Research Of Urban Signal Control Strategies Based On Vehicle Emission

The operating conditions of vehicles change dramatically when they approaching to the intersection entrances, which leads to sharp increase of vehicle emission. How to reduce vehicle emission through effective signal control has become an important topic. To date, few studies of signal control that using minimizing vehicle emission as the optimization goal have been proposed. Moreover, exiting researches are limited to the optimization problems at independent intersections. In this research, the analysis of vehicle emission was started with a single intersection, then a signal optimization model was set up with the target of minimizing the overall vehicle emission for an intersection group. The optimization for the intersection group was achieved through the interaction between the proposed optimization model and the traffic simulation software. Finally, a signal control strategy for the intersection group was made.When calculating the vehicle emission, a method was adopted based on the different vehicle operating conditions at an intersection. Vehicle emission factors of four operation conditions, i.e. deceleration, idling, acceleration, uniform, were calibrated using the emission factors for specific power partition. In the calibrating process, operating condition of vehicles arriving during red time was treated as a full-stop; that of vehicles arriving during early green time, when the queue due to red time has not been completely discharged, was treated as a partial-stop; and that of vehicles arriving during late green time, when the queue has been completely discharged, was treated as a non-stop. Emission of individual vehicle was calculated from matching the specific vehicle operating condition and its stop type at the intersection. The emission of individual vehicle was aggregated to the vehicle emission for a single lane in first. Then the overall vehicle emission for the intersections was summarized from vehicle emission of each lane.During the process of signal time optimizing, the original phase program and cycle length were kept but only the green time has been optimized. A genetic algorithm was used to solve the proposed optimization model. Then an interaction between the proposed optimization model and traffic simulation was introduced to produce an optimal signal timing. A case study based on a group of seven adjacent intersections located in the downtown area of Kunshan city was conducted to illustrate the proposed method. The results show the effectiveness of the proposed optimization model. Apart from the analysis of vehicle emission, control delay was introduced as a supplemental performance measure to evaluate the proposed method. A signal control strategy was made based on the analysis of consistency and trade-off between vehicle emission and delay.