Accident risk analysis and model applications of railway level crossings

Shou-Ren Hu, Kai Han Wu

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

In order to reduce property loss and casualties from level crossing accidents, it is crucial to develop effective accident prediction models that are capable of providing effective information of accident frequency and severity given a vector of covariates. In the present research, a set of statistical count and categorical data models are developed; they are not only able to evaluate accident frequency and severity but also capable of exploring the potential risk factors that are responsible for traffic accidents. Using the data set collected by the Ministry of Transportation and Communication (MOTC) in 1998, which consist of both historical accident data and railway level crossing related data, the empirical study identifies a vector of factors that are significantly associated with accident frequency and/or severity. Finally, the developed accident frequency and severity models are also employed to provide the evaluation of black spots and countermeasure effects.

Original languageEnglish
Pages687-692
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 1
Event11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008 - Beijing, China
Duration: 2008 Dec 102008 Dec 12

Other

Other11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008
CountryChina
CityBeijing
Period08-12-1008-12-12

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Hu, S-R., & Wu, K. H. (2008). Accident risk analysis and model applications of railway level crossings. 687-692. Paper presented at 11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008, Beijing, China. https://doi.org/10.1109/ITSC.2008.4732661