网联环境下连续交叉口车速引导及优化

Speed Induction and Optimization at Successive Intersections Under Network Environment

为降低车辆通过信号交叉口区域时的油耗和排放量,基于网联环境下车辆可以实时获取道路交通信息的特征,对连续信号交叉口车辆生态驾驶速度进行引导;以车辆通过连续信号交叉口的油耗、排放及通行效率为目标,以车辆不停车通过连续信号交叉口的速度区间为约束,结合瞬态油耗排放模型,利用多目标粒子群算法优化目标车辆速度。仿真结果表明,车速优化后,在高算法渗透率低道路饱和度条件下通过3个连续信号交叉口的油耗和NOX、CO、HC排放量分别降低12.77%、8.20%、11.75%及16.42%;利用转毂试验台对仿真得到的车辆轨迹进行实验发现,车速优化后车辆油耗降低10.20%。

In order to reduce the fuel consumption and emissions of vehicles passing signalized intersection area,an ecological driving speed induction strategy for vehicles passing successive signal intersections is established based on the feature that vehicles can obtain real time road traffic information in a network environment.The fuel consumption,emissions and traffic efficiency of vehicles passing successive signalized intersections were taken as the goal,the speed range of vehicles passing successive signalized intersections without stop was taken as the constraint,and the transient fuel consumption and emission model was combined.The multiobjective particle swarm optimization algorithm was then used to optimize the target vehicle speed.The simulation results indicate that the fuel consumption and NOX,CO and HC emissions of vehicles passing three successive signal intersections under high algorithm penetration and low road saturation with optimized speed are reduced by 12.77%,8.20%,11.75%and 16.42%respectively in contrast with those unoptimized.Finally,results of the test on the simulated vehicle trajectory using the drum test table indicate that the optimized vehicle fuel consumption is reduced by 10.2%in contrast with those unoptimized.