通过优化地铁时刻表可有效降低地铁牵引能耗。为解决客流波动和车辆延误对实际节能率影响的问题,提出列车牵引和供电系统实时潮流计算分析模型和基于Dueling Deep Q Network(Dueling DQN)深度强化学习算法相结合的运行图节能优化方法,...通过优化地铁时刻表可有效降低地铁牵引能耗。为解决客流波动和车辆延误对实际节能率影响的问题,提出列车牵引和供电系统实时潮流计算分析模型和基于Dueling Deep Q Network(Dueling DQN)深度强化学习算法相结合的运行图节能优化方法,建立基于区间动态客流概率统计的时刻表迭代优化模型,降低动态客流变化对节能率的影响。对预测Q网络和目标Q网络分别选取自适应时刻估计和均方根反向传播方法,提高模型收敛快速性,同时以时刻表优化前、后总运行时间不变、乘客换乘时间和等待时间最小为优化目标,实现节能时刻表无感切换。以苏州轨道交通4号线为例验证方法的有效性,节能对比试验结果表明:在到达换乘站时刻偏差不超过2 s和列车全周转运行时间不变的前提下,列车牵引节能率达5.27%,车公里能耗下降4.99%。展开更多
This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and ...This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.展开更多
基金sponsored in part by the National Natural Science Foundation of China(No.71101109)the Open Fund of the Key Laboratory of Highway Engineering of Ministry of Education,Changsha University of Science & Technology(No.kfj120108)
文摘This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.
