Abstract
This paper presents a novel de-centralized flexible phasing scheme, cycle-free, adaptive traffic signal controller using a Nash bargaining game-theoretic framework. The Nash bargaining algorithm optimizes the traffic signal timings at each signalized intersection by modeling each phase as a player in a game, where players cooperate to reach a mutually agreeable outcome. The controller is implemented and tested in the INTEGRATION microscopic traffic assignment and simulation software, comparing its performance to that of a traditional decentralized adaptive cycle length and phase split traffic signal controller and a centralized fully-coordinated adaptive phase split, cycle length, and offset optimization controller. The comparisons are conducted in the town of Blacksburg, Virginia (38 traffic signalized intersections) and in downtown Los Angeles, California (457 signalized intersections). The results for the downtown Blacksburg evaluation show significant network-wide efficiency improvements. Specifically, there is a reduction in travel time, a reduction in queue lengths, and a reduction in emissions relative to traditional adaptive traffic signal controllers. In addition, the testing on the downtown Los Angeles network produces a reduction in travel time on the intersection approaches, a reduction in queue lengths, and a reduction in emissions compared to traditional adaptive traffic signal controllers. The results demonstrate significant potential benefits of using the proposed controller over other state-of-the-art centralized and de-centralized adaptive traffic signal controllers on large-scale networks both during uncongested and congested conditions.
Highlights
Traffic growth and limited available capacity within the roadway system produces problems and challenges for transportation agencies
Vehicles were loaded for one hour, while the simulation continued until all vehicles cleared the network to ensure that the same number of vehicles were used in comparing the performance of the various traffic signal control algorithms
The results indicated significant reduction in the average travel time of 6.5%, a reduction in the average total delay of 19.8%, and a reduction in the average stopped delay of 52.7% over the phase split-cycle length and offset optimization controller (PSCO) controller. These results show that the proposed DNB controller outperforms both the phase split and cycle length controller (PSC) and PSCO controllers
Summary
Of Civil and Environmental Engineering, Director of the Center of Sustainable. Virginia Tech Transportation Institute, Virginia Tech, Blacksburg, VA 24061, USA
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