Computational study explores optimal route choices in traffic networks using vehicle-to-vehicle communication, aiming for reduced travel times.
Key Points
This research aims to develop a traffic flow model that incorporates vehicle-to-vehicle communication and rational decision-making for route optimization.
Developed a microscopic follow-the-leader model for traffic flow on road networks.
Assumed drivers choose routes based on minimal travel time and rational decisions at junctions.
Implemented anonymous information sharing among vehicles for position and planned path optimization.
Identified that with infinite communication range, the model converges to Reactive User Equilibrium (RUE) and Dynamic User Equilibrium (DUE).
Demonstrated the potentials of real-time information sharing for optimizing route choices and reducing travel times.