Multi-commodity traffic signal control and routing with connected vehicles

de Souza, F., Carlson, R. C., Muller, E. R. and Ampountolas, K. (2022) Multi-commodity traffic signal control and routing with connected vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(5), pp. 4111-4121. (doi: 10.1109/TITS.2020.3041436)

Abstract

A real-time traffic management policy that integrates traffic signal control and multi-commodity routing of connected vehicles in networks with multiple destinations is developed. The proposed policy is based on a multi-commodity formulation of the store-and-forward model and assumes all vehicles are able to exchange information with the infrastructure. Vehicles share information about their current location and final destination. Based on this information, the strategy determines both optimized signal timings at every intersection and vehicle-specific routing information at every link of the network. The control actions, i.e., signal times and routing information, are updated at every cycle and delivered by a finite horizon optimal control problem cast into a rolling horizon framework. The underlying optimization problem is convex, and thus the method is suitable for real-time operation in large networks. The method is validated via a micro-simulation study in networks with up to twenty intersections and, in all simulations, outperforms a real-time traffic-responsive signal control strategy that is based on a single-commodity store-and-forward model. The scalable computation effort for increasing network sizes and prediction horizon confirms the computational efficiency of the method.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ampountolas, Dr Konstantinos
• Authors: de Souza, F., Carlson, R. C., Muller, E. R., and Ampountolas, K.
• College/School: College of Science and Engineering > School of Engineering
• Journal Name: IEEE Transactions on Intelligent Transportation Systems
• Publisher: IEEE
• ISSN: 1524-9050
• ISSN (Online): 1558-0016
• Published Online: 11 December 2020
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in IEEE Transactions on Intelligent Transportation Systems 23(5): 4111-4121
• Publisher Policy: Reproduced in accordance with the publisher copyright policy