Development and Evaluation of Connected-Vehicle-Enabled Optimal Dynamic Path Planning with Bus Stops

The frequent stops of transit buses significantly block lanes on roads and generate vehicle queues behind. The passenger cars traveling behind buses may be stuck in the queues and miss the green light in the downstream intersection. They will be very tempted to make lane changes to avoid the stopping vehicles efficiently. However, without knowing the information of bus stations and traffic signals, it is very difficult and dangerous for the queued vehicles to make lane changes at last minute. In this paper, an optimal dynamic path planning system will be developed to assist passenger cars avoid buses so as to improve their mobility on local roads. The system utilizes connected vehicles to receive stop information, including times, duration, and locations, of buses, and the signal timing information from intersections. The information is applied to predict the delay of connected vehicles caused by the buses and intersections. The system also estimate optimal paths for the target vehicles to make lane changes and overpass the buses and the downstream intersection to minimize its travel time delay. In this paper, both synthetic and realistic examples are designed with microscopic traffic simulations to evaluate the performance of the proposed system. The results indicate that the travel time delay for connected vehicles can be reduced by up to 35%. In addition, a sensitivity analysis of the market penetration rates of connected vehicles and demand levels is conducted to understand the benefits and reliability of the system under different stages of the connected environment.