Shared Autonomous Electric Vehicle: A Simulation Study on Operational Efficiency and Service Dynamics

Shared autonomous electric vehicles (SAEV) represent a transformative shift in urban mobility, promising enhanced flexibility and sustainability. This study investigates the impact of integrating SAEVs into a taxi-hailing aggregator, focusing on their operational efficiency and environmental benefits. Based on New York City trip data from high-volume for-hire vehicle (FHV) services, a simulation is conducted to model how such vehicles would operate, exploring fleet performance, environmental impact, and revenue while considering constraints such as charging infrastructure, fleet size, and real-time demand fuctuations in an urban setting. The simulation evaluates key metrics, including CO2 emissions, utilization, completed trips rate, and net revenue, comparing them with traditional 15-hour driver-based taxis and 24-hour hailing service. Our results confrm the initial expectations, demonstrating that SAEVs outperform traditional taxi services across all key metrics, irrespective of fleet size. The simulation reveals that, on average, net revenue increased by over 250%, while CO2 emissions were reduced by more than 100% compared to the benchmark services. In comparison to 24-hour hailing services, SAEVs clearly offer advantages in terms of revenue and environmental impact, though they do exhibit a decline in operational efficiency. Importantly, this decline can be mitigated through appropriate scaling of the SAEV feet..