A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation
Shared autonomous vehicles (SAVs) are expected to revolutionize urban mobility. To explore the complex dynamics of competition and cooperation between operators and other traditional transportation modes, this study proposes a tri-level programming model with equilibrium constraints in a multimodal...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Multimodal Transportation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772586325000553 |
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| author | Qing Li Zihao Yan Ke Lu Feixiong Liao |
| author_facet | Qing Li Zihao Yan Ke Lu Feixiong Liao |
| author_sort | Qing Li |
| collection | DOAJ |
| description | Shared autonomous vehicles (SAVs) are expected to revolutionize urban mobility. To explore the complex dynamics of competition and cooperation between operators and other traditional transportation modes, this study proposes a tri-level programming model with equilibrium constraints in a multimodal transportation system. At the upper level, the government regulates the fleet size constraints and hub locations for SAVs. The middle level captures the effect of duopoly competition of SAV operators on fleet size and pricing considering the regulation constraints, which is represented as a 2-player noncooperative game with each player maximizing its profit. At the lower level, travelers’ responses to operational strategies are captured by the dynamic activity-travel assignment model in a multimodal transportation system. A hybrid genetic algorithm, involving a hub-based SAV relocation assignment and a route-swapping algorithm for travelers’ path choice at the lower level, is designed to solve the multi-objective programming problem at the middle level with certain government decisions. A numerical example with two SAV operators shows that the operator with higher-quality vehicles charges more but deploys a smaller fleet compared to the competitor deploying lower-cost vehicles. Government regulations can boost fleet utilization but are less effective when not strict. |
| format | Article |
| id | doaj-art-a0ce1bc56d104af2b01784a0d4b997b7 |
| institution | DOAJ |
| issn | 2772-5863 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Multimodal Transportation |
| spelling | doaj-art-a0ce1bc56d104af2b01784a0d4b997b72025-08-20T03:17:39ZengElsevierMultimodal Transportation2772-58632025-12-014410024110.1016/j.multra.2025.100241A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulationQing Li0Zihao Yan1Ke Lu2Feixiong Liao3School of Management Science and Engineering, Nanjing University of Information Science and Technology, China; Corresponding author.School of Management Science and Engineering, Nanjing University of Information Science and Technology, ChinaSchool of Management Science and Engineering, Nanjing University of Information Science and Technology, ChinaUrban Planning and Transportation Group, Eindhoven University of Technology, the NetherlandsShared autonomous vehicles (SAVs) are expected to revolutionize urban mobility. To explore the complex dynamics of competition and cooperation between operators and other traditional transportation modes, this study proposes a tri-level programming model with equilibrium constraints in a multimodal transportation system. At the upper level, the government regulates the fleet size constraints and hub locations for SAVs. The middle level captures the effect of duopoly competition of SAV operators on fleet size and pricing considering the regulation constraints, which is represented as a 2-player noncooperative game with each player maximizing its profit. At the lower level, travelers’ responses to operational strategies are captured by the dynamic activity-travel assignment model in a multimodal transportation system. A hybrid genetic algorithm, involving a hub-based SAV relocation assignment and a route-swapping algorithm for travelers’ path choice at the lower level, is designed to solve the multi-objective programming problem at the middle level with certain government decisions. A numerical example with two SAV operators shows that the operator with higher-quality vehicles charges more but deploys a smaller fleet compared to the competitor deploying lower-cost vehicles. Government regulations can boost fleet utilization but are less effective when not strict.http://www.sciencedirect.com/science/article/pii/S2772586325000553Shared autonomous vehicleDuopoly competitionFleet sizePricingDynamic activity–travel assignment modelGovernment regulation |
| spellingShingle | Qing Li Zihao Yan Ke Lu Feixiong Liao A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation Multimodal Transportation Shared autonomous vehicle Duopoly competition Fleet size Pricing Dynamic activity–travel assignment model Government regulation |
| title | A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| title_full | A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| title_fullStr | A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| title_full_unstemmed | A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| title_short | A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| title_sort | duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation |
| topic | Shared autonomous vehicle Duopoly competition Fleet size Pricing Dynamic activity–travel assignment model Government regulation |
| url | http://www.sciencedirect.com/science/article/pii/S2772586325000553 |
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