title: What are the differences in driver injury outcomes at highway-rail grade crossings? Untangling the role of pre-crash behaviors.
abstract: Crashes at highway-rail grade crossings can result in severe injuries and fatalities to vehicle occupants. Using a crash database from the Federal Railroad Administration (N=15,639 for 2004-2013), this study explores differences in safety outcomes from crashes between passive controls (Crossbucks and STOP signs) and active controls (flashing lights, gates, audible warnings and highway signals). To address missing data, an imputation model is developed, creating a complete dataset for estimation. Path analysis is used to quantify the direct and indirect associations of passive and active controls with pre-crash behaviors and crash outcomes in terms of injury severity. The framework untangles direct and indirect associations of controls by estimating two models, one for pre-crash driving behaviors (e.g., driving around active controls), and another model for injury severity. The results show that while the presence of gates is not directly associated with injury severity, the indirect effect through stopping behavior is statistically significant (95% confidence level) and substantial. Drivers are more likely to stop at gates that also have flashing lights and audible warnings, and stopping at gates is associated with lower injury severity. This indirect association lowers the chances of injury by 16%, compared with crashes at crossings without gates. Similar relationships between other controls and injury severity are explored. Generally, crashes occurring at active controls are less severe than crashes at passive controls. The results of study can be used to modify Crash Modification Factors (CMFs) to account for crash injury severity. The study contributes to enhancing the understanding of safety by incorporating pre-crash behaviors in a broader framework that quantifies correlates of crash injury severity at active and passive crossings.
authors.affiliation: Department of Civil and Environmental Engineering, The University of Tennessee, 311 John Tickle Building, Knoxville, TN 37996, United States. Electronic address: jliu34@utk.edu.
authors.forename: Jun
authors.initials: J
authors.lastname: Liu
authors.affiliation: Department of Civil and Environmental Engineering, The University of Tennessee, 322 John Tickle Building, Knoxville, TN 37996, United States. Electronic address: akhattak@utk.edu.
authors.forename: Asad J
authors.initials: AJ
authors.lastname: Khattak
authors.affiliation: Center for Transportation Research, The University of Tennessee, 309 Conference Center Building, Knoxville, TN 37996, United States. Electronic address: stever@utk.edu.
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Richards
authors.affiliation: Department of Civil and Environmental Engineering, The University of Tennessee, 320 John Tickle Building, Knoxville, TN 37996, United States. Electronic address: shashi@utk.edu.
authors.forename: Shashi
authors.initials: S
authors.lastname: Nambisan
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001334:Automobile Driving / Q000523:psychology*; D016208:Databases, Factual; D005260:Female; D006801:Humans; D008123:Location Directories and Signs / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011336:Probability; D011890:Railroads / Q000706:statistics & numerical data*; D012044:Regression Analysis; D015599:Trauma Severity Indices; D014481:United States
keywords: Controls; Data imputation; Grade crossing; Injury severity; Path analysis; Pre-crash behavior