Abstract
This paper investigates the impact of ride-hailing services, particularly the integration of autonomous vehicles (AVs), on urban transportation systems. The paper discusses the challenges faced by ride-hailing platforms in managing a fleet of both AVs and conventional vehicles (CVs) within the spatial network of a city. It examines the approaches and methods used to manage demand allocation for AVs and CVs, considering the strategic behavior of human drivers and considerations for possible regulations. Using mean-field game theory, this paper proposes efficient strategies for managing fleet operations along with those of traffic optimization and service efficiency. The analysis highlights the complexities of integrating AVs into existing transportation systems and advocates for the development of robust theoretical traffic models for regulatory decisions and improved urban mobility.
| Original language | English |
|---|---|
| Pages (from-to) | 759-765 |
| Number of pages | 7 |
| Journal | Frontiers of Engineering Management |
| Volume | 11 |
| Issue number | 4 |
| DOIs |
|
| State | Published - Dec 2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- autonomous vehicles
- conventional vehicles
- mean-field game
- ride-hailing
- strategic behavior
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