Journal of Transportation Technologies

Journal of Transportation Technologies

ISSN Print: 2160-0473
ISSN Online: 2160-0481
www.scirp.org/journal/jtts
E-mail: jtts@scirp.org
"Crash Severity Analysis of Single Vehicle Run-off-Road Crashes"
written by Sunanda Dissanayake, Uttara Roy,
published by Journal of Transportation Technologies, Vol.4 No.1, 2014
has been cited by the following article(s):
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[15] Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: A case study of North Carolina
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[17] A copula-based approach for jointly modeling crash severity and number of vehicles involved in express bus crashes on expressways considering temporal stability of …
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[18] Modeling severity of motorcycle crashes with Dirichlet process priors
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[19] Risk Factors Affecting Driver Severity of Single-Vehicle Run Off Road Crash for Thailand Highway
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[20] Analyzing injury severity of rear-end crashes involving large trucks using a mixed logit model: A case study in North Carolina
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[21] A comparison between artificial neural network and hybrid intelligent genetic algorithm in predicting the severity of fixed object crashes among elderly drivers
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[22] A Comprehensive Review on Risk Factors Affecting the Crash Severity
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[23] Modeling head-on crash severity with drivers under the influence of alcohol or drugs (DUI) and non-DUI
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[26] Severity analysis of tree and utility pole crashes: Applying fast and frugal heuristics
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[27] Incorporating travel time reliability in predicting the likelihood of severe crashes on arterial highways using non-parametric random-effect regression
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[28] Analysis of head-on crash injury severity using a partial proportional odds model
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[29] Modeling head-on crash severity on NCDOT freeways: a mixed logit model approach
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[30] Traffic Safety Benefit of A Lane Departure Warning System
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[31] Design and experiment verification of a novel analysis framework for recognition of driver injury patterns: from a multi-class classification perspective
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[32] Understanding Fixed Object Crashes with SHRP2 Naturalistic Driving Study Data
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[33] Modeling Unobserved Heterogeneity and the Injury Severities of Truck Drivers in Run-Off-Road (ROR) Crashes: Econometric Methods and Applications
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[34] Definition of run-off-road crash clusters—For safety benefit estimation and driver assistance development
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[35] Review of crash prediction models and their applicability in black spot identification to improve road safety
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[36] Effectiveness of Experimental Left-Turn Sign Usage in Terms of Crashes and Analyzing Severity of Left Turn Crashes in Alaska
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[37] Likelihood estimation of secondary crashes using Bayesian complementary log-log model
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[38] Safety Evaluation of Alternative Audible Lane Departure Warning Treatments in Reducing Traffic Crashes: An Empirical Bayes Observational Before–After Study
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[39] Exploratory analysis of run-off-road crash patterns
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[40] Safety Analysis Considering the Impactof Travel Time Reliability on Elderly Drivers
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[42] Investigating Factors Affecting the Occurrence and Severity of Rear-End Crashes
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[44] Analysis of the Severity of Large Truck Crashes Using the Ordered Probit Model
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[45] Modeling severity of single vehicle run-off-road crashes in rural areas: model comparison and selection
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[46] Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways
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[47] Factors influencing road accidents in Sri Lanka: a logistic regression approach
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[48] Roadside Features in Crash Prediction Models: Data Collection and Evaluation
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[49] Assessment of the Psychosocial Behavior Associated with Elderly Drivers to Reduce Their Involvement in Crashes
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[52] Examining the Factors Affecting the Severity of Run-off-Road Crashes in Abu Dhabi
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[53] 山区高速公路交通死亡事故显著影响因素鉴别
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[54] Examining the differences between contributing factors affecting the severity of single and multi-vehicle Crashes
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[55] Characteristics of serious crashes at signalized intersections In Abu Dhabi City, UAE
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