A spatial agent-based approach to simulating the ride-hailing system and its environmental impacts

Abstract

Ride-hailing services could potentially optimize vehicle use and reduce emissions. To investigate the diffusion of ride-hailing services and its impacts at the individual level, we proposed a spatial agent-based model, which integrated the supply-demand dynamics, to simulate the behaviors of the service provider, drivers, and users in Shenzhen, China, from 2023 to 2038 in various future scenarios. The results of the baseline scenario (assuming the market would evolve as before from 2023 to 2038) show a 36 % increase in annual ride-hailing usage, a 24.63 % decrease in the average ride-hailing price, and a 73.16 % increase in drivers' compensation. Carbon emissions reduces by 33.13 % (given that ride-hailing services replace existing combined transportation modes). The what-if scenarios show that price and compensation affect the ride-hailing system in the early stages and further its carbon emission reduction potential. The results would be useful for policy making and optimization of a ride-haling system.