TASR: A Novel Trust-Aware Stackelberg Routing Algorithm to Mitigate Traffic Congestion

A Stackelberg routing platform (SRP) reduces congestion in one-shot traffic networks by proposing optimal route recommendations to the selfish travelers. Traditionally, Stackel-berg routing is cast as a partial control problem where a fraction of the traveler flow complies with route recommendations, while the remaining responds as selfish travelers. In this paper, we formulate a novel Stackelberg routing framework where the agents exhibit probabilistic compliance by accepting SRP's route recommendations with a trust probability. Specifically, we propose a greedy Trust-Aware Stackelberg Routing algorithm (in short, TASR) for SRP to compute unique path recommendations to each traveler flow with a unique demand. Simulation experiments are designed with random travel demands with diverse trust values on real road networks, such as Sioux Falls, Chicago Sketch, and Sydney networks for both single-commodity and multi-commodity flows. The performance of TASR is compared with state-of-the-art Stackelberg routing methods in terms of traffic congestion and trust dynamics over repeated interaction between the SRP and the travelers. Results show that while it may require several interactions for travelers to reach perfect trust, TASR improves network congestion in the single-commodity and multi-commodity settings when compared to the most well-known Stackelberg routing strategies.