Title
A correlated random parameter approach to investigate the effects of weather conditions on crash risk for a mountainous freeway
Abbreviated Journal Title
Transp. Res. Pt. C-Emerg. Technol.
Keywords
Aggregate traffic safety; Correlated random parameter model; Tobit; model; Weather warning system; FIXED DISPERSION PARAMETER; MOTOR-VEHICLE CRASHES; POISSON-GAMMA MODELS; SAMPLE-MEAN VALUES; ACCIDENT RATES; TOBIT ANALYSIS; FREQUENCY; SIZE; Transportation Science & Technology
Abstract
Freeway crashes are highly influenced by weather conditions, especially for a mountainous freeway affected by adverse weather conditions. In order to reduce crash occurrence, a variety of weather monitoring systems and Intelligent Transportation Systems (ITS) have been introduced to address the weather impact. However, the effects of weather conditions on crash occurrence have not been fully investigated and understood. With detailed weather information from weather monitoring stations, this study seeks to investigate the complex effects of weather factors, such as visibility and precipitation, on crash occurrence based on safety performance functions. Unlike conventional traffic safety studies which deal with crash frequency, crash rates per 100 million vehicle miles travelled were adopted as the dependent variable in this study. Three years of weather related crash data from a 15 mile mountainous freeway on 1-70 in Colorado were utilized. First, a fixed parameter Tobit model was estimated to unveil the effects of explanatory variables on crash rates. Then, in order to characterize the heterogeneous effects of weather conditions across the homogeneous segments, a traditional random parameter Tobit model was developed. Furthermore, for the purpose of monitoring the intricate interactions between weather conditions and geometric characteristics, a multivariate structure for the distribution of random parameters was introduced; which result in a correlated random parameter Tobit model. Likelihood ratio test results demonstrated that the correlated random parameter Tobit model was superior to the uncorrelated random parameter and fixed parameter Tobit models. Moreover, visibility and precipitation variables were found to have substantial correlations with geometric characteristics like steep downgrade slopes and curve segments. Results from the models will shed lights on future applications of weather warning systems to improve traffic safety. (C) 2014 Elsevier Ltd. All rights reserved.
Journal Title
Transportation Research Part C-Emerging Technologies
Volume
50
Publication Date
1-1-2015
Document Type
Article
Language
English
First Page
68
Last Page
77
WOS Identifier
ISSN
0968-090X
Recommended Citation
"A correlated random parameter approach to investigate the effects of weather conditions on crash risk for a mountainous freeway" (2015). Faculty Bibliography 2010s. 6903.
https://stars.library.ucf.edu/facultybib2010/6903
Comments
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