Assessing Autonomous Mobility-on-Demand Services and the Impacts of Operational Strategies: A Case Study of Chengdu, China

Research utilizing a simulation framework in Chengdu, China, indicates that Autonomous Mobility-on-Demand (AMoD) services hold potential as an alternative to traditional urban street-hailing. The study evaluates AMoD's operational performance, focusing on passenger waiting times, deadheading mileage, and energy consumption, while also assessing the impact of various operational strategies.

Why it matters

The emergence of Autonomous Mobility-on-Demand (AMoD) services could significantly reshape urban transportation paradigms, offering potential for improved efficiency and sustainability. Understanding AMoD's operational performance and the effectiveness of various strategies is crucial for strategic planning and investment in future mobility solutions.

Key insights

• A simulation framework was developed to integrate a graph theory-based trip-vehicle matching mechanism.
• Historical street-hailing operational data from Chengdu, China, was used to simulate AMoD services.
• Operational performance of AMoD and traditional street-hailing was evaluated using average passenger waiting time (APWT), average deadheading mileage (ADM), and average deadheading energy consumption (ADEC).
• The study aims to clarify the operational effectiveness of AMoD relative to traditional services and the efficacy of associated operational strategies.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2511.06074