Investigating safety impacts of autonomous vehicles using traffic micro-simulation

Autonomous Vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are highly expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs etc. However, very little research has been conducted to estimate safety impacts of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from VISSIM traffic micro-simulator using Surrogate Safety Assessment Model (SSAM). Behaviours of Human-driven Vehicles (HVs) and AVs (level 4 automation) are modelled within VISSIM’s car following model. The safety investigation is conducted for two case studies, including a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they are expected to travel with shorter headways to improve road capacity. For the signalised intersection, AVs reduce the number of conflicts by 20% to 47% with the penetration rates of between 50% and 100% (statistically significant at p<0.05). For the roundabout, the number of conflicts is reduced by 29% to 32% with the 100% AV penetration rate (statistically significant at p<0.05).¹