Literature DB >> 24892876

Safety propensity index for signalized and unsignalized intersections: exploration and assessment.

Justin P Schorr1, Samer H Hamdar2.   

Abstract

The objective of this study is to develop a safety propensity index (SPI) for both signalized and unsignalized intersections. Through the use of a structural equation modelling (SEM) approach safety is quantified in terms of multiple endogenous variables and related to various dimensions of exogenous variables. The singular valued SPI allows for identification of relationships between variables and lends itself well to a comparative analysis between models. The data provided by the Highway Safety Information System (HSIS) for the California transportation network was utilized for analysis. In total 22,422 collisions at unsignalized intersections and 20,215 collisions at signalized intersections (occurring between 2006 and 2010) were considered in the final models. The main benefits of the approach and the subsequent development of an SPI are (1) the identification of pertinent variables that effect safety at both intersection types, (2) the identification of similarities and differences at both types of intersections through model comparison, and (3) the quantification of safety in the form of an index such that a ranking system can be developed. If further developed, the adopted methodology may assist in safety related decision making and policy analysis.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Keywords:  Index; Intersections; Safety; Signals; Structural equations; Traffic

Mesh:

Year:  2014        PMID: 24892876     DOI: 10.1016/j.aap.2014.05.008

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  Multilevel models for evaluating the risk of pedestrian-motor vehicle collisions at intersections and mid-blocks.

Authors:  D Alex Quistberg; Eric J Howard; Beth E Ebel; Anne V Moudon; Brian E Saelens; Philip M Hurvitz; James E Curtin; Frederick P Rivara
Journal:  Accid Anal Prev       Date:  2015-09-01

2.  Modeling Driver Behavior near Intersections in Hidden Markov Model.

Authors:  Juan Li; Qinglian He; Hang Zhou; Yunlin Guan; Wei Dai
Journal:  Int J Environ Res Public Health       Date:  2016-12-21       Impact factor: 3.390

  2 in total

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