A Systematic Review of Macro/Mesoscopic Agent-based Models for Assessing Vehicle Automation within Mobility Networks

Autonomous vehicles(AVs) occupy a crucial part of the emerging mobility. Currently, the potential impacts of self-driving fleets are of great interest to public bodies and authorities. The impact is studied in pilots, but these still have a limited scope, therefore also simulation studies are necessary. This study aims to offer a comprehensive review of recent macro/mesoscopic agent-based models for AVs. Through keyword search, we extracted twenty-nine papers from the Web of Science database. These studies analysed AVs' impact on the land-use, travel behaviour, environment and cost. Therefore, we summarise the similarities and particularities of modelling specifications and outcomes, meanwhile analysing the reasons for conflicting results. In general, the results from analysed papers are distinct from each other, and some even hold opposite results. There are several effective methods for increasing AVs' customer acceptance. When implemented, it will bring significant amounts of benefit, including much lower energy consumptions, emission, operational costs and parking space demands. However, a more congested network and urban sprawl are the most unignorable problems. Finally, this research offers several suggestions and research directions regarding AV future development, which will be referential for both researchers and urban planners.