The economic growth of a country is directly influenced by the efficient transportation ecosystem. Along with rapid technological changes, the world is moving towards faster road transportation. 2-wheelers (also known as motorcycle or scooter) are evolving as one of the most preferred modes of road transportation in both developing and developed countries. India is one of the biggest markets for the 2-wheelers (44.5% of on-road vehicles are 2-wheelers), due to its affordability, high fuel efficiency and finally easy mobility even in heavy traffic conditions.
As 2-wheelers are becoming a preferred mode of transportation, motorists stand at the precipice of a greater risk of accidents. These accidents are fatal in nature as the design and build of a 2-wheeler may not be able to withstand severe crashes.
According to recent studies, deaths or fatality caused by 2-wheeler crashes are 30X more than that of a car. Out of all 2-wheeler accidents, almost 50% of them are caused due to reckless, careless, or distracted driving, such as over speeding, violation of traffic rules, failing to pay proper attention to the road/weather condition, not wearing adequate safety gears by riders, and/or inexperienced riding.
Thus, all automotive industry leaders are focusing on software enabled systems in 2-wheelers that offer various mechanisms and connectivity to enhance safety not only for the rider, but also for pedestrians.
Software enabled safety system for 2-wheeler includes Advanced Rider Assistance Systems (ARAS) which is based on two important technologies available as of today – Computer Vision by Machine Learning and Vehicle to Everything (V2X/CV2X) communication.
The aim of ARAS is to enhance 2-wheeler safety by using advanced algorithms that combine computer vision by machine learning and V2X/CV2X wireless communication with nearby vehicles or infrastructure (like traffic lights) with real-time information, and thereby detect safety risks and imminent crash/danger to the rider. ARAS analyzes real-time camera feeds from the front and rear cameras along with inputs from different other sensors (Radar, Gyro, Accelerometer, Tire pressure monitor, GPS/GNSS etc.) mounted on the 2-wheeler to create a computer vision.
By Mrinal Sarkar
Senior Architect - System Software
