An Intelligent Traffic Signal Coordination Method Based on Asynchronous Decision-Making

The intelligent traffic signal control system is a component of the intelligent traffic system (ITS), offering real-time services for the creation of a safe and efficient traffic environment. However, due to restricted communication, conventional adaptive traffic signal-controlled methods are unable to fulfill the complex and changing traffic requirements. A multi-agent adaptive coordination method (ADM) based on asynchronous decision-making and edge computing is presented to address the issues of communication delay and a decrease in signal utilization. Firstly, the end-side-cloud architecture is proposed for real-time environmental information collection and related processing. Then, to enhance the agent coordination process, asynchronous communication is implemented. An approach for calculating the decision cycle of the agent is presented, and an asynchronous decision mechanism employing multiple agents’ decision cycles is devised. The experimental results show that edge computing technology provides a good solution for traffic signal control scenarios with high real-time requirements. In addition, compared with the fixed time (FT) and independent Q-learning decision algorithm (IQA), ADM achieves collaboration among the agents based on the asynchronous decision mechanism and the neighbor information base, and reduces the average vehicle waiting length and improves intersection time utilization.