June 6, 2018 (auto.economictimes.indiatimes.com). According to a report from auto.economictimes.indiatimes.com, congestion and accidents could be reduced by artificial intelligence (“AI”).*

With its dense population, India is notorious for its traffic congestion, the cost of which is skyrocketing in the country. Accordingly, per the Government of India and a study conducted by IIT Madras, the cost of congestion in New Delhi, one of India’s most populated cities, was around $8,500 with buses contributing to most of the congestion, following by cars and two-wheeled vehicles. This cost has increased to nearly $9,500 in 2018 with all vehicles mentioned herein contributing to the congestion in the same order. Projections are that by 2030, the cost of congestion will be around $14,658.

The rate of accidents in India is also staggering. For instance, according to the Ministry of Road Transport and Highways, data collected by this department demonstrate that the total number of accidents in the country back in 2015 was around $500,000, and resulting in nearly 150,000 deaths.

In light of the foregoing, it has been suggested that AI could be the answer that addresses the rate of accidents and traffic flow issues, as follows:

  • The advanced cruise control can follow highway traffic and curves in the road as well as start and stop during heavy traffic.
  • It would impact greenfield road construction and design. What this means is that the size of each lane, reduced traffic congestion and a reduction in costs to upgrade highway infrastructure would provide benefits to those who have cars with AI.
  • By virtue of AI cars’ intelligent management system, which include sensors, cameras, automatic plate number recognition cameras, speed detection cameras, etc., “real time dynamic decisions on traffic flows such as lane monitoring, access to exits, toll pricing, allocating right of way to public transport vehicles, enforcing traffic regulations through smart ticketing can be made.”
  • AI could also assist in the designing of urban traffic control systems that can optimize the timing of signals at intersections, etc. while at the same time, facilitating services such as “automatic vehicle detection for extension of red/green phase or providing intermittent priority.”

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