Abstract
Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.
Highlights
In urban areas, high population densities are related to traffic problems such as CO2 emissions, accidents, noise and environmental pollution, all of them being critical issues for city authorities
Among the packages included in the SUMO distribution Version 0.20.0, we rely on the DFROUTER [6] tool, which has been designed for road scenarios based on the idea that the roads are equipped with induction loops, measuring the inflow and outflow of the roads
For the city of Valencia, we are using traffic flow definitions obtained according to the iterative heuristic defined in Section 4.2 with φ = 0.38914 and ε < 0.0001 in the ninth iteration, while the latter two are typical scenarios provided by the SUMO tool itself that will be used as a reference
Summary
High population densities are related to traffic problems such as CO2 emissions, accidents, noise and environmental pollution, all of them being critical issues for city authorities. We start from induction loop measurements made available by the City Hall of Valencia (see [5] for more details), and we propose a heuristic that iteratively refines the output produced by the DFROUTER tool [6] which consists of a list of routes and a list of vehicles associated with each route This allows determining where vehicles are coming from and what are their destinations. Since traffic planning and optimization typically require studying the impact of unexpected traffic load conditions, we detail how, based on our reference scenario, we can regulate the amount of vehicles in the city to generate different degrees of congestion This allows determining which degree of congestion is expectable in different situations; in particular, we study the impact of having an additional traffic load on the overall traffic congestion levels when adopting either a uniform or a hotspot-based pattern for traffic injection.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
