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An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

Author

Listed:
  • Kumar Sumit

    (Department of Work & Social Psychology, Maastricht University, 6200 MD Maastricht, The Netherlands
    UHasselt–Hasselt University, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium
    Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal 576104, India)

  • Veerle Ross

    (UHasselt–Hasselt University, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

  • Robert A. C. Ruiter

    (Department of Work & Social Psychology, Maastricht University, 6200 MD Maastricht, The Netherlands)

  • Evelien Polders

    (UHasselt–Hasselt University, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

  • Geert Wets

    (UHasselt–Hasselt University, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

  • Kris Brijs

    (UHasselt–Hasselt University, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

Abstract

Road crashes are the sixth leading cause of death in India. There has been a fourfold increase in the number of road traffic crashes in India in the last four decades and an increase of 9.8 times in the fatalities associated with that exponential increase. Manipal is a coastal place with a population of approximately 50,000 inhabitants lying in between the western Mountain range and the Arabian sea. The study’s objective is to explore the characteristics of fatal road crashes in Manipal from 2008–2018 using the data pertaining to fatal crashes retrieved from the office of the superintendent of police. Furthermore, it aims to forecast crashes by time series analysis prediction. The results show that most of the fatal crashes are due to exceeding the lawful speed limit, followed by driving under the influence of alcohol and going ahead and overtaking. The time series analysis forecasted the number of fatal crashes until the year 2025 and predicted that there will be an increase in the number of fatal road crashes by 4.5%. The results also provide essential leads for initiating specific intervention programmes targeting the causes of fatal road crashes.

Suggested Citation

  • Kumar Sumit & Veerle Ross & Robert A. C. Ruiter & Evelien Polders & Geert Wets & Kris Brijs, 2022. "An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India," Sustainability, MDPI, vol. 14(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2851-:d:761616
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    Cited by:

    1. Juan Pablo Montero-Salgado & Jose Muñoz-Sanz & Blanca Arenas-Ramírez & Cristina Alén-Cordero, 2022. "Identification of the Mechanical Failure Factors with Potential Influencing Road Accidents in Ecuador," IJERPH, MDPI, vol. 19(13), pages 1-27, June.

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