In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation,the method for setting bus scheduled travel time is proposed. Firstly,multistate model is introduced to fit historical ...In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation,the method for setting bus scheduled travel time is proposed. Firstly,multistate model is introduced to fit historical travel time data and identify different service states. Based on the calibrated travel time distribution parameters,an optimization model is proposed,followed by a Monte Carlo( MC) simulation based genetic algorithm( GA)procedure to obtain the optimal scheduled time. A case study from a fixed bus route from Shenzhen is used to demonstrate the model applicability. The sensitivity analysis is conducted to study the effects of parameters setting on optimal slack time for each segment. The results show that multistate model fits travel time under peak hours better than Lognormal distribution,and the length of scheduled travel time basically reflects travel time reliability.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 by the National Natural Science Foundation of China(Grant No.71101109)Key Project of Shanghai Soft Science Research Program(Grant No.15692105400)Humanities and Social Sciences Program of the Ministry of Education,China(Grant No.15YJCZH148)
文摘In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation,the method for setting bus scheduled travel time is proposed. Firstly,multistate model is introduced to fit historical travel time data and identify different service states. Based on the calibrated travel time distribution parameters,an optimization model is proposed,followed by a Monte Carlo( MC) simulation based genetic algorithm( GA)procedure to obtain the optimal scheduled time. A case study from a fixed bus route from Shenzhen is used to demonstrate the model applicability. The sensitivity analysis is conducted to study the effects of parameters setting on optimal slack time for each segment. The results show that multistate model fits travel time under peak hours better than Lognormal distribution,and the length of scheduled travel time basically reflects travel time reliability.
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.
