Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing
This study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. The approach aims to assign the routes that pick up the transit passengers located at the different stops by shuttle service. A bilevel op...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/5117488 |
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| _version_ | 1850162240620068864 |
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| author | Weibin Kou Jiayu Wang Yanxi Liu Chenxu Li |
| author_facet | Weibin Kou Jiayu Wang Yanxi Liu Chenxu Li |
| author_sort | Weibin Kou |
| collection | DOAJ |
| description | This study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. The approach aims to assign the routes that pick up the transit passengers located at the different stops by shuttle service. A bilevel optimization model is established: the upper model of route design considers the tradeoff between time cost and fare cost when some of the passengers take the shuttles, and the lower model assigns the demand of transit passengers. The proposed model effectively captures the reliability of travel time because related parameters are estimated by a statistical fitting test with a large number of real-world bus geographic information system (GPS) data. Moreover, dynamic demand diverting from conventional transit to shuttle service and travel time reliability, including passenger in-vehicle time (IVT) and waiting time (WT), are fully considered in this model. Since the task is a nonlinear programming model, a two-stage algorithm combined with linearization processing is presented to find an optimal solution. Finally, from the case study of Zhongguancun Software Park zone in Beijing, it is indicated that when last-mile shuttle service is provided, bus passengers’ travel time reliability of last-mile trips can be improved by 14%. The study can be an important reference for improving the low reliability widely existing in the current transit commuters’ last-mile problem. |
| format | Article |
| id | doaj-art-fab6aede7fdd4cd69ac2b8d922a91503 |
| institution | OA Journals |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-fab6aede7fdd4cd69ac2b8d922a915032025-08-20T02:22:37ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/5117488Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of BeijingWeibin Kou0Jiayu Wang1Yanxi Liu2Chenxu Li3School of Transportation Science and EngineeringNational Defense Transportation DepartmentSchool of Transportation Science and EngineeringSchool of Transportation Science and EngineeringThis study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. The approach aims to assign the routes that pick up the transit passengers located at the different stops by shuttle service. A bilevel optimization model is established: the upper model of route design considers the tradeoff between time cost and fare cost when some of the passengers take the shuttles, and the lower model assigns the demand of transit passengers. The proposed model effectively captures the reliability of travel time because related parameters are estimated by a statistical fitting test with a large number of real-world bus geographic information system (GPS) data. Moreover, dynamic demand diverting from conventional transit to shuttle service and travel time reliability, including passenger in-vehicle time (IVT) and waiting time (WT), are fully considered in this model. Since the task is a nonlinear programming model, a two-stage algorithm combined with linearization processing is presented to find an optimal solution. Finally, from the case study of Zhongguancun Software Park zone in Beijing, it is indicated that when last-mile shuttle service is provided, bus passengers’ travel time reliability of last-mile trips can be improved by 14%. The study can be an important reference for improving the low reliability widely existing in the current transit commuters’ last-mile problem.http://dx.doi.org/10.1155/2022/5117488 |
| spellingShingle | Weibin Kou Jiayu Wang Yanxi Liu Chenxu Li Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing Journal of Advanced Transportation |
| title | Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing |
| title_full | Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing |
| title_fullStr | Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing |
| title_full_unstemmed | Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing |
| title_short | Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing |
| title_sort | last mile shuttle planning for improving bus commuters travel time reliability a case study of beijing |
| url | http://dx.doi.org/10.1155/2022/5117488 |
| work_keys_str_mv | AT weibinkou lastmileshuttleplanningforimprovingbuscommuterstraveltimereliabilityacasestudyofbeijing AT jiayuwang lastmileshuttleplanningforimprovingbuscommuterstraveltimereliabilityacasestudyofbeijing AT yanxiliu lastmileshuttleplanningforimprovingbuscommuterstraveltimereliabilityacasestudyofbeijing AT chenxuli lastmileshuttleplanningforimprovingbuscommuterstraveltimereliabilityacasestudyofbeijing |