinting in the human and mouse genomes; the *IGF2R* is repressed on the paternal chromosome in the murine genome, but the same gene is expressed from both alleles in humans. For humans, the study was conducted on several tissues—adult liver, placenta, fetus, kidney, adrenal, brain, intestine, heart, tongue, skin and muscle: in all these samples both IGF2R alleles were expressed more or less at the same level. Accordingly, it was established that this character is subject to Mendelian segregation, escaping imprinting. As a plausible explanation for this phenomenon, Kalscheuer et al. suggested that the stages of initiation and maintenance of imprinting could be under the control of trans-acting factors that could act differently in mice compared to in humans [37]. They also hypothesized an alternative explanation based on the structural difference of the mouse and human *IGF2R* genes, as an "imprinting box" was previously discovered that could be modified by methylation in the female gamete and allowed maternal expression [37]. The *IGF2R* gene is located on mouse chromosome 17: it is composed of 48 exons and encoded for a 2482-amino acid protein. Exons 1–46 comprise the extracellular part of the receptor, while the transmembrane portion and the cytoplasmic region are located, respectively, on exon 46 and 46–48 [38].

### **3. IGF2R-Dependent Pathway**

M6P/IGF2-R lacks intrinsic kinase activity, and the role of G-proteins in its downstream pathway has been investigated. Functionally, G-proteins are a class of proteins that interact with multi-spanning receptors (seven transmembrane receptors or heptahelical receptors). Some studies have speculated that M6P/IGF2-R, although characterized by a single-spanning structure, might initiate signaling cascades through G-proteins in a direct or indirect manner. It is well known that the pertussis toxin exerts its activity by binding and blocking the activation of the α subunit of the Gq/11-protein [39]. El-Shewy et al. showed that the use of this toxin is able to inhibit the function of M6P/IGF2-R, therefore suggesting the involvement of G-proteins in the downstream pathway of M6P/IGF2-R. Pre-treatment of Human embryonic kidney 293 cells (HEK-293) cells with the pertussis toxin can significantly reduce the level of extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation resulting from the interaction of IGFs with their receptors. The indirect activity of these receptors is carried on through parallel activation of G-protein-coupled receptors (GPCR). They also observed that the administration of IGF1 and IGF2 ligands activates sphingosine kinase (SK) 4, which is translocated from the cytosol to the plasma membrane. There, it promotes an increase in extra- and intracytoplasmic levels of sphingosine-1-phosphate (S1P). S1P's interaction with its G-protein-coupled receptor represents a general mechanism for indirect G-protein-dependent signaling of M6P/IGF2-R resulting in ERK1/2 phosphorylation [40]. Conversely, the direct activity of IGF2R and G-proteins was hypothesized by Nishimoto et al. [41,42]: based on their observations, a region of the cytoplasmatic domain of M6P/IGF2-R may contain aminoacidic residues (2410–2423) that directly bind and activate G-proteins, in particular, Gi-2. This is supported by evidence that the use of both human and rat antibodies targeting aminoacidic residues is able to inhibit the activation of Gi-2 resulting from M6P/IGF2-R stimulation.

#### **4. Functions of IGF2R**

#### *4.1. IGF2R Expression Levels Regulate Cardiac Development and Remodeling*

The expression of the *IGF2R* gene is particularly abundant in embryo hearts. IGF2R-deficient mice display dramatic cardiac dysfunction and heart failure development. In adults, low levels of IGF2R expression lead to heart disease and apoptosis in cardiac myocytes [43], while upregulation determines myocardial infarction, remodeling [44] and hypertrophy [45]. In particular, the IGF2R activates phospholipase C (PLC) through the heterotrimeric G-protein-coupled receptor: this interaction is mediated by αq G subunits (Gαq) that in turn allow the function of different enzymes such as the protein kinase C-α (PKC-α), Ca2<sup>+</sup>-calmodulin-dependent protein kinase II (CaMKII) and ERK kinase—all upregulated in cardiac hypertrophy [46]. Alternatively, the modulation of IGF2R can enhance cardiomyocyte apoptosis and cardiac contractility by inhibiting protein kinase A (PKA) phosphorylation [47]. A recent study showed that IGF2R expression is negatively controlled by the cardioprotective heat shock transcription factor 1 (HSF1). Antitumor drugs such as doxorubicin (DOX), meanwhile, lead to high levels of IGF2R expression in cardiomyocytes, through a decrease in HSF1, and trigger cardiac apoptotic processes [48]. IGF2R expression in the heart may also mediate increased sizes of cardiomyocytes, in a manner dependent on PKA activation, and mediate atrial natriuretic peptide (ANP), calcium-dependent channels (SERCA) and phospho-troponin I signaling, as described recently by Wang et al. [49].