Abstract:
Arterial coordination control usually aims at maximizing the traffic efficiency in the main direction, which leads to a large delay in the cross street of some minor intersections.Based on the cooperative vehicle infrastructure, the work studies the multi-objective optimization method of double-cycling arterials under speed guidance.Aiming at the saturated and unsaturated traffic flow at the upstream intersection, a dynamic speed guidance model considering queue dissipation and offset is proposed.Furthermore, a double-cycling arterials multi-objective optimization model is constructed taking the average delay time, the average number of stops, the capacity of arterials, and the average delay of the double-cycling intersection as the comprehensive optimization objectives.Then, the genetic algorithm is used to solve the model to obtain the optimized coordinated signal-timing scheme.Based on the COM interface, the cooperative vehicle infrastructure environment is built using Python and Vissim software, and the model is simulated by taking three intersections of Guanganmen Inner Street in Beijing as a case study.The results of this model are compared with those of the original scheme and the multi-objective optimization model of the double-cycling artery without speed guidance.Compared with the original scheme and the multi-objective optimization model without speed guidance, the average delay of arterial is reduced by 19.6% and 8.3%; the capacity increased by 5.6% and 8.4%; the average number of stops is reduced by 11.2% and 24.2%; the average delay of the cross street of the double-cycling intersection re-duced by 33.9% and 5.8%, respectively.The results show that this model combines speed guidance with multi-objective optimization to achieve dynamic speed guidance, with the increased traffic efficiency of the double-cycling artery, the reduced delay of a cross street at a double-cycling intersection, and the mutual optimization of the artery and double-cycling intersection.
