Novel Transit Driver Advisory System for Supporting e-Bus Operations

The emerging connected vehicle (CV) technology offers new ways for improving transit service performance in mixed-traffic corridors without having adverse impacts on the general traffic. One promising strategy, CV-enabled driver advisory system (DAS) for transit, aims at advising each bus driver of target travel speed and dwell time values to allow the bus to arrive at the downstream signalized intersection during the green phase, thus minimizing stoppage instances. In this paper, four different DAS algorithms with different objectives were tested with two space priority strategies in the form of exclusive bus lanes (EBLs) or dynamic bus lanes (DBLs). To evaluate the performance of the DAS algorithms, a traffic simulation model of the Eglinton East corridor in Toronto, Canada, was built in Aimsun Next for the morning peak period. The simulation results showed that DAS is a promising strategy that allows the bus to travel at or near the maximum allowable speed with 50% reduction in the total number of stops and 15 to 20% reduction in the bus energy consumption rate (for e-buses). Adding headway regularity as another objective of DAS shows significant benefits, with the regularity level of service (LOS) rising from LOS F to LOS C.