Identifying Traffic Control Mechanism to Improve Level of Service and Resilience in Road Networks based on Topological Credentials

Abstract

Traffic congestion mitigation strategies often include debating the merit of adding more roads versus optimizing the existing ones. Identifying and improving critical intersections, particularly by adjusting signal control mechanisms, may result in a cost-effective solution. During system disruptions, such as natural or man-made disasters, traffic patterns become unpredictable, leading to gridlocks at certain intersections. It is essential to proactively identify these intersections and apply time and cost-saving solutions. Research has explored various improvement strategies for signalized intersections, such as using actuated controllers or implementing urban traffic control strategies during peak demand. However, the literature does not provide enough guidance on how to prioritize one intersection over the others at the network level to improve level service as well as resilience. Moreover, none of the research conducted network analysis for improving transportation network reconfiguring traffic controllers using node-weighted and full- weighted (both edge and node weight) betweenness centrality (BC). This study presents a new traffic control mechanism technique for improved level of service and resilience in road networks based on topological credentials i.e., rank of relative importance (i.e., node centrality using both edge and node weights) of network elements such as intersections. The goal is to systematically improve the network performance by adopting specific intervention strategies (i.e., traffic controller setup) at certain intersections based on centrality and observing performance metrics such as total travel time, total delay, and Level of Service (LOS).

The study considered the Boise downtown network in Idaho to run these experiments in a simulated environment using Dynamic Traffic Assignment for two specific scenarios (i.e., normal and disrupted) under different network intervention schemes. Results indicate that interventions made at certain intersections improved network performance. For example, changing fixed-time Ring Barrier Controllers (RBC) into actuated RBCs at 8 most important intersections reduces total travel time by 6.7%, total delay by 7.8% and 96 out of 175 turning and through movements at various intersections/nodes experienced better LOS when full-weighted BC ranking is considered. A higher reduction in total travel time (7.8%), total delay (8.8%) and increased number of turning and through movement improvement on intersection in terms of LOS (103 out of 175) is observed when 3 most important intersections are converted into roundabout and rest of the 5 most important intersections into actuated RBCs as per BC ranking. Under disrupted condition (i.e., removing the most important road segment/edge based on the ranking of edge BC measurement of edges of base network), the system performance (total travel time as an indicator) drops down to 96.49% when the original network is assumed to be working at 100% efficiency. After systematically applying node intervention strategies using the full- weighted BC ranking of nodes, the system performance recovers up to 105.95%. Future research should observe system performance by considering a combination of network properties as well as interventions made at other network elements such as roadway segments instead of intersections.