Accident risk analysis and model applications of railway level crossings

Shou-Ren Hu; Kai Han Wu

doi:10.1109/ITSC.2008.4732661

Accident risk analysis and model applications of railway level crossings

Shou-Ren Hu, Kai Han Wu

Department of Transportation and Communication Management Science

Research output: Contribution to conference › Paper › peer-review

6 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 language	English
Pages	687-692
Number of pages	6
DOIs	https://doi.org/10.1109/ITSC.2008.4732661
Publication status	Published - 2008 Dec 1
Event	11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008 - Beijing, China Duration: 2008 Dec 10 → 2008 Dec 12

Other

Other	11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008
Country	China
City	Beijing
Period	08-12-10 → 08-12-12

All Science Journal Classification (ASJC) codes

Automotive Engineering
Mechanical Engineering
Computer Science Applications

Access to Document

10.1109/ITSC.2008.4732661

Cite this

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