Sustainable traffic management and control system for arterial with contraflow left-turn lanes.

Nowadays, air pollution caused by traffic congestion has progressively drawn more and more attention. This paper proposes a traffic management and control platform from the perspective of sustainable development to reduce both vehicle emission and delay along arterial with contraflow left-turn lane (CLL). Unlike the traditional intersection layout and the control strategy, the existence of the contraflow left-turn lanes at intersections brings difficulties in setting phase sequences due to the complex interactions among upstream and downstream lanes. Furthermore, the queueing conditions are totally different from traditional intersections due to the complex queueing phenomenon between pre-signals and main signals. A macroscopic traffic model is proposed to model the intersection along arterial with CLL and is established on the basis of finite capacity queueing models. The optimization framework derives fixed-time traffic signal control plans, in which the green splits of the main signal and the pre-signal are explicitly considered. The nondominated sorting genetic algorithm II (NSGA-II) is employed to solve problem. A case study based on the field data of four intersections along the West Yan'an Road in the city of Shanghai is carried out to investigate the performance of the proposed framework. The microscopic simulator AIMSUN is used to evaluate and compare the travel delay and vehicle emissions obtained by the newly proposed signal plans and the signal plans derived by using traditional traffic control method. The simulation results indicate that the proposed framework successfully reduce travel delay and vehicle emission at intersections along arterial road with CLL. • A sustainable multi-objective traffic management and control platform for arterials with contraflow left-turn lanes (CLL) is proposed to minimize vehicle emission and delay. • A macroscopic traffic model is proposed to model the intersection along arterial with CLL and is established on the basis of finite capacity queueing models. • The nondominated sorting genetic algorithm II is employed to solve the fixed-time traffic control problem. • A case study based on the field data of four intersections along an arterial in the city of Shanghai is carried out to investigate the performance of the proposed framework. [ABSTRACT FROM AUTHOR]