In early November, a bus carrying 42 passengers in the Almora district of Uttarakhand, skidded before tumbling down a 60-metre (200-foot) gorge.
Barring six survivors, all the other passengers died in the crash.
Road mishaps, whether on India’s highways or city streets, happen with such regularity that they do not stir either the central or state governments into taking strong preventive measures.
But advances in artificial intelligence could offer new solutions to tackling India’s road toll.
India’s road trauma burden
While over the last two decades, there have been significant investments in the development of better road infrastructure in India, challenges persist.
These are in the form of poor maintenance of roads, inadequate safety measures, urban congestion, reckless driving, insufficient protection for vulnerable road users, weak enforcement of traffic laws and a lack of education and public awareness about safe driving practices.
As a consequence, India ranks as the top country in terms of the global road fatality rate, accounting for 11.7 per cent of all deaths.
In 2022, India reported over 460,000 crashes that resulted in 168,491 deaths and 443,366 injuries.
The previous year, the numbers stood at 412,432 crashes, 153,972 deaths and 384,448 injuries.
This marks an increase of 11.9 per cent for accidents, 9.4 per cent for deaths and 15.3 per cent for injuries.
While the state of Tamil Nadu in the south recorded the most number of road accidents between 2018 and 2022, the most deaths during the same period were in Uttar Pradesh where 22,595 and 21,227 people died in road crashes in 2022 and 2021.
Overspeeding is often attributed as the main cause of road deaths in Uttar Pradesh.
How can we reduce the number of accidents on India’s roads?
To get an overall sense of the reasons for road accidents, the resulting deaths and what could be done to reduce them, the Central Road Research Institute analysed data related to Nagpur, a city in Maharashtra state, between 2008 and 2021.
With a total population of 3.06 million people, Nagpur witnessed an annual average of 200 deaths and about 1,000 injuries, which is on the higher side for Maharashtra state.
This study highlighted the urgent need for marrying engineering solutions with technology to address urban traffic problems such as risk of collisions.
The AI-based technology – advanced driver assistance systems – involves mounting a camera on a vehicle’s windshield to scan the road ahead and uses complex algorithms to track potential risks.
In the event of a potential collision, the systems send an audio and a visual warning to the driver. A similar warning is sounded when collision situations involving pedestrians, cyclists or stray animals arise.
With India’s central government’s avowed goal to achieve a 50 per cent reduction in road deaths and injuries by 2030, one of the measures open to it is adopting such AI-based systems.
These systems use road-facing cameras to capture images or video to detect static and moving objects within a predefined distance and time range and identify the lane used by a vehicle in motion.
Such systems can then alert drivers in real-time if they are at imminent risk of crashing.
In addition to alerting drivers, the systems collect timestamped details of generated alerts which include the identity of the driver and their geographical coordinates (latitude and longitude), allowing real-time mapping of potential crash risk areas or grey spots.
Reduced road crashes
One of the pilot project’s key findings was that these driver Pilot projects such as show that AI-based tools have the potential to significantly reduce road crashes and fatalities, and hence improve road safety.
This initiative illustrated the impact of technology in high-risk areas, paving the way for broader adoption across varying types of vehicles.
More importantly, similar systems and technology should be used in India’s megacities and highways where road accidents go unchecked.
Article sourced from 360info.org
By S Velmurugan.
Velmurugan is the Chief Scientist and Head, Traffic Engineering and Safety Division, Central Road Research Institute, New Delhi.
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