An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System
With the potential of increasing mobility and reducing cost, shared mobility of autonomous vehicles (AVs) is going to gain solid growth in the coming decade. The major issue for the shared use of AVs is how to project serving routes in an efficiently way. From another perspective, this issue could b...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/3271608 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850227930209189888 |
|---|---|
| author | Ming Li Nan Zheng Xinkai Wu Weihua Li Jianhua Wu |
| author_facet | Ming Li Nan Zheng Xinkai Wu Weihua Li Jianhua Wu |
| author_sort | Ming Li |
| collection | DOAJ |
| description | With the potential of increasing mobility and reducing cost, shared mobility of autonomous vehicles (AVs) is going to gain solid growth in the coming decade. The major issue for the shared use of AVs is how to project serving routes in an efficiently way. From another perspective, this issue could be understood as to segment maximum number of passengers into groups. Therefore, this paper intends to investigate passengers’ similarity instead of directly matching AVs and passengers. The goal is to determine the minimum number of groups and assign each group with an AV. To this end, a cluster-based algorithm is proposed to classify passengers. Numerical experiments with both small-size and large-size demands are performed to present the validity of the proposed algorithm. Results indicate that the cluster-based algorithm could bring benefit to minimizing the number of vehicles and total travel distance. At last, sensitivity analysis of key parameters shows that vehicle capacity will have little impact when the number of seats exceeds four, and time windows could make continuous influence on gathering passengers. |
| format | Article |
| id | doaj-art-2433d9650d284e528a4e24a7040d773b |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-2433d9650d284e528a4e24a7040d773b2025-08-20T02:04:41ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/32716083271608An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle SystemMing Li0Nan Zheng1Xinkai Wu2Weihua Li3Jianhua Wu4School of Transportation Science and Engineering, Beihang University, Beijing 100191, ChinaInstitute of Transport Studies, Department of Civil Engineering, Monash University, AustraliaSchool of Transportation Science and Engineering, Beihang University, Beijing 100191, ChinaInstitute of Rail Transportation of Jinan University, Electrical and Information College of Jinan University, Zhuhai 519070, ChinaInstitute of Rail Transportation of Jinan University, Electrical and Information College of Jinan University, Zhuhai 519070, ChinaWith the potential of increasing mobility and reducing cost, shared mobility of autonomous vehicles (AVs) is going to gain solid growth in the coming decade. The major issue for the shared use of AVs is how to project serving routes in an efficiently way. From another perspective, this issue could be understood as to segment maximum number of passengers into groups. Therefore, this paper intends to investigate passengers’ similarity instead of directly matching AVs and passengers. The goal is to determine the minimum number of groups and assign each group with an AV. To this end, a cluster-based algorithm is proposed to classify passengers. Numerical experiments with both small-size and large-size demands are performed to present the validity of the proposed algorithm. Results indicate that the cluster-based algorithm could bring benefit to minimizing the number of vehicles and total travel distance. At last, sensitivity analysis of key parameters shows that vehicle capacity will have little impact when the number of seats exceeds four, and time windows could make continuous influence on gathering passengers.http://dx.doi.org/10.1155/2020/3271608 |
| spellingShingle | Ming Li Nan Zheng Xinkai Wu Weihua Li Jianhua Wu An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System Journal of Advanced Transportation |
| title | An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System |
| title_full | An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System |
| title_fullStr | An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System |
| title_full_unstemmed | An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System |
| title_short | An Efficient Solving Method to Vehicle and Passenger Matching Problem for Sharing Autonomous Vehicle System |
| title_sort | efficient solving method to vehicle and passenger matching problem for sharing autonomous vehicle system |
| url | http://dx.doi.org/10.1155/2020/3271608 |
| work_keys_str_mv | AT mingli anefficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT nanzheng anefficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT xinkaiwu anefficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT weihuali anefficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT jianhuawu anefficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT mingli efficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT nanzheng efficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT xinkaiwu efficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT weihuali efficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem AT jianhuawu efficientsolvingmethodtovehicleandpassengermatchingproblemforsharingautonomousvehiclesystem |