Bicyclist injury severity in traffic crashes: A spatial approach for geo-referenced crash data to uncover non-stationary correlates |
| |
| Institution: | 1. Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, AL 35487, United States;2. Beaman Distinguished Professor & Transportation Program Coordinator, Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, AL 37996, United States;3. Alabama Transportation Institute, The University of Alabama, Tuscaloosa, AL 35487, United States;4. The Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, AL 35487, United States;5. Virginia Department of Transportation, Richmond, VA 23219, United States;1. Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, AL 35487, United States;2. Alabama Transportation Institute, The University of Alabama, Tuscaloosa, AL 35487, United States;3. Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN 37996, United States;1. Department of Physical Education, Sports and Recreation, Universidad de La Frontera, Av Francisco Salazar 01145, 4780000, Chile;2. Queensland University of Technology (QUT), School of Public Health and Social Work, Victoria Park Road, Brisbane, 4059, Australia;3. Queensland University of Technology (QUT), Institute of Health and Biomedical Innovation, 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia;4. UFRO Activate Research Group, Universidad de La Frontera, Av Francisco Salazar 01145, Temuco, 4780000, Chile;1. Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall, West Lafayette, IN 47907-2051, USA;2. Department of Civil and Environmental Engineering, University of South Florida, 4202 E Fowler Avenue, ENC 3300, Tampa, FL 33620, USA;1. Institute of Transport Studies, 23 College Walk (Building 60), Monash University, Clayton VIC, 3800, Australia;2. Institute of Transport Studies, 23 College Walk (Building 60), Monash University, Clayton VIC, 3800, Australia;3. Monash University Accident Research Centre, 21 Alliance Ln (Building 70), Monash University, Clayton VIC, 3800, Australia |
| |
| Abstract: | Introduction: Bicyclists are among vulnerable road users with their safety a key concern. This study generates new knowledge about their safety by applying a spatial modeling approach to uncover non-stationary correlates of bicyclist injury severity in traffic crashes. Method: The approach is Geographically Weighted Ordinal Logistic Regression (GWOLR), extended from the regular Ordered Logistic Regression (OLR) by incorporating the spatial perspective of traffic crashes. The GWOLR modeling approach allows the relationships between injury severity and its contributing factors to vary across the spatial domain, to account for the spatial heterogeneity. This approach makes use of geo-referenced data. This study explored more than 7,000 geo-referenced bicycle--motor-vehicle crashes in North Carolina. Results: This study performed a series of non-stationarity tests to identify local relationships that vary substantially across the spatial domain. These local relationships are related to the bicyclist (bicyclist age, bicyclist behavior, bicyclist intoxication, bicycle direction, bicycle position), motorist (driver age, driver intoxication, driver behavior, vehicle speed, vehicle type) and traffic (traffic volume). Conclusions: Results from the regular OLR are in general consistent with previous findings. For example, an increased bicyclist injury severity is associated with older bicyclists, bicyclist being intoxicated, and higher motor-vehicle speeds. Results from the GWOLR show local (rather than global) relationships between contributing factors and bicyclist injury severity. Practical Applications: Researchers and practitioners may use GWOLR to prioritize cycling safety countermeasures for specific regions. For example, GWOLR modeling estimates in the study highlighted the west part (from Charlotte to Asheville) of North Carolina for increased bicyclist injury severity due to the intoxication of road users including both bicyclists and drivers. Therefore, if a countermeasure is concerned with the road user intoxication, there may be a priority for the region from Charlotte to Asheville (relative to other areas in North Carolina). |
| |
| Keywords: | Bicycle--motor-vehicle crash Bicyclist injury severity Non-stationarity Geographically weighted ordinal logistic regression |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
