Optimization design of intersection traffic organization based on Growth-TRRL algorithm

Traffic problems frequently occur due to improper intersection channelization and signal timing. The key to resolving these issues lies in optimizing the traffic organization design for specific intersections. Firstly, a new algorithm, Growth-TRRL, was proposed to improve TRRL by introducing the hill climbing method, and this improved algorithm was used to search for the optimal signal period iteratively. Secondly, the intersection data of Renmin Road and Shangcheng Road in Zhengzhou were collected and input into the Growth-TRRL algorithm to optimize the channelization and signal period timing of the intersection. Finally, VISSIM modeling and simulation were conducted to verify the accuracy of the optimization scheme, using vehicle delay and queue length as evaluation indicators, and the optimization performance was analyzed in detail. The results show that the optimized scheme can reduce vehicle delay time by 66.3%, shorten average queue length by 58.0%, significantly improve intersection traffic efficiency, and effectively alleviate congestion.