Connection-Based Scheduling for Real-Time Intersection Control
This addresses traffic congestion at intersections for urban planners and transportation systems, representing an incremental improvement over existing scheduling methods.
The researchers tackled real-time adaptive traffic signal control to reduce congestion by introducing a heuristic scheduling algorithm that minimizes cumulative vehicle delay. Their approach outperformed Dynamic Programming and previous A* methods in runtime, achieving real-time scheduling every second in both simulated and field tests.
We introduce a heuristic scheduling algorithm for real-time adaptive traffic signal control to reduce traffic congestion. This algorithm adopts a lane-based model that estimates the arrival time of all vehicles approaching an intersection through different lanes, and then computes a schedule (i.e., a signal timing plan) that minimizes the cumulative delay incurred by all approaching vehicles. State space, pruning checks and an admissible heuristic for A* search are described and shown to be capable of generating an intersection schedule in real-time (i.e., every second). Due to the effectiveness of the heuristics, the proposed approach outperforms a less expressive Dynamic Programming approach and previous A*-based approaches in run-time performance, both in simulated test environments and actual field tests.