Review of Accident Black Spot Identification and Mitigation Methods: Global and Indian Perspectives
Chaitali Vishwakarma1, Dr. Ashutosh Sharma2
Department of Architecture and Planning
Maulana Azad National Institute of Technology
Abstract
Road traffic injuries are a global public health and economic challenge, responsible for approximately 1.35 million deaths annually (World Health Organization [WHO], 2018). The burden is disproportionately higher in developing nations where limited road safety management systems, infrastructure deficiencies, and rapid motorization coexist. In India, the problem is particularly acute, accounting for nearly 11% of global road fatalities (Mondal, Pandey, Gupta, & Pani, 2023). Over 400,000 road accidents and more than 150,000 deaths were recorded in 2021, highlighting persistent systemic weaknesses in road infrastructure design and enforcement (Ministry of Road Transport and Highways [MoRTH], 2021, as cited in Mondal et al., 2023). Researchers across the world have developed a range of analytical, statistical, and simulation-based approaches to identify and mitigate accident black spots—locations characterized by an unusually high concentration of traffic crashes.
Globally, methodologies such as Bayesian Networks, multicriteria decision-making (MCDM), microsimulation, and geographic information systems (GIS)-based spatial analysis have advanced the scientific precision of accident hotspot detection (Gregoriades & Mouskos, 2013; Waizman, Shoval, & Benenson, 2015; Yakar, 2021; Srikanth, Srikanth, & Srikanth, 2022). In India, the Road Safety Audit (RSA) and the Analytic Hierarchy Process (AHP) are increasingly applied to rank risk factors and prioritize mitigation measures (Mondal et al., 2023). The integration of these diverse techniques provides a more holistic understanding of crash causation by combining infrastructural, behavioral, environmental, and economic parameters.
This paper presents a comparative review of major global methodologies for identifying accident-prone locations while emphasizing their applicability and adaptation to Indian contexts. It further discusses the evolution of accident risk modeling from static data analyses to dynamic, simulation-based, and GIS-integrated frameworks. The study concludes that for India and similar developing nations, a hybrid approach combining road safety audits, multicriteria evaluation, and spatial data analytics offers the most effective and economically viable strategy for black spot identification and mitigation.
Keywords:- Accident Black Spots, Road Safety, Accident Risk Index (ARI) , Fatalities, Road accidents, Black spot identification, Spatial analysis, urban transport safety
