Volume List  / Volume 2 (3)

Article

INVESTIGATION OF THE EFFECT OF TRAFFIC PARAMETERS ON ROAD HAZARD USING CLASSIFICATION TREE MODEL

DOI: 10.7708/ijtte.2012.2(3).08


2 / 3 / 271-285 Pages

Author(s)

Md. Mahmud Hasan - School of Civil, Environmental and Chemical Engineering, RMIT University, Melbourne 3001, Australia -


Abstract

This paper presents a method for the identification of hazardous situations on the freeways. For this study, about 18 km long section of Eastern Freeway in Melbourne, Australia was selected as a test bed. Three categories of data i.e. traffic, weather and accident record data were used for the analysis and modelling. In developing the crash risk probability model, classification tree based model was developed in this study. In formulating the models, it was found that weather conditions did not have significant impact on accident occurrence so the classification tree was built using two traffic indices; traffic flow and vehicle speed only. The formulated classification tree is able to identify the possible hazard and non-hazard situations on freeway. The outcome of the study will aid the hazard mitigation strategies.


Download Article

Number of downloads: 3274


Acknowledgements:

The author is greatly indebted to Dr. Shamas Bajwa for his helpful and expert suggestions. Thanks to Mr. Jude Jusayan and Tim Strickland of Vic Roads and the authority of Bureau of Meteorology (Australia) for providing the data.


References:

Aarts, L.; Ingrid, V.S. 2006. Driving speed and the risk of road crashes: A review, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/j.aap.2005.07.004, 38(2): 215-224.

 

Aljanahi, A.A.M.; Rhodes, A.H.; Metcalfe, A.V. 1999. Speed, speed limits and road traffic accidents under free flow conditions, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(98)00058-X, 31(1–2): 161-168.

 

Ayati, E.; Abbasi, E. 2011. Investigation on the role of traffic volume in accidents on urban highways, Journal of Safety Research, DOI: http://dx.doi.org/10.1016/j.jsr.2011.03.006, 42(3): 209-214.

 

Breiman, L.; Friedman, J.H.; Olshen, R.A.; Stone, C.J. 1984. Classification and regression trees. Wadsworth & Brooks/Cole Advanced Books & Software, Belmont, CA, United States of America.

 

Dickerson, A.; Peirson, J.; Vickerman, R. 1998. Road accidents and traffic flows: an econometric investigation. Available from Internet: ftp://ftp.ukc.ac.uk/pub/ejr/RePEc/ukc/ukcedp/9809.pdf.

 

Durduran, S.S. 2010. A decision making system to automatic recognize of traffic accidents on the basis of a GIS platform, Expert Systems with Applications, DOI: http://dx.doi.org/10.1016/j.eswa.2010.04.068, 37(12): 7729-7736.

 

Eisenberg, D. 2004. The mixed effects of precipitation on traffic crashes, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(03)00085-X, 36(4): 637-647.

 

Elvik, R.; Christensen, P.; Amundsen, A. 2004. Speed and road accidents: An evaluation of the Power Model. Institute of Transport Economics, Oslo, Norway. 134 p.

 

Gang, R.; Zhuping, Z. 2011. Traffic safety forecasting method by particle swarm optimization and support vector machine, Expert Systems with Applications, DOI: http://dx.doi.org/10.1016/j.eswa.2011.02.066, 38(8): 10420-10424.

 

Golob, T.F.; Recker, W.W.; Alvarez V. 2004. Freeway safety as a function of traffic flow, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/j.aap.2003.09.006, 36(6): 933-946.

 

Goodwin, L.C. 2002. Weather Impacts on Arterial Traffic Flow. Prepared for the Federal Highway Administration (FHWA) Road Weather Management Program. United States of America. 5 p.

 

Greibe, P. 2003. Accident prediction models for urban roads, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(02)00005-2, 35(2): 273-285.

 

Hasan, M.M.; Bajwa, S.; Horan, E.; Chung, E. 2011. Investigation of the effect of rainfall and traffic on road accidents. In Proceeding of the 2nd International Transport Research Conference. University Sains Malaysia, Pulau Pinang, Malaysia: 145-153.

 

Higgs, R.; Cummins, D. 2003. Recursive Partitioning, Lecture for CHM696D, Statistical & Information Sciences, Lilly Research Laboratories. Available from Internet: http://miner.chem.purdue.edu/Lectures/Lecture15%20-%20Higgs_RP.pdf.

 

Hong, D.; Kim, J.; Kim, W.; Lee, Y.; Yang, H.C. 2005. Development of traffic accident prediction models by traffic and road characteristics in urban areas. In Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5: 2046-2061.

 

Jean-Louis, M. 2002. Relationship between crash rate and hourly traffic flow on interurban motorways, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(01)00061-6, 34(5): 619-629.

 

Kalokota, K.R.; Seneviratne, P.N. 1994. Accident prediction models for two-lane rural highways. Available from Internet: http://www.mountain-plains.org/pubs/pdf/MPC94-32.pdf.

 

Lord, D.; Manar, A.; Vizioli, A. 2005. Modeling crash-flowdensity and crash-flow-V/C ratio relationships for rural and urban freeway segments, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/j.aap.2004.07.003, 37(1): 185-199.

 

Mustakim, F.; Yusof, I.; Onn, H.; Rahman, I.; Samad, A.A.A.; Salleh, N.E.B.M., 2008. Blackspot Study and Accident Prediction Model Using Multiple Liner Regression. First International Conference on Construction in Developing Countries (ICCIDC–I): Advancing and Integrating Construction Education, Research & Practice. Karachi, Pakistan.

 

Navon, D. 2003. The paradox of driving speed: two adverse effects on highway accident rate, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(02)00011-8, 35(3): 361-367.

 

Ossiander, E.M.; Cummings, P. 2002. Freeway speed limits and traffic fatalities in Washington State, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/S0001-4575(00)00098-1, 34(1): 13-18.

 

Pham, M.H.; Bhaskar, A.; Chung, E.; Dumont, A.-G. 2010. Random forest models for identifying motorway Rear-End Crash Risks using disaggregate data. In Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC), DOI: http://dx.doi.org/10.1109/ITSC.2010.5625003. 468-473.

 

Rujun, Y.; Xiuqing, L. 2010. Study on Traffic Accidents Prediction Model Based on RBF Neural Network. In Proceedings of the 2nd International Conference on Information Engineering and Computer Science (ICIECS), DOI: http://dx.doi.org/10.1109/ICIECS.2010.5678126. 1-4.

 

Shankar, V.; Fred. M.; Woodrow, B. 1995. Effect of roadway geometrics and environmental factors on rural freeway accident frequencies, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/0001-4575(94)00078-Z, 27(3): 371-389.

 

Taylor, M.C.; Lynam, D.A.; Baruya, A. 2000. The effects of drivers’ speed on the frequency of road accidents. Road Safety Division, Department of the Environment, Transport and the Regions. United Kingdom. 50 p.

 

Therneau, T.M.; Atkinson, E.J. 1997. An introduction to recursive partitioning using the RPART routines. Technical report, Mayo Foundation. United States of America. 52 p.

 

Wang, C.; Quddus, M.A.; Ison, S.G. 2009. Impact of traffic congestion on road accidents: A spatial analysis of the M25 motorway in England, Accident Analysis & Prevention, DOI: http://dx.doi.org/10.1016/j.aap.2009.04.002, 41(4): 798-808.