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Blackspot Identification and Cluster Analysis of Small Sized Indian Cities of Patiala and Rajpura

India has been witnessing a persistent increase of road traffic fatalities, which has resulted in an estimated 3% GDP loss. Thus road safety initiatives need to be taken to improve the road safety scenario. Blackspot identification is the initial step of safety improvement programs. A number of methods have been proposed to identify blackspots. Among these methods, previous studies have indicated that Empirical Bayes method outperforms other methods in giving most accurate and reliable estimates of blackspots. The study identifies the blackspots in the cities of Patiala and Rajpura using data from first information reports (FIRs), and traffic and geometric details of the cities using the Empirical Bayes method by optimizing Negative Binomial likelihood function. Eight, seventeen and thirty-five blackspot segments have been identified in Rajpura, rural Patiala, and urban Patiala respectively. Further, the pattern of crashes on these blackspots have been studied and the deficiencies in existing roadway designs have been identified. Based on the study findings, the paper also provides recommendations to improving traffic safety in the case study cities.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABE90 Standing Committee on Transportation in the Developing Countries.
  • Authors:
    • Dhanoa, Kirat Kaur
    • Tiwari, Geetam
    • Malayath, Manoj
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01659923
  • Record Type: Publication
  • Report/Paper Numbers: 18-01672
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 13 2018 9:52AM