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Identification and Prioritization of Accident Blackspots in Surat, India, Using Geographical Information Systems

  • 2025
  • OriginalPaper
  • Chapter
Published in:
Authors
Manasi Mahajan
Aninda Bijoy Paul
Rohit Rathod
Shriniwas Arkatkar
Published in
Traffic Management, Operation, Safety and Emerging Technology
Publisher
Springer Nature Singapore

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Abstract

This chapter explores the identification and prioritization of accident blackspots in Surat, India, using Geographical Information Systems (GIS). The study focuses on the application of Kernel Density Estimation (KDE) and styled spatial density techniques to analyze crash data from 2018 to 2022. Key findings include the identification of high-risk areas such as Delhi Gate Junction, Udhana Darwaja, and the World Trade Centre on NH 6. The Total Severity Score (TSS) is used to rank and prioritize these blackspots, with Udhana Teen Rasta emerging as the location with the highest TSS. The chapter also presents a case study of the Khatushyam Mandir intersection, demonstrating the effectiveness of geometric improvements in reducing crash frequencies. The text concludes with recommendations for future studies, emphasizing the importance of data cleaning and targeted safety interventions.
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previous chapter Understanding the Driver Performance for Lower Levels of ADAS Using Kinematic Variables
next chapter Development of Conflicting Flow Model for Unsignalized Intersections: Tier-II Cities of India
Title
Identification and Prioritization of Accident Blackspots in Surat, India, Using Geographical Information Systems
Authors
Manasi Mahajan
Aninda Bijoy Paul
Rohit Rathod
Shriniwas Arkatkar
Copyright Year
2025
Publisher
Springer Nature Singapore
Book
Traffic Management, Operation, Safety and Emerging Technology

Print ISBN: 978-981-9681-17-4

Electronic ISBN: 978-981-9681-18-1

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-981-96-8118-1_17
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