According to the Ministry of Road Transport and Highways, overspeeding is responsible for about 70% of road deaths in India.
Researchers at various Indian Institutes of Technology (IITs) are working to develop a first-of-its-kind “smart speed warning system” for vehicles that will alert drivers based on road infrastructure and geographical location to avoid extra-avoidance. Accidents related to speeding.
According to figures available with the Ministry of Road Transport and Highways, about 70 per cent of road accidents in India are due to speeding.
To reduce such casualties, the government mandated that all new cars sold from July 1, 2019, include a speed governor device that will produce a non-stop warning beep at speeds of up to 80 kmph and a constant beep above 120 kmph for drivers. To further reduce the loss of life, fines for speeding have been increased tenfold under the new Motor Vehicles Act of 2019.
However, researchers at IIT Guwahati and Bombay believe that the current speed control device is a “one size fits all” solution and does not have much intelligence and the same system may not work effectively when driving in hilly, flat or desert areas.
“Our research shows that the safe speed of a vehicle can change significantly with changes in road geometry, such as sharp or blind curves or hairpin curves. Therefore, a smart speed warning system, including dynamic and adaptive speed thresholds, needs to be developed to avoid additional speed-related accidents.” Upcoming road infrastructure, ”Akhilesh Kumar Maurya, Professor of Civil Engineering, IIT Guwahati, told PTI.
“Traditional warning systems are based on specific speed thresholds, however, the concept of a smart warning system is based on impending road infrastructure and vehicle positioning. The system will warn drivers in advance, which will allow drivers to take corrective action and avoid accidents, ”he added.
Researchers, who are in the process of filing a patent for the system, claim that such a system is not found anywhere in the world.
According to the team, the algorithm for the smart speed warning system has been developed based on field data collected from a 45-kilometer stretch of the four-lane highway (NH-40) between Jorabat in Assam and Nangpoh in Meghalaya comprising 285 horizontal curves. The study section covers a wide range of road geometries (curve radius 20-800 m, curve length 30-244 m and gradient varies from seven percent to nine percent.
“We are in the process of analyzing data on NH-61, a two-lane undivided highway between Mumbai and Malshej Ghat in Maharashtra. We have now completed our pilot study between the four lane divided highway, NH-160 Thane and Nasik (Maharashtra). And now very soon. We are planning to collect detailed information, “said Maurya.
The team plans to conduct similar pilot studies on different highways across the country to get an idea of the different geographical locations and will eventually present the model to the National Highway Authority of India (NHAI).
During a pilot study to develop speed prediction models, the researchers came up with car speed models and HCV and LCV speed models.
According to Abhijit Majir, an associate professor in the Department of Civil Engineering at IIT Bombay, the researchers used the operating speed of the vehicle as a surrogate measure to assess the safety of horizontal curves.
“Now, the 85th percentile speed of a vehicle in free-flow mode is widely regarded as operating speed. However, the geometric features of highways have been designed based on design speed. 95th to 98th percentile speed, “he described in a research paper published in the Journal of the American Society of Civil Engineers (ASCE).
“Drivers in developing countries are not disciplined and often drive based solely on their perceptions of road geometry. Therefore, the 98th percentile speed can be effective in assessing highway safety in a country. Now, available vehicle speed prediction models vary greatly. Differences in behavior and highway geometry may be the cause of this diversity, “he added.
Another research scholar in the team emphasized that studies show that the decision-making process and driver performance depend on situational awareness.
“Drivers want to drive at a safe speed based on the geometric features of the road. These features are characterized by gradient, horizontal curvature, length of curve and tangent section, extreme height, etc. Creates and thus minimizes driver errors.
“To date, most research on geometric pattern consistency has been conducted in isolated curves of flat terrain for traffic with strong lane discipline. The effect of gradient is not significant in these terrains. Has done.