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India’s Surface Transportation: Future is Intelligent Systems


· India,Transportation,Transportation Tech,Asia,Intelligent Transit

India’s Surface Transportation: Future is Intelligent Systems

Current State:

The automotive sector has made a major contribution to GDP according to the Government of India data. Currently, the automotive sector’s share is approximately 6.7%, which is expected to grow to about 12% of GDP in 2026. It would be one of the largest employment-producing sectors. As per Automotive Mission Plan 2006-16, 25 million jobs have been created in the automotive sector over the last decade, and 10 million jobs are expected to be created by 2022. [1]

The use of motor vehicles has increased which can be witnessed by the density per 1000 population. [2]

Despite such high usage and major contribution to Indian economy, the transportation sector is grappling with problems like weak infrastructure, high traffic congestion, and high traffic deaths. According to a PIB release by the Ministry of Road Transport and Highways (MORTH) in March 2017, the total number of road accidents in the country during 2015 was 501,423, which resulted in 146,133 fatalities. The National Highways (NHs) accounted for about 29.1% of total road accidents and 35.0% of total fatalities. Although the existing NHs comprise approximately 1.9% of the total road network, they carry about 40% of total road traffic. [3]

To overcome these problems and attain maximum and efficient output from the existing transportation setup, the Government of India, through its planning body, NITI Aayog (National Institution for Transforming India), is planning to utilize automation and Artificial Intelligence.

Currently, autonomous vehicles are not economically viable in India, as driver costs per kilometer is too low. However, investing in the field of autonomous vehicle technologies and exporting such vehicles represents a significant economic opportunity for India. Since the same technologies can play a large role in reducing fatalities and decreasing congestion, it would be wise for Indian manufactures to invest in research and development of the broader suite of technologies that are essential for assistive AI.

Major Applications of AI in Indian Transportation:

  • Automated trucking: Can be used in freight and goods movement. AI can help increase hauling efficiency and safety, wherein trucks form platoons. A driver can rest while the platoon moves forward. This method can increase road-space utilization.
  • Intelligent transportation aiding devices: Can be used for traffic management with systems like CCTV cameras, speed detection cameras, automatic number plate recognition cameras, intelligent pedestrian crossings, etc.
  • Corporate decision making: Can be used to accurately forecast the road-freight volume of using AI methods, which simplifies the transportation planning at company level.
  • Travel route/flow optimization: Can be used to access traffic data at the network level, which can be utilized to make informed predictions of traffic congestion and improve route selection by optimizing total journey time, including access time, waiting time, and travel time. AI can suggest alternative flow strategies in order to relieve congestion, alleviating cities of this major issue.
  • Railways: Loco Pilots can obtain the real time operational data and analyze it for proper scheduling and to avoid accidents.
  • Public Safety in Transportation: Safety of the travelers can be ensured by tracking crime in real time. Also, this data can help law enforcement authorities in patrolling and planning their operations. Accident heat maps could be generated using accident data and driver behavior at specific locations on the road network related to topology, road geometric design, speed limit, etc., and suitable measures could be pre-emptively taken to prevent possible accidents.
  • Intelligent parking systems: The availability of parking is a major issue for Indian cities. AI can help optimize parking, likely by minimizing vehicle downtime and maximizing driving time. Parking guidance systems can help drivers find vacant parking spaces while they are using the road network and have started to approach their destination.

Road Ahead:

Despite being the sixth largest economy in the world, India is still facing the age-old problem of not-so-robust infrastructure. AI and algorithms can help the sector by reducing fuel usage and time spent on the field through optimization. According to an estimate, the investment in the Indian Transportation market should touch $10.30 billion by 2030. One of the more prevalent problems is also the talent crunch [4]. The talent pool of India needs to be analogous to the industry as it becomes more data-driven and automated. More people skilled in AI who have the knowledge of Intelligent systems will be needed by India.

Written by Aditya Zalte & Edited by Alexander Fleiss

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