Evaluating the impact of autonomous vehicles on accessibility using agent-based simulation — A Case study of gunma prefecture

Abstract

The emergence of autonomous vehicles is expected to shape the urban transportation system in various ways. In this study, a large-scale agent-based disaggregate simulation model, MATSim, is employed to measure the impact of autonomous vehicles on accessibility changes. This study used disaggregate spatial data from the Gunma Prefecture Person Trip Survey as the initial travel demand input for the model. Two new autonomous transport modes, namely shared autonomous vehicle (SAV) and private autonomous vehicle (PAV), are included in the simulation, in addition to the existing human-driven private vehicles. A scenario analysis is conducted using fleet size of SAV, ownership of PAV, operation cost, value of time changes as the key variables in the scenario setting. Based on the final travel demand results, a Hansen-type accessibility analysis is conducted, providing quantitative evidence to measure the potential impact of autonomous vehicles on accessibility changes in Japanese regional cities. Results suggest a considerable market share of AVs in scenarios with positive assumptions, and an overall accessibility increase in the scenario where PAVs were introduced. Particularly, suburban areas seemed to enjoy more accessibility gains, which might result in further urban sprawl in the future.