Over recent decades, traffic density has continuously increased. In many metropolitan areas, the road network has reached its limit and cannot easily be extended to meet the growing traffic demand. Consequently more and more drivers are stuck in traffic, causing billions of dollars worth
Over recent decades, traffic density has continuously increased. In many metropolitan areas, the road network has reached its limit and cannot easily be extended to meet the growing traffic demand. Consequently more and more drivers are stuck in traffic, causing billions of dollars worth of economic damage. Recently, a new monitoring paradigm has drawn the attention of the research community: floating car data directly retrieved from private vehicles. Anonymous information on the current speed and position is sent at regular intervals to a centralized server where it is aggregated to obtain a global picture of the traffic conditions in real time. It is important to take in account that the literature provides a lot of different methods to estimate the travel time in an extra-urban environment (e.g. highway) but unfortunately all these methods are not directly applicable in an urban setting due to the complexity of the environment itself. The aim of this project is to exploit the collected data (discovering new models applicable in the urban environment) and design dynamic routing algorithms, which take into account changing traffic conditions and predictable traffic patterns to provide the best possible equilibrium for the traffic and thus reduce individual and global traffic delays in urban environments.
Luxembourg SUMO Traffic (LuST) Scenario
In order to evaluate the different dynamic routing algorithms proposed in fAVoR, the first step is to use a vehicular traffic simulator and an appropriate scenario. Various vehicular communities ranging from telecommunication to infrastructure are working on problems related to traffic congestion, intelligent transportation systems, and mobility patterns using information collected from a variety of sensors. Many mobility simulators are available, but a common problem is finding a realistic traffic scenario. The aim of this project is to provide a scenario able to meet all the common requirements in terms of size, realism and duration, in order to have a common basis for the evaluations. In the interest of building a realistic scenario, we decided to start from a real city with a standard topology common in mid-size European cities, and real information concerning traffic demands and mobility patterns.
The scenario is freely available under the MIT licence to the whole community. The scenario is hosted on GitHub (https://github.com/lcodeca/LuSTScenario). Your contribution is highly appreciated!