Collaborative Control Method of Transit Signal Priority Based on Cooperative Game and Reinforcement Learning

TL;DR

This paper presents a novel hybrid decision-making framework combining cooperative game theory and reinforcement learning to improve transit signal priority control, achieving more adaptive and efficient traffic management.

Contribution

It introduces the CBQL-TSP method, integrating cooperative game theory with Q-Learning for dynamic, fair, and efficient transit signal priority control in eight-phase traffic signals.

Findings

Enhanced traffic signal efficiency compared to traditional methods

Effective real-time adaptation to traffic conditions

Maintains fairness principles in signal priority allocation

Abstract

To address the low efficiency in priority signal control within intelligent transportation systems, this study introduces a novel eight-phase priority signal control method, CBQL-TSP, leveraging a hybrid decision-making framework that integrates cooperative game theory and reinforcement learning. This approach conceptualizes the allocation of bus signal priorities as a multi-objective decision-making problem across an eight-phase signal sequence, differentiating between priority and non-priority phases. It employs a cooperative game model to facilitate this differentiation. The developed hybrid decision-making algorithm, CBQL, effectively tackles the multi-objective decision-making challenges inherent in the eight-phase signal sequence. By computing the Shapley value function, it quantifies the marginal contributions of each participant, which in turn inform the construction of a state transition probability equation based on Shapley value ratios. Compared to conventional control methods, the CBQL-TSP method not only upholds the fairness principles of cooperative game theory but also harnesses the adaptive learning capabilities of Q-Learning. This enables dynamic adjustments to signal timing in response to real-time traffic conditions, significantly enhancing the flexibility and efficiency of priority signal control.