Integration of Spatial Models for Web-based Risk Assessment of Road Accident

Sippakarn KASSAWAT; Sunya SARAPIROME; Vatanavongs RATANAVARAHA

Authors

Sippakarn KASSAWAT School of Remote Sensing, Suranaree University of Technology, Nakhon Ratchasima 30000
Sunya SARAPIROME School of Remote Sensing, Suranaree University of Technology, Nakhon Ratchasima 30000
Vatanavongs RATANAVARAHA Department of Transportation Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000

Keywords:

Spatial analysis, road accident risk assessment, spatial web-based application, Poisson regression model, Decision expert

Abstract

This study is a combination of the web-based system of the Poisson regression model and the Decision expert (DEX) approach to assess the risk of traffic accidents on each segment of Highway 304 in the province of Nakhon Ratchasima, Thailand. The variables of the Poisson model include average daily traffic (ADT), road geometric and environmental parameters. Geometric parameters were used in a factor analysis to the high accident segment portion of the road. The DEX was used as a tool to determine environmental parameters derived from environmental conditions potentially promoting road accidents. The system developed allows users’ interaction to vary environmental conditions subject to change with different times of a day and weather. The system can provide the analytical results to identify potential positions at risk of accidents on the highway based on individual users’ situations. The system developed can be used as a guide for planning and managing to reduce the number of accidents on the highway. Additionally, the system can provide warning information of road segments for highway users.

doi:10.14456/WJST.2015.62

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Author Biography

Sunya SARAPIROME, School of Remote Sensing, Suranaree University of Technology, Nakhon Ratchasima 30000

Head of the School of Remote Sensing

References

World Health Organization. Global Status Report on Road Safety 2013: Supporting a Decade of Action. WHO Press, Geneva, 2013, p. 1-4.

A Leelakajonjit. Comparison of international road accident database and Thailand’s. J. Soc. Transport. Traffic Stud. 2011; 3, 39-46.

B Nambuusi, T Brijs and E Hermans. A Review of Accident Prediction Models for Road Intersections. Policy Research Centre for Mobility and Public Works, Hasselt, 2008, p. 1-9.

RR Dinu and A Veeraragavan. Random parameter models for accident prediction on two-lane undivided highways in India. J. Saf. Res. 2011; 42, 39-42.

SH Kim, SB Chong, KH Song and KS Chon. Development of an accident prediction model using GLIM (Generalized Log-linear Model) and EB method: A case of Seoul. J. Eastern Asia Soc. Transport. Stud. 2005; 6, 3669-82.

T Arh and BJ Blazic. Application of multi-attribute decision making approach to learning management systems evaluation. J. Comput. 2007; 2, 28-37.

M Bohanec and V Rajkovic. Multi-attribute decision modeling: Industrial applications of DEX. Informatica 1999; 23, 487-91.

J Abellan, G Lopez and J Ona. Analysis of traffic accident severity using Decision Rules via Decision Trees. Expert Syst. Appl. 2013; 40, 6047-54.

M Bohanec, B Zupan and V Rajkovic. Applications of qualitative multi-attribute decision models in health care. Int. J. Med. Informat. 2000; 59, 191-205.

M Pipan, T Arh and BJ Blazic. Evaluation cycle management - model for selection of the most applicable learning management system. WSEAS Trans. Adv. Eng. Edu. 2008; 5, 129-36.

DG Kang, S Washington and J Oh. Modeling crash types: New insights into the effects of covariates on crashes on rural intersections. J. Transport. Eng. 2006; 132, 282-92.

C Lee and M Abdel-Aty. Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accid. Prev. 2005; 37, 775-86.

N Garber and A Ehrhart. The Effect of Speed, Flow, and Geometric Characteristic on Crash Rates for Different Types of Virginnia Highways. Virginia Transpotation Research Council, Virginia, 2000, p. 1-4.

R Lyles and W Taylor. Communicating changes in horizontal alignment, technical report Michigan State University. Transport. Res. Board 2006; 559, 60-3.

EH Choi. Crash Factors in Intersection-Related Crashes: An On-Scene Perspective. NHTSA’s National Center for Statistics and Analysis, Washington DC, 2010, p. 30-1.

J Ma and K Kockelman. Crash frequency and severity modeling using clustered data from Washington State. In: Proceedings of the 2006 IEEE Intelligent Transportation Systems Conference, Toronto, 2006, p. 1621-6.

P Liu, T Pan, JJ Lu and B Cao. Estimating capacity of u-turns at unsignalized intersection: Conflicting traffic volume, impedance effects, and left-turn lane capacity. Transport. Res. Rec. 2008; 32, 44-51.

P O Wanvik. Effects of road lighting: An analysis based on Dutch accident statistics 1987-2006. Accid. Anal. Prev. 2009; 41, 123-8.

A Williams. Teenage drivers: Patterns of risk. J. Saf. Res. 2003; 34, 5-15.

M Hijar, C Carrillo, M Flores, R Anaya and V Lopez. Risk factors in highway traffic accidents: A case control study. Accid. Anal. Prev. 2000; 32, 703-9.

D Lord, SP Washington and JN Ivan. Poisson, Poisson-gamma and zero-inflated regression models of motorvehicle crashes: Balancing statistical fit and theory. Accid. Anal. Prev. 2005; 37, 35-46.

D Lord. Application of accident prediction models for computation of accident risk on Transportation networks. Transport. Res. Board 2002; 1784, 17-26.

JL Martin. Relationship between crash-rate and hourly traffic flow on interurban motorways. Accid. Anal. Prev. 2002; 34, 19-29.

A Pande and M Abdel-Aty. Assessment of freeway traffic parameters leading to lane-change related collisions. Accid. Anal. Prev. 2006; 38, 936-48.