• Mohit Nandal
• Navdeep Mor
• Dr. Hemant Sood

Road accident is one of the major problems for most communities in developing countries, where 90% of the world road accident fatalities occur (WHO), which require serious attention in searching for preventive measures to minimize this problem. Next to human suffering, traffic accidents also result in huge social and economic costs. Road accidents can be the consequence of different factors like environmental, human, vehicle, and road factors. The most important factor is the experience and the alertness of the road user. The road characteristics and features of the immediate environment are a second important factor. Evaluation of road safety measures appears to be the weakest component of road safety management systems. To improve Road Infrastructure Safety Management, road authorities, road designers and road safety practitioners need prediction tools, commonly known as Accident Prediction Models (APMs), allowing them to analyse the potential safety issues, to identify safety improvements and to estimate the potential effect of these improvements in terms of crash reduction. This study aims to review of the development of crash prediction models, and their applications to analyse and identify black spots to improve road safety. Several modelling techniques have been reviewed in this study including, multiple linear regression, Poisson distribution, negative binomial, random effect technique, and multiple logistic regression models to identify their suitability to develop the crash prediction models. The models identified in this research are already being used but the modelling approaches can be further modified to include the latest technical application on roads, available post-crash management system or safety culture which are commonly related road safety outcomes.

Road Accident, APM, Black Spot mangement

"An Overview of Crash Prediction Models and Their Suitability in Black Spot Identification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.362-369, June 2019, Available :http://www.jetir.org/papers/JETIR1906P56.pdf

"An Overview of Crash Prediction Models and Their Suitability in Black Spot Identification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp362-369, June 2019, Available at : http://www.jetir.org/papers/JETIR1906P56.pdf