Now, Artificial Intelligence to drive innovation for road safety

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Technology, specifically Artificial Intelligence (AI), has the potential to make driving safer. Deep learning methods can be used to learn from the various driving conditions on Indian roads.

By Nivruti Rai

According to a McKinsey report, transport will be one of the most capital-intensive sectors in India by 2030; however, the dichotomy on Indian roads continues to amaze. On one hand, 9,800 km of highway roads were constructed in 2017-18, and the target for 2018-19 is 40 km a day; on the other, basic safety on Indian roads remains a serious cause for concern. In fact, our country is responsible for nearly 11% of the road fatalities across the globe. The reasons are manifold, and go beyond reckless driving and lack of adherence to traffic rules. What is interesting to note is that almost 75% of the accidents taking place on Indian roads are preventable if better driving standards are mandated.

Taking the tech route to safety
Technology, specifically Artificial Intelligence (AI), has the potential to make driving safer. Deep learning methods can be used to learn from the various driving conditions on Indian roads. The diverse driving conditions while challenging, offer opportunities to build automated systems capable of better reasoning and decisions to aid drivers on Indian roads. AI technologies are capable of recognising multiple objects, obstacles and hazards from a safe distance and alerting the driver. These technologies are built into applications called Advanced Driver Assistance Systems (ADAS) and work on camera and other sensor data to alert the drivers as they sense hazardous conditions on the road. Additional applications called Driver Monitoring Systems constantly monitor the driver for fatigue and drowsiness. Fleet telematics systems combine multiple vehicle parameters with road conditions to assess the driving behaviour of fleet drivers.
Technology firms in India are working on AI-based solutions to monitor driver behaviour to adjust the car accordingly, detect potholes, and much more. Lane departure warnings, frontal collision warning systems, intelligent speed assistance, parking assist, electronic stability control, emergency distress signals, blind spot monitoring, and night vision are among the features based on futuristic technologies that are currently being offered by manufacturers of premium segment vehicles such as Land Rover, in India.

Hand in hand with the government agencies, apps such as the MTPapp launched recently by the Mumbai Police aim to create more alert citizens. The aim is to empower Mumbaikars to get offenders and rule violators booked. Bengaluru, where potholes have become a nightmare for commuters and are responsible for as many as 50% of the fatalities on the road, is running a “Report a pothole, get it fixed immediately” initiative, where citizens can report potholes online, via WhatsApp or by calling the control room.

The Karnataka government is adopting new generation of technologies such as AI and ADAS to fulfil their vision of reducing road accidents by at least 30% in the next five years. The Delhi government has pledged to bring down accidents and fatalities by 30% in the next two years and a state-level road safety management information system will connect all hospitals, trauma care centres and ambulance services.
As a signatory to the Brasilia Declaration on Road Safety (commitment to reduce road accidents by 50% by 2020), the Indian government has mandated that by end-2018 all cars on Indian roads must compulsorily sport airbags, an Anti-braking System (ABS), seat belt reminders and speed alert systems.
The mandate, however, cannot rest here. All stakeholders in the ecosystem, from the manufacturers to the individual drivers, must shoulder the onus of better safer driving. With every step that we take towards the future, the scope for technology to transform our transportation sector and enhance road safety, broadens exponentially.

The writer is country head, Intel India, vice president, Data Centre Group

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