A Comprehensive Analysis of the Impacts of Transit Driver Advisory Systems with Space Priority on the Corridor Performance

Connected vehicles open the way for offering new strategies that can prioritize transit vehicles without having adverse impacts on the general traffic. Driver advisory system (DAS) is one strategy that relies on vehicle-to-infrastructure communication to advise bus drivers with specific traveling speeds and dwell times that achieve specific objectives. In this study, we conducted a comprehensive analysis of the impacts of different DAS algorithms on the performance of electric buses (e-buses) and the general traffic. Additionally, we examined two supporting space priority strategies to allow the buses to travel at the advised speeds. A simulation model for the Eglinton East corridor in Toronto, Canada was built using Aimsun Next in order to quantify the impacts of the DAS algorithms. The results show that DAS is a promising strategy that allows the buses to travel near the maximum possible speed with 25% to 55% reduction in the total number of stops, 20% to 55% higher levels of comfort, and 10% to 20% reduction in the bus energy consumption rates. Additionally, the DAS can improve the headway regularity, improving the level of service (LOS) from LOS F to LOS C when the headway regularity was added to the objectives of the DAS.