Advancing traffic microsimulation: a systematic review of parameter selection for connected and autonomous vehicles

The integration of Connected and Autonomous Vehicles (CAVs) is anticipated to transform transportation by enhancing traffic flow, safety and system efficiency. Microscopic simulation offers a promising framework to study automated mobility in scenarios where historical data for Autonomous Vehicles (AVs) and CAVs is limited. Incorporating AVs and CAVs requires adjusting parameters within existing behavioural models. However, the reliability of such simulations depends on the accuracy of parameter adjustments and assumptions about vehicle behaviour. This paper presents a systematic review of 54 studies (from 934 initially screened) to consolidate key parameters for modelling AVs and CAVs in traffic microscopic simulations. By comparing them to those used for human-driven vehicles, valuable insights are provided, including statistical summaries and boxplots, to inform the enhancement of simulation models. The findings provide a resource for researchers, supporting direct integration and refinement of AV/CAV parameters to improve the accuracy and reliability of future traffic simulations.