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Overview of Truck Accidents in India and Its Economic Loss Estimation
Technical Paper
2021-26-0007
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
India contributed to 11% of the global road accidents and was ranked 1st among road deaths according to the latest World Health Organization (WHO) report 2018. Indian National Highways (NH) is a meagre 5% of the country’s road network but accounts for 55% of the road accidents and 61% of the road deaths. Majority of the freight traffic is ferried by Commercial Vehicles (CV) or trucks along these highways and this in turn increases the probability of them being involved in a road accident. The country’s economy is forecasted to thrive in the coming years and hence the requirement of CVs is aligned to international categorisation in the supply chain and shall play a pivotal role. In the year 2019, 13,532 road deaths were associated with CV occupants.
The trucking industry is an unorganized sector wherein the illegal overloading of vehicles and over-the-limit driving hours pose a serious threat to road users. The first objective of the paper is to provide a root cause analysis for CV accidents. The analysis shall make use of suitable extrapolations using weighting factors from the Road Accident Sampling System of India (RASSI) database to provide an overview on the national scale, creating a first of its kind representative sample study for India. The second objective is to estimate the economic loss incurred by the owners and fleet operators due to these CV accidents using the Human Capital (HC) method.
The method and the resulting figures provide a more accurate view of accident situation and can be used by Original Equipment Manufacturers (OEM), fleet operators, and automotive research industry and transport authorities for technological innovations, infrastructural changes and law enforcement in an attempt at making Indian roads safer.
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Authors
Citation
Kumaresh, G., Saldanha, F., Lich, T., and Moennich, J., "Overview of Truck Accidents in India and Its Economic Loss Estimation," SAE Technical Paper 2021-26-0007, 2021, https://doi.org/10.4271/2021-26-0007.Data Sets - Support Documents
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References
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