Vehicle trajectory data in Eco-friendly Cooperative Traffic Optimization (EcoTOp) system at signalized intersections

Surface transportation systems (e.g., arterial roadways with signalized intersections) are inherently inefficient, particularly at higher traffic volumes. In general, both the infrastructure (e.g., traffic signals) and the vehicles operate independently, with little coordination between them. Previous research has shown that implementing strategies that take advantage of infrastructure-to-vehicle communication can improve overall mobility and reduce environmental impacts, e.g., the Eco-Approach and Departure (EAD) application that takes advantage of communicating signal phase and timing information to the vehicles. In this research, we will build upon this past research to develop a new cooperative traffic operation approach that takes advantage of not only infrastructure-to-vehicle communications, but also vehicle-to-infrastructure communications. This effort integrates a dynamic traffic signalization algorithm together with EAD algorithm to achieve even greater traffic efficiency. The research was carried out in a high-fidelity simulation environment and shows upwards of 15% fuel savings and 85% reductions in waiting time. The dataset contain the vehicle trajectory of all CAVs and non-CAVs in the SUMO-based traffic simulation from all approaches, with vary penetratin rate at 0% (baseline), 20%, 50%, 80% and 100%.The data were saved in txt files in the format of second-by-second trajectories. One can use any text editor to open it.Funding provided by: National Center for Sustainable Transportation*Crossref Funder Registry ID: Award Number: DOT 69A3551747114The dataset was collected from the trajectory output of SUMO, a micro-scopic traffic simulation software. Different scenarios under varying penetrations are tested, e.g. penetratin rate at 0% (baseline), 20%, 50%, 80% and 100%. The trajectory data are then archived as txt files