Safety propensity index for signalized and unsignalized intersections: Exploration and assessment

被引:14
作者
Schorr, Justin P. [1 ]
Hamdar, Samer H. [1 ]
机构
[1] George Washington Univ, Dept Civil & Environm Engn, Ctr Intelligent Syst Res, Traff & Networks Res Lab, Ashburn, VA 20147 USA
基金
美国国家科学基金会;
关键词
Index; Intersections; Safety; Signals; Structural equations; Traffic; SEVERITY LEVELS; CRASHES; MODEL;
D O I
10.1016/j.aap.2014.05.008
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
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. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:93 / 105
页数:13
相关论文
共 41 条
[1]   Exploring the overall and specific crash severity levels at signalized intersections [J].
Abdel-Aty, M ;
Keller, J .
ACCIDENT ANALYSIS AND PREVENTION, 2005, 37 (03) :417-425
[2]   Predicting injury severity levels in traffic crashes: A modeling comparison [J].
Abdel-Aty, MA ;
Abdelwahab, HT .
JOURNAL OF TRANSPORTATION ENGINEERING, 2004, 130 (02) :204-210
[3]   Analyzing angle crashes at unsignalized intersections using machine learning techniques [J].
Abdel-Aty, Mohamed ;
Haleem, Kirolos .
ACCIDENT ANALYSIS AND PREVENTION, 2011, 43 (01) :461-470
[4]  
[Anonymous], 2011, PREL DAT AN THIS PAP
[5]  
[Anonymous], 2003, 82 ANN M TRANSP RES
[6]  
[Anonymous], 2004, STRUCT EQ MOD THIS P
[7]  
[Anonymous], 2012, TRAFF SAF FACTS 2010
[8]   Multinomial Logistic Regression Model for Single-Vehicle and Multivehicle Collisions on Urban U.S. Highways in Arkansas [J].
Bham, Ghulam H. ;
Javvadi, Bhanu S. ;
Manepalli, Uday R. R. .
JOURNAL OF TRANSPORTATION ENGINEERING, 2012, 138 (06) :786-797
[9]   Microsimulation Approach for Predicting Crashes at Unsignalized Intersections Using Traffic Conflicts [J].
Caliendo, Ciro ;
Guida, Maurizio .
JOURNAL OF TRANSPORTATION ENGINEERING-ASCE, 2012, 138 (12) :1453-1467
[10]   Applying the random effect negative binomial model to examine traffic accident occurrence at signalized intersections [J].
Chin, HC ;
Quddus, MA .
ACCIDENT ANALYSIS AND PREVENTION, 2003, 35 (02) :253-259