基于A*算法的智能车多红绿灯信号交叉口通行的经济车速规划研究

Economic Speed Planning Based on A-Star Algorithm for Intelligent Vehicle in Traffic Light Intersection

  • 摘要: 智能汽车通过高精度地图可以获得前方红绿灯信号交叉口信息,利用其具有的复杂的全局规划能力,可以提高车辆通过多红绿灯信号交叉口的燃油经济性. 本研究通过瞬时燃油消耗模型与动态规划算法计算车辆的燃油消耗以及对应的速度序列,并将其作为红绿灯时空拓扑图的边集权重,然后利用A*算法规划车辆的速度轨迹,旨在提高车辆的燃油经济性. 结果表明,规划的车速轨迹通过4个红绿灯信号交叉口时,相对于以平路行驶的最经济车速行驶,在红绿灯最差配时时能够提升33.6%的燃油经济性以及减少17.7%的通过时间.

     

    Abstract: It can improve the fuel economy of vehicles when they pass through traffic light intersection to acquire traffic light intersection information in front by a high-precision map and possess the ability of automatic driving to exceed human's global decision-making and planning. In this study, a transient fuel consumption model and dynamic programming algorithm were used to calculate the vehicle fuel consumption and corresponding vehicle speed sequence, taken as the edge set weights of the traffic light spatio-temporal topology map. And then an A-star algorithm was used to plan the vehicle speed trajectory in order to improve the vehicle fuel economy. The results show that when the speed trajectory planned in this paper passes through four traffic light intersections, it can improve fuel economy by 33.6% and reduce the travel time by 17.7% at most compared with the most economical speed of flat roads.

     

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