Abstract
Black spots are short stretches of areas on road that have a recurring history of traffic fatalities/accidents. Hence, it becomes even more critical to track the development of such black spots on roads when the lives of people are at stake. There is not any suitable infrastructure for governing bodies or ministries to monitor such black spots and alert on-road commuters in India. This paper proposes an integrated software platform that enables administrators to monitor the development of these black spots and alert on-road commuters if they are approaching a black spot. It uses geofencing and crowdsourcing in conjunction. Black spots are populated onto the proposed platform by employing the official dataset provided by the Ministry of Road Transport and Highways. The data gathered through crowdsourcing will further develop temporary black spots based on user input frequency for a particular location. The proposed platform is not just limited to black spots but also has an alert mechanism for blind spots (like sharp turnings, U-turns, T-intersections, etc.). Pedestrians’ safety is also taken into account by generating timely alerts for them if they are near a black spot. The proposed platform has been successfully tested on the official dataset provided by the Ministry of Road Transport and Highways (MoRTH) and has shown satisfactory results.
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Notes
- 1.
Road To Hell: India’s Most Dangerous National Highways: “https://sites.ndtv.com/roadsafety/road-hell-indias-dangerous-national-highways-1915/”.
- 2.
Ministry of Road Transport and Highways, Transport Research Wing (2019, September 26). Road accidents in India—2018. Government of India. https://morth.nic.in/sites/default/files/Road_Accidednt.pdf.
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Jaiswal, Y., Parikh, S., Sanjay, H.A., Manoj Kumar, M.V. (2022). Real-Time Crowdsourcing and Geofencing-Based Black Spot Detection, Monitoring and Alert Platform. In: Pandian, A.P., Palanisamy, R., Narayanan, M., Senjyu, T. (eds) Proceedings of Third International Conference on Intelligent Computing, Information and Control Systems. Advances in Intelligent Systems and Computing, vol 1415. Springer, Singapore. https://doi.org/10.1007/978-981-16-7330-6_10
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