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      Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

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      Journal of Advanced Transportation

      Hindawi Limited

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          Abstract

          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 traffic 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. 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 the VISSIM traffic 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. The 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 significantly 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 conflicts by 20% to 65% with the AV 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 64% with the 100% AV penetration rate (statistically significant at p < 0.05 ).

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          Most cited references 19

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          Policy and society related implications of automated driving: A review of literature and directions for future research

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            Using an Activity-Based Model to Explore the Potential Impacts of Automated Vehicles

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              Examining accident reports involving autonomous vehicles in California

              Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Department of Motor Vehicles has mandated that reports of accidents involving autonomous vehicles be drafted and made available to the public. The present work shows an in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California (testing data from September 2014 to March 2017). The data provides important information on autonomous vehicles accidents’ dynamics, related to the most frequent types of collisions and impacts, accident frequencies, and other contributing factors. The study also explores important implications related to future testing and validation of semi-autonomous vehicles, tracing the investigation back to current literature as well as to the current regulatory panorama.
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                Author and article information

                Journal
                Journal of Advanced Transportation
                Journal of Advanced Transportation
                Hindawi Limited
                0197-6729
                2042-3195
                2018
                2018
                : 2018
                : 1-11
                Affiliations
                [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
                Article
                10.1155/2018/6135183
                b32e7cdc-f3ae-4ce2-8dba-153931df82d7
                © 2018

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