摘要
城市道路交通主干道发生事故时,车道发生堵塞,道路通行受到严重影响,尤其会延长货物运输时长。为了避免交通事故发生后车辆长时间排队问题,需及时调度各个方向车辆。但是由于车辆行驶的路线具有交叉性,通行调度难度较大。为此构建交通事故约束下车辆通行最优调度模型。结合交通事故因素和驾驶员自身特征因素,构建车辆通行调度模型,利用自适应遗传算法和模拟退火算法提高全局和局部寻优能力。采用优化后算法求解车辆通行调度最优模型。实验结果表明,所构建模型调度下车辆行驶到目的地的总距离更短,生成最优调度路径时迭代次数低于30次,耗时不超过10min。
When an accident occurs on an urban main road, lane congestion will affect the capacity of the road. Especially, the transportation time will be prolonged. In order to avoid the vehicles queuing for a long time, vehicles in all directions need to be dispatched in time. However, it is difficult to achieve traffic scheduling due to the intersection of vehicle routes. Therefore, an optimal vehicle scheduling model under traffic accident constraints was constructed. At first, a vehicle access scheduling model was constructed combined with traffic accident factors and drivers’ self-characteristics. And then, an adaptive genetic algorithm and simulated annealing algorithm were adopted to improve the ability of global and local optimization. Finally, the optimized algorithm was used to solve the optimal traffic scheduling model. Experimental results show that the distance from the vehicle to the destination can be shortened by the designed model. In addition, the number of iterations is less than thirty, and the time consumption is no more than ten minutes when the optimal scheduling path is generated.
作者
顾洵
戴帅
GU Xun;DAI Shuai(School of Traffic Management,People's Public Security University of China,Beijing 100038,China)
出处
《计算机仿真》
北大核心
2022年第9期140-143,149,共5页
Computer Simulation
关键词
交通事故约束
车辆通行
最优调度模型
模拟退火算法
自适应遗传算法
Traffic accident constraints
Vehicle access
Optimal scheduling model
Simulated annealing algorithm
Adaptive genetic algorithm
