Traffic Optimization for Signalized Corridors (TOSCo) Phase 1 Project Vehicle-level Simulation Report
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2019-06-28
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Edition:Final Report
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Abstract:The Traffic Optimization for Signalized Corridors (TOSCo) system consists of a series of innovative applications designed to optimize traffic flow and minimize vehicle emissions on signalized arterial roadways. The TOSCo system applies both infrastructure- and vehicle-based V2X communications to assess the state of vehicle queues and cooperatively controls the behavior of strings of equipped vehicles approaching a designated series of signalized intersections to minimize the likelihood of stopping. Assessment of the benefit and the working principles of the TOSCo system is performed by employing two different simulation environments. The traffic-level simulation environment implements a simplified version of the TOSCo algorithm, not focusing on the implementation in an actual vehicle, but on the assessment of macroscopic effects such as improved traffic flow or reduced energy consumption. This report constitutes the analysis of Vehicle-level Simulations, targeting the implementation of the TOSCo-algorithm in an actual vehicle. Its focus lies on the microscopic elements constituting a real-time enabled system ready to be deployed in a real-life prototype vehicle environment rather than on macroscopic benefits. The ability to test vehicle-ready software in a simulation environment before deployment in an actual vehicle reduces the development time, as incremental improvements can be tested without the need for a prototype vehicle and a test track, and it, therefore, also reduces the costs associated to the development process. The TOSCo vehicle-ready software is assessed in eight distinct traffic scenarios. This simulation report shows that the developed TOSCo algorithm is able to perform as specified in most of these simulation scenarios, thereby optimizing the approach strategy of a string of TOSCo-enabled vehicles towards an intersection. The variation of different simulation parameters for each scenario helped to identify remaining tasks and work items that have to be addressed before implementing the software in an actual vehicle environment. The specification of the speed profiles has to be revisited for cases in which the vehicle is currently decelerating, when computing the optimized profile. It is identified that the definition provided in this report does not take potential initial acceleration into account, resulting in undesirable behavior in case the vehicle is currently decelerating when the profile is generated. This occurs frequently especially in scenarios where the state of the traffic light changes and a vehicle is already decelerating (e.g., a vehicle decelerates while approaching a traffic light that is about to turn red), as this change in external conditions triggers a re-computation of the optimized speed profiles. The report closes with a summary of the different simulation scenarios and provides detailed insights to future work and an alternative speed profile definition to alleviate the limitations identified in this report.
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