Developing a de-centralized cycle-free nash bargaining arterial traffic signal controller

Abstract

This paper presents a novel de-centralized cycle-free traffic signal controller that adapts to changes in traffic demand. Traffic signal timing optimization is achieved using a Nash Bargaining game-theoretic framework, where each phase is modeled as a player in a game in which the players cooperate to reach a mutual agreement. The Nash bargaining solution is applied to obtain the optimal control strategy, considering a flexible phasing sequence and free cycle length. The system is implemented and evaluated in the INTEGRATION microscopic traffic assignment and simulation software. The proposed control approach is compared to the operation of an optimum fixed-time coordinated plan, a centralized adaptive phase split controller, a decentralized phase split and cycle length controller, and a fully coordinated adaptive phase split, cycle length, and offset optimization controller to evaluate the performance of the proposed decentralized controller. The simulation results were tested on an arterial network located in the heart of downtown Blacksburg, Virginia, USA. The simulation results show significant reductions in the average travel time ranging from 7% to 21%, a reduction in the total delay ranging from 36% to 67%, and a reduction in the emission levels ranging from 6% to 13%. Analysis of variance, Tukey, and pairwise comparison tests were conducted, to examine the statistically significant difference of the proposed controller. The results demonstrate that the proposed decentralized controller produces major improvements over other state-of-the-art centralized and de-centralized control approaches.