A method for relating type of crash to traffic flow characteristics on urban freeways |
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| Institution: | 1. Institute of Transportation Studies, University of California, 522 Social Science Tower, Irvine, CA 92697, USA;2. Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Irvine, CA 92697, USA;1. Professor of Civil and Environmental Engineering, Courtesy Department of Economics, University of South Florida, 4202 E. Fowler Avenue, ENC 3506, Tampa, FL 33620, United States;2. Professor of Civil Engineering, Pennsylvania State University, 226C Sackett Building, University Park, PA 16802, United States;3. Adnan Abou-Ayyash Centennial Professor in Transportation Engineering, Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St. Stop C1761, Austin, TX 78712, United States;1. Department of Modeling, Simulation & Visualization Engineering, Old Dominion University, 4700 Elkhorn Ave, Norfolk, VA 23529, USA;2. Department of Civil and Natural Resources Engineering, University of Canterbury 20 Kirkwood Ave, Christchurch, 8041, New Zealand;3. C2SMART Center (A Tier 1 USDOT UTC), Department of Civil and Urban Engineering, Center for Urban Science and Progress (CUSP), Tandon School of Engineering, New York University (NYU), Six MetroTech Center, 4th Floor (RM 404), Brooklyn, NY 11201, USA;4. Transport Studies Group, School of Architecture, Civil & Building Engineering, Loughborough University, Loughborough, LE11 3TU,United Kingdom;1. School of Public and Environmental Health, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia;2. Addis Continental Institute of Public Health, Addis Ababa, Ethiopia;3. School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia;4. Ministry of Transport, Addis Ababa, Ethiopia;5. World Health Organization (WHO) Ethiopia, Addis Ababa, Ethiopia |
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| Abstract: | A method is developed to determine how crash characteristics are related to traffic flow conditions at the time of occurrence. Crashes are described in terms of the type and location of the collision, the number of vehicles involved, movements of these vehicles prior to collision, and severity. Traffic flow is characterized by central tendencies and variations of traffic flow and flow/occupancy for three different lanes at the time and place of the crash. The method involves nonlinear canonical correlation applied together with cluster analyses to identify traffic flow regimes with distinctly different crash taxonomies. A case study using data for more than 1000 crashes in Southern California identified twenty-one traffic flow regimes for three different ambient conditions: dry roads during daylight (eight regimes), dry roads at night (six regimes), and wet conditions (seven regimes). Each of these regimes has a unique profile in terms of the type of crashes that are most likely to occur, and a matching of traffic flow parameters and crash characteristics reveals ways in which congestion affects highway safety. |
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