Collision Avoidance System In Hairpin Curve In Hilly Region

Abstract: India has the highest rate of traffic accidents in the world. The majority of road accidents are caused at high speeds or when the driver is unaware of other vehicles coming opposite to it, especially in deep curves (hairpin curve) which are situated in the hilly regions. Due to a lack of communication and zero visibility over the hairpin curves, vehicles traveling around hairpin bends are extremely vulnerable to accidents. It is also very difficult to see whether the vehicle on the other side of the hairpin curve is a light weight vehicle like a car or two-wheeler or a heavy weight vehicle like a truck or a trailer. As the different size of vehicles will take different amount of space to take a turn at the hairpin curves which are generally much narrower. As a result, vehicles must take extreme caution when driving through these kinds of curves. Moreover, the roads in the hill stations are having steep slopes at these curves which makes the turning at these curves very critical. The existing systems available generally has a mirror at the curves, which will display the vehicle coming from the other side. But due to fog or mist in the hilly region many times these mirrors are not visible from a significant distance, so that the drivers are not able to control their speed on time, leading to accidents. These issues also cause traffic congestion and delay in travel. The proposed system is used to detect the vehicles on one side of the hairpin curve and assist the vehicle coming opposite to it. The aim of the proposed system is to classify different vehicles passing through one direction of the hairpin road and notify the vehicles that are coming in the opposite direction of the hairpin through a display board. This display board is a LED display containing the information about vehicle category, whether the vehicle is light weight or heavy weight and also the time taken by that vehicle to pass the curve and number of vehicles in the curve. The system will also have sensors placed at significant distance before the hairpin curve and on the roads on both the sides of the curve, which can detect the speed and weight of the incoming vehicle. Machine learning algorithms will be used to detect the category of the vehicle based on its weight, calculate the time required by it to cross the curve and also predict the speed it should maintain while crossing the curve. The sensors on the other side of the road will signal the vehicles on that side to stop at a significant distance from the curve and wait till the vehicle on the other side cross the curve and pass on. The display used will have LED fog lights, which will be visible to the vehicles during fog and mist in the hilly region.

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