Multiagent spatial simulation of autonomous taxis for urban commute : travel economics and environmental impacts

Abstract

With the likelihood of autonomous vehicle technologies in public transport and taxi systems increasing, their impact on commuting in real-world road networks is insufficiently studied. In this study, an agent-based model is developed to simulate how commuters travel by autonomous taxis (aTaxis) in real-world road networks. The model evaluates the travel costs and environmental implications of substituting conventional personal vehicle travel with aTaxi travel. The proposed model is applied to the city of Ann Arbor, Michigan, to demonstrate the effectiveness of aTaxis. The results indicate that to meet daily commute demand with wait times less than 3 min, the optimized autonomous taxi fleet size is only 20% of the conventional solo-commuting personal car fleet. Commuting cost decreases by 38%, and daily vehicle utilization increases from 14 to 92 min When using internal combustion engine aTaxis, energy consumption, greenhouse gas (GHG) emissions, and SO2 emissions are respectively 16, 25, and 10% higher than conventional solo commuting, mainly because of unoccupied repositioning between trips. Given the emission intensity of the local electricity grid, the environmental impacts of electric aTaxis do not show significant improvement over conventional vehicles.