Dynamic management of vehicular traffic congestion to maximize throughput in urban areas has been drawing increased attention in recent years. For that purpose, a number of adaptive control algorithms have been proposed for individual traffic lights based on the inflow rate. However, little attention has been given to the traffic throughput maximization problem considering real-time road conditions from multiple intersections. In this paper, we formulate such a problem as maximum integer multi-commodity flow by considering incoming vehicles that have different outgoing directions. Then, we propose a novel adaptive traffic light signal control algorithm which opts to maximize traffic flow through and reduce the waiting time of vehicles at an intersection. The proposed algorithm adjusts traffic light signal phases and durations depending on real-time road condition of local and neighboring intersections. Via SUMO simulation, we demonstrate the effectiveness of the proposed algorithm in terms of traffic throughput and average travel time. INDEX TERMS Adaptive traffic light control, k-commodity flow problem, traffic flow maximization, dynamic traffic management.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.