Optimizing Signalized Intersections Performance under Conventional and Automated Vehicles Traffic
For traffic engineers and AV developers, this work addresses the challenge of integrating AVs into existing signalized intersections, but the results are limited to undersaturated conditions and simulation.
The study developed an Intelligent Intersection Control System (IICS) that jointly optimizes signal timing and automated vehicle trajectories under undersaturated mixed traffic. Simulations showed 38-52% reduction in average travel time compared to conventional actuated control.
Automated vehicles, or AVs (i.e. those that have the ability to operate without a driver and can communicate with the infrastructure) may transform the transportation system. This study develops and simulates an algorithm that can optimize signal control simultaneously with the AV trajectories under undersaturated traffic flow of AV and conventional vehicles. This proposed Intelligent Intersection Control System (IICS) operates based on real-time collected arrival data at detection ranges around the center of intersection. Parallel to detecting arrivals, the optimized trajectories and signal control parameters will be transmitted to AVs and the signal controller to be implemented. Simulation experiments using the proposed IICS algorithm successfully prevented queue formation up to undersaturated condition. Comparison of the algorithm to operations with conventional actuated control shows 38-52% reduction in average travel time compared to conventional signal control.