Arterial Coordinated Optimization with Time-of-Day Control in Urban Areas

This study combined the coordinated control and time-of-day strategy to improve the stability and benefit cost ratio of the control strategy in the context of China's traffic condition. The coordination boundary was determined by the coordinatability model of intersections. The traffic volumes of intersections in the research area were dealt with the mixed clustering method to obtain the corresponding time-of-day strategies. On the basis of the previous study, the multiple-objective particle swarm optimization is used for the average delay to find the best switching time for time-of-day control. Relevant simulation indicates that when compared with current traffic control plans and mixed clustering optimization, the proposed strategy shows more advantages in termsof bandwidth of traffic control plan and delay optimization. After minimizing the disturbance caused by switching traffic control plans, the resulting decrement rate of average vehicle delay is 12.63% for the current traffic control plan and 2.45% for the mixed clustering optimization; the increasing bandwidth rates of the traffic control plan are 0.98% and 23.51%, respectively.