Identification of Accident-Prone Road Sections by Using Relative Frequency Method

In this study, assuming that traffic accident occurrence is determined by some road and environment related factors, and future traffic accidents will occur under the same conditions as past traffic accidents, use of Relative Frequency Method (RFM) (also called frequency ratio method) in the determination of accident-prone road sections is investigated. Method was tested on a highway in Trabzon province of Turkey. At the end of the study, sensitivity and specificity values were calculated as 1.00 and 0.83 respectively, which reflects that the method identified all of the 'accident-prone' sections (there is no false negative) and the method has very strong ability to distinguish 'relatively safe' sections. The most useful property of the method is that, if accident data does not exist due to any reason for some part of the road, method can be still used to identify accident-prone sections by using the road properties.

[1]  Shaw-Pin Miaou,et al.  Bayesian ranking of sites for engineering safety improvements: decision parameter, treatability concept, statistical criterion, and spatial dependence. , 2005, Accident; analysis and prevention.

[2]  Ezra Hauer,et al.  Observational Before-After Studies in Road Safety , 1997 .

[3]  Saro Lee,et al.  Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models , 2006 .

[4]  Wen Cheng,et al.  Experimental evaluation of hotspot identification methods. , 2005, Accident; analysis and prevention.

[5]  Esmaeel Ayati,et al.  Identification and Prioritization of Hazardous Road Locations by Segmentation and Data Envelopment Analysis Approach , 2013 .

[6]  L. Ayalew,et al.  Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications , 2005 .

[7]  Bhagwant Persaud.  SAFETY MIGRATION, THE INFLUENCE OF TRAFFIC VOLUMES, AND OTHER ISSUES IN EVALUATING SAFETY EFFECTIVENESS--SOME FINDINGS ON CONVERSION OF INTERSECTIONS TO MULTIWAY STOP CONTROL , 1986 .

[8]  Tom Brijs,et al.  Multiple Criterion Decision-Making Approach for Prioritizing Accident Hot Spots in Developing Countries in the Absence of Crash Data , 2010 .

[9]  Isik Yilmaz,et al.  Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) , 2009, Comput. Geosci..

[10]  Biswajeet Pradhan,et al.  Application of Airborne LiDAR-Derived Parameters and Probabilistic-Based Frequency Ratio Model in Landslide Susceptibility Mapping , 2012 .

[11]  Liping Fu,et al.  Bayesian multiple testing procedures for hotspot identification. , 2007, Accident; analysis and prevention.

[12]  Hwasoo Yeo,et al.  Evaluating the performance of network screening methods for detecting high collision concentration locations on highways. , 2013, Accident; analysis and prevention.

[13]  Li-Yen Chang,et al.  Data mining of tree-based models to analyze freeway accident frequency. , 2005, Journal of safety research.

[14]  Aykut Akgün.  A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey , 2012 .

[15]  Xiao Qin,et al.  Identifying crash-prone locations with quantile regression. , 2010, Accident; analysis and prevention.

[16]  B. Pradhan,et al.  Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya , 2014, Arabian Journal of Geosciences.

[17]  Aykut Akgün,et al.  A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods , 2013, Natural Hazards.

[18]  Bhagwant Persaud,et al.  COMPARISON OF TWO METHODS FOR DEBIASING BEFORE-AND-AFTER ACCIDENT STUDIES (DISCUSSION AND CLOSURE) , 1984 .

[19]  M. Abdel-Aty,et al.  Crash data analysis: collective vs. individual crash level approach. , 2007, Journal of safety research.

[20]  Ali Tavakoli Kashani,et al.  Identification of Black Spots Based on Reliability Approach , 2013 .

[21]  A. Akgun.  A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey , 2012, Landslides.

[22]  Saro Lee,et al.  Probabilistic landslide susceptibility and factor effect analysis , 2005 .

[23]  Alfonso Montella,et al.  A comparative analysis of hotspot identification methods. , 2010, Accident; analysis and prevention.