Simulating the relative influence of tire,vehicle and driver factors on forward collision accident rates |
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| Institution: | 1. College of Medicine and Life Sciences, University of Toledo, 700 Children’s Drive, Columbus, OH 43205-2664, United States;2. Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children’s Hospital, 700 Children’s Drive, Columbus, OH 43205, United States;3. Department of Pediatrics, College of Medicine, The Ohio State University, 700 Children’s Drive, Columbus, OH 43205, United States;4. Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, 984395 Nebraska Medical Center, Omaha, NE 68198-4395, United States;5. Center for Surgical Outcomes Research and Center for Innovation in Pediatric Practice, Abigail Wexner Research Institute at Nationwide Children’s Hospital, 700 Children’s Drive, Columbus, OH 43205, United States;6. Division of Epidemiology, College of Public Health, The Ohio State University, 700 Children’s Drive, Columbus, OH 43205, United States;1. Chongqing Key Laboratory of Vehicle Crash/Bio-Impact and Traffic Safety, Department 4, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China;2. Department of Medical Engineering, Daping Hospital, Army Medical University, Chongqing, China;3. Department of Medical Engineering, People’s Liberation Army 958th Hospital, Chongqing, China;1. Division of Injury Prevention, National Center for Injury Prevention and Control, CDC, Atlanta, Georgia, USA;2. Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA;3. TJFACT Consulting, Atlanta, Georgia, USA;1. Qatar University – Qatar Transportation and Traffic Safety Center, College of Engineering, P.O. Box 2713, Doha, Qatar;2. UHasselt, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium;3. Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan |
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| Abstract: | Introduction: There is currently a strong focus within the automotive industry centered on traffic safety, with topics such as distracted driving, accident avoidance technologies, and autonomous vehicles. These papers tend to focus on the possible improvements from a single factor. However, there are many factors that are present in each accident, and it is important to understand the influence of each factor on the relative accident risk in order to identify the most effective approaches for improving driver safety. Rear-end accidents tend to be the most common accident type with approximately 1.8 M cases, or 31% of all accidents, in 2012, according to NHTSA. Of the rear-end accident scenarios, approximately 18–23% occur on wet surfaces. Method: A Monte Carlo Forward Collision Simulation models the conditions of a wet rear-end accident and estimates the relative impact of various vehicle collision parameters. The model takes distributions of these parameters as inputs, and outputs a risk of collision relative to a known reference case. The parameters that can be studied include: tire grip level, road grip level, vehicle velocity, following distances, and the presence of vehicle technologies (ABS, FCW & AEB). Distributions of some of these parameters have been improved thanks to Naturalistic Driving Study data from SHRP2. Results: This study shows that these vehicle systems have a large impact on safety and can change the amount of influence attributed to other parameters such as tire grip levels. As the use of automated vehicle systems expands, so will the influence of tire grip performance levels on collision risks. Practical Applications: It is more important than ever for consumers and auto manufacturers to consider tire performance levels. Therefore, the tire industry should continue to focus on wet grip as a key performance related to safety and should strive to continue to improve tire performance. |
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| Keywords: | Wet braking Accidents Simulations Automated vehicles Tire performance |
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