Research Article Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures Mark Mario Morando, 1 Qingyun Tian, 2 Long T. Truong , 1 and Hai L. Vu 1 1 Monash Institute of Transport Studies, Department of Civil Engineering, Monash University, Melbourne, VIC, Australia 2 School of Civil and Environmental Engineering, Nanyang Technological University, Singapore Correspondence should be addressed to Long T. Truong; long.truong@monash.edu Received 30 November 2017; Revised 11 February 2018; Accepted 20 February 2018; Published 22 April 2018 Academic Editor: Abdelaziz Bensrhair Copyright © 2018 Mark Mario Morando et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce trafc crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. Tis 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 conficts extracted from the VISSIM trafc microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car- following model. Te safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety signifcantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conficts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically signifcant at  < 0.05). For the roundabout, the number of conficts is reduced by 29% to 64% with the 100% AV penetration rate (statistically signifcant at  < 0.05). 1. Introduction Autonomous vehicle (AV) technology has advanced signif- icantly in recent years. Automakers have already provided vehicles with some automated features (e.g., self-parking) and crash avoidance features such as automated braking, forward collision warning, lane departure warning, and blind spot monitoring [1, 2]. AV testing and piloting have begun in various countries. By 2014, AV testing on roadways has been legalised in four states in the US. In Australia, AV testing has been frst introduced in South Australia’s roadways in 2016 [3]. Te market penetration rate of AVs is estimated to be between 24% and 87% by 2045 [4, 5]. AVs have the potential to signifcantly improve road safety as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs [6–8]. It is also expected that AVs can travel with shorter headways due to improved safety, leading to increased road and intersection capacities [9, 10]. AVs would also provide improved mobility to the disabled, those who are too young to drive, and older people [11]. Other potential benefts of AVs include enhanced productive use of travel time, fewer emissions, better fuel efciency, and reduced parking costs [12, 13]. Implementing AVs within the road network has the potential to signifcantly reduce the number of crashes caused by the drivers through the gradual removal of human control [12]. Already, many vehicle manufacturers are increasing the implementation of features such as adaptive cruise control and parking assistance that enables the vehicle to park itself with minimal human intervention [14]. Many of these driver assistance features are partially automated, meaning that driver intervention is still required. Although the implemen- tation of automated features has increased in recent years, fully AVs are yet to be legally deployed on a large scale within the road network globally. Safety benefts of fully AVs would not be maximised without a high penetration rate of AVs [12]. Hindawi Journal of Advanced Transportation Volume 2018, Article ID 6135183, 11 pages https://doi.org/10.1155/2018/6135183