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Title:Impact of Connected Vehicle Technology on Traffic Safety under Different Highway Geometric Designs
Authors:Bahar Azin, Qinzheng Wang, Xianfeng Yang, and Yaobang Gong
University:University of Utah
Publication Date:Sep 2022
Report #:MPC-22-484
Project #:MPC-590
TRID #:01864874
Keywords:autonomous vehicles, connected vehicles, geometric design, high risk locations, traffic safety, traffic simulation


Connected and automated vehicle (CAV) driving features can impact traffic safety in many aspects owing to their improved driving behavior. On the other hand, road geometric design elements are mainly based on human reactions and behavior, which might affect safety depending on road layout and the parties involved. However, automation and connectivity can convey more data about the driving environment that will reduce confronting unexpected driving conditions and driving load on drivers. Therefore, the risk of crashes due to roadway geometries will be reduced. The main objective of this study is to focus on the performance of the traffic flow, including CAVs with different geometric designs addressing the potential crash spots. This study aims to determine the efficacy of CAVs on traffic network safety quantitively and qualitatively. For this purpose, multiple scenarios with different geometric features are designed and simulated. Simulations include varied CAV shares in traffic composition and employ CAV driving features. Using the surrogate safety assessment model (SSAM), simulation results are evaluated for potential conflicts. Crash severity, frequency, and classification are studied to determine the safety effects of CAVs in potential crash hot spots. Results indicated that higher penetration rates of CAVs could improve the safety performance of traffic networks in multiple cases by reducing deceleration rates, cooperative lane changing, and adjusted speed in required situations. However, due to the interaction of CAVs and HDVs in a signalized intersection, safety performance might not benefit from CAV presence.

How to Cite

Azin, Bahar, Qinzheng Wang, Xianfeng Yang, and Yaobang Gong. Impact of Connected Vehicle Technology on Traffic Safety under Different Highway Geometric Designs, MPC-22-484. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2022.

NDSU Dept 2880P.O. Box 6050Fargo, ND 58108-6050