Abstract

Road traffic injuries continue to be a major health burden in India. In 2016 itself 1 50 785 persons were killed and 4 94 624 injured in road traffic crashes in India according to government statistics. Recently government of India has taken various policy level initiatives to reduce the road traffic crashes on Indian highways. One of the dimensions of these policies is the blackspot identification and treatment on various National and State highways of India.

Ministry of Roads Transport and Highways (MoRTH) has issued a specific definition for identifying blackspots and states have been asked to identify black spots. Top priority has been accorded to correction of blackspots on National Highways. Short-term measures such as rumble strips, reflective stickers at junctions, fixing signboard/cautionary board, providing signage and speed restrictions are being used. Whereas, long-term measures such as construction of vehicular under-pass, By-pass, flyover and 4-laning are being taken up.

Blackspots are the locations of the high crashes on the highways. Traditionally, the locations are ranked by crash rate, crash frequency or severity index. Researchers have tried to develop various techniques and indices to justify the identification of blackspots. In principle, each road type is said to have a characteristic mix of accident severity. The observed accident frequency is an unreliable estimate of the accident frequency when a short accident history is used. Empirical Bayes (EB) estimate can be used to predict accident frequency of road section and rank them accordingly. EB approach is recommended to reduce regression to mean error.

This study assess the effectiveness of blackspot identification and rectification policy of the government. The study highlights the strengths and drawbacks of the policy based on specific case studies and recommends measures to improve the process of identification and rectification of blackspots.