Title: Accident prediction models for urban roads

Authors: Amrita Sarkar; U. C. Sahoo; G. Sahoo

Addresses: Department of Information Technology, Birla Institute of Technology, Mesra, Ranchi 835215, Jharkhand, India. ' School of Infrastructure, Indian Institute of Technology Bhubaneswar, Bhubaneswar 751013, Odisha, India. ' Department of Information Technology, Birla Institute of Technology, Mesra, Ranchi 835215, Jharkhand, India

Abstract: Traffic accidents prediction has an important meaning to the improvement of traffic safety management, and urban traffic accidents prediction model. Different approaches for developing Accident Prediction Models (APMs) are used such as multiple linear regression, multiple logistic regression, Poisson models, negative binomial models, random effects models and various soft computing techniques such as fuzzy logic, artificial neural networks and more recently the neuro-fuzzy systems. This paper reviews application of these approaches for developing APMs and advantages of neuro-fuzzy system in modelling accidents in urban road links and intersections.

Keywords: accident prediction models; statistical techniques; soft computing; urban roads; modelling; road traffic accidents; fuzzy logic; artificial neural networks; ANNs; neuro-fuzzy systems; road links; road intersections; traffic safety management.

DOI: 10.1504/IJVS.2012.049020

International Journal of Vehicle Safety, 2012 Vol.6 No.2, pp.149 - 161

Received: 20 Dec 2011
Accepted: 06 Jun 2012
Published online: 31 Dec 2014 *

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