Dr Grigorios Fountas G.Fountas@napier.ac.uk
Associate
Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach
Fountas, Grigorios; Sarwar, Md Tawfiq; Anastasopoulos, Panagiotis Ch.; Blatt, Alan; Majka, Kevin
Authors
Md Tawfiq Sarwar
Panagiotis Ch. Anastasopoulos
Alan Blatt
Kevin Majka
Abstract
Traditional accident analysis typically explores non-time-varying (stationary) factors that affect accident occurrence on roadway segments. However, the impact of time-varying (dynamic) factors is not thoroughly investigated. This paper seeks to simultaneously identify pre-crash stationary and dynamic factors of accident occurrence, while accounting for unobserved heterogeneity. Using highly disaggregate information for the potential dynamic factors, and aggregate data for the traditional stationary elements, a dynamic binary random parameters (mixed) logit framework is employed. With this approach, the dynamic nature of weather-related, and driving- and pavement-condition information is jointly investigated with traditional roadway geometric and traffic characteristics. To additionally account for the combined effect of the dynamic and stationary factors on the accident occurrence, the developed random parameters logit framework allows for possible correlations among the random parameters. The analysis is based on crash and non-crash observations between 2011 and 2013, drawn from urban and rural highway segments in the state of Washington. The findings show that the proposed methodological framework can account for both stationary and dynamic factors affecting accident occurrence probabilities, for panel effects, for unobserved heterogeneity through the use of random parameters, and for possible correlation among the latter. The comparative evaluation among the correlated grouped random parameters, the uncorrelated random parameters logit models, and their fixed parameters logit counterpart, demonstrate the potential of the random parameters modeling, in general, and the benefits of the correlated grouped random parameters approach, specifically, in terms of statistical fit and explanatory power.
Citation
Fountas, G., Sarwar, M. T., Anastasopoulos, P. C., Blatt, A., & Majka, K. (2018). Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach. Accident analysis and prevention, 113, 330-340. https://doi.org/10.1016/j.aap.2017.05.018
Journal Article Type | Article |
---|---|
Acceptance Date | May 21, 2017 |
Online Publication Date | Mar 7, 2018 |
Publication Date | 2018-04 |
Deposit Date | Sep 20, 2018 |
Journal | Accident Analysis & Prevention |
Print ISSN | 0001-4575 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 113 |
Pages | 330-340 |
DOI | https://doi.org/10.1016/j.aap.2017.05.018 |
Keywords | Public Health, Environmental and Occupational Health; Law; Safety, Risk, Reliability and Quality; Human Factors and Ergonomics; General Medicine |
Public URL | http://researchrepository.napier.ac.uk/Output/1302959 |
You might also like
To move or not to move: A review of residential relocation trends after COVID-19
(2024)
Journal Article
From self-reports to observations: Unraveling digital billboard influence on drivers
(2024)
Journal Article
Effective Trigger Speeds for Vehicle Activated Signs on 20 mph Roads in Rural Areas
(2024)
Journal Article
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search