IIT Mandi develops system to reduce accident risk on sharp curves

The developers have acquired a patent for the innovation. The team includes students from mechanical engineering, electrical engineering and civil engineering and a faculty coordinator.

The Indian Institute of Technology (IIT) Mandi has developed a smart road monitoring system that will help prevent accidents caused at sharp turns, causing fatalities and injuries and enhanced traffic management. 

The monitoring system can be used for speed detection, vehicle counting, enhanced traffic control and road usage. Kala Venkata Uday, assistant professor, School of Engineering, IIT Mandi, and his team of BTech students from the 2016-20 batch have developed the system by employing the Micro-Electro-Mechanical Systems (MEMS) and Internet of Things (IoT) technologies. 

Detection, signalling units to alert drivers 

The developed system comprises two layers of detection units on each side of the turn and two signalling units to alert the drivers. When a vehicle passes through the two consecutive layers of detection units, the sensing system detects the speed, direction and type of vehicle (two/four/multiple wheels). The detected direction confirms if the vehicle is advancing towards the turn, and a corresponding signal (light/sound/barrier) is displayed on the other side to alert the drivers of an oncoming vehicle. If the vehicle moves away from the curve, no signal is displayed. The signals are decided based on the speed, direction, gradient of slope and type of vehicle. 

Kala Venkata Uday said, “This technique will not only reduce the accident risk on sharp curves, but will also help in reducing human intervention on traffic counts, management and helps in decision making.”  

Apart from alarming the curves, the developed system can also be used for vehicle counting and its advanced versions will also be able to detect the load of the vehicle. This data can be used for enhanced traffic management, road use, traffic flow on single line tunnels and restricted areas by employing artificial intelligence and machine learning tools. The prediction on traffic jams, increased flows and diversion alerts can also be generated after sufficient data collection.  

Being mechanical in nature, the developed system can work in any weather, including rain, snow, fog or other poor visibility conditions and the data can be encrypted and shared to only appropriate stakeholders. 

“Though existing technologies are effective, their effectiveness drastically is affected during adverse weather conditions, that is where our system is robust,” added Uday. 

At a prototype development stage, the system costs less than Rs 20,000 excluding the alerting units per curve. However, the innovators are currently working on the commercial aspects and trying to bring down the overall product cost, by lowering operating and maintenance costs, and utilising alternative energy sources to make the system self-sustainable using solar energy. 

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