How is AI helping the Indian Govt to make roads safer?

Artificial Intelligence (AI) has been helping us across various industries and sectors. One of the best applications of AI-powered solutions is called collision alert systems. It is all set to make driving safer for Indians. This unique, high-tech system of AI uses prediction to find the potential risks on the road which can lead to accidents.


The collision alert system makes the driver aware of the threats so that the driver can then implement the right strategy to avoid the accident. It is projected that with the use of AI, there will be a considerable reduction in the number of accidents on the road.

How is AI Making Roads in India Safer to Drive?

It is said that the recent project named ‘Intelligent Solutions for Road Safety using Technology and Engineering’ or iRASTE is aimed at finding potential accidents or the conditions leading to them when the driver is driving the vehicle. The features such as Advanced Driver Assistance System ADAS can send timely alerts to the driver to avert any oncoming threat.


Here is what you need to know about how AI is helping to make the roads in India safer:

  • iRASTE Project

        iRASTE project, a part of the I-Hub Foundation of the IIIT Hyderabad along with the Technology Innovation Hub or TIH, is excelling in Data Banks & Data Services. The project also involves the big names of CSIR-CRRI, Nagpur Municipal Corporation or NMC, Mahindra, and Intel.

  • Grey Spots

       This system is equipped to recognise the weak spots, also called grey spots. They are those areas of the roads which could turn into black spots if they are left unattended. Black spots are locations where there is a high possibility of fatal accidents. Deep data analysis is conducted along with the mobility analysis at the time of identifying and controlling a range of risks on the road network.

  • Preventive Measures

       The system also ensures smooth and constant monitoring of the roads. Using design and engineering features, some essential resolutions and fixes take care of the existing black spots on the road. They also suggest other preventive or maintenance measures that can make the road infrastructure better.

  • Modern Techniques

        The techniques such as machine learning, computer vision, e-challan and AI camera, computational sensing, and more are being used to their maximum potential to gain data-driven technical solutions. One of the major objectives is to ready a critical resource for the future. The same can be used by professionals, researchers, and industry experts in the fields such as mobility, healthcare, construction, etc.

  • Practical Solutions

       The best part about AI and its technology is to offer practical solutions. All the innovations and developments in this field are happening as per the Indian road conditions and the blueprints of the roads. When the iRASTE was rolled out in Nagpur, the aim was to implement the same solution in different cities.

  • India Driving Dataset

        Another solution that has come up recently is the India Driving Dataset or IDD. The dataset has more than 10,000 images. Gathered from 182 drive sequences on the roads, the data annotates 34 classes. It is made available by the front-facing camera and displayed in the public domain, where it can be used unrestrictedly under a public licence. With more than 5,000 registered users for this data worldwide, it is important to know and study it.

  • Open World Object Detection on Road Scenes or ORDER

       This is also a dataset, which is called Open World Object Detection on Road Scenes or ORDER. It has been launched along with IDD or India Driving Dataset to be utilised by the autonomous navigation systems in India. It aims to localise as well as classify the road objects.

  • Mobility Car Data Platform or MCDP

        A Mobility Car Data Platform or MCDP contains a range of sensors such as those used in e-challans and AI cameras. It helps to capture and evaluate important data. Researchers and new start-ups examine this data to check whether the automotive algorithms and navigation approaches are working or not.

  • LaneRoadNet or LRNet

       This is yet another framework that has to do with the lane and road parameters. It uses deep learning as well. It can take care of common Indian road issues and obstacles such as occluded lane markings, damaged dividers, chips and cracks, potholes, and more. Due to all this, the drivers are always at risk when they are driving the car. It calculates the road quality score using the modular scoring function. The score makes the authorities aware of the road quality and helps them prepare better road maintenance schedules.


Nitin Gadkari, the Minister for Road Transport and Highways, has released a plan to lower road accidents by as much as 50% by the end of 2024. This goal would be impossible without the use of AI and predictive analytics. Many more initiatives and plans in Motor Insurance are coming up in the near future that will improve transportation and road safety in different parts of the country.

FAQs on AI Traffic Camera Making Roads Safer

  • ✔️What is the iRASTE project?

    iRASTE project is run with the support of the Department of Science and Technology or DST under the NM-ICPS or National Mission on Interdisciplinary Cyber-Physical Systems and INAI or Applied AI Research Institute. This hub is continually making efforts to coordinate, improve, and execute basic as well as applied research in data technologies. They aim to spread and translate it across the entire country.

  • ✔️What are the AI solutions that are helping to make the roads safer?

    AI uses solutions like India Driving Dataset or IDD, Open World Object Detection on Road Scenes, Mobility Car Data Platform or MCDP, LaneRoadNet, or LRNet to make road driving safer.

  • ✔️What is LaneRoadNet or LRNet?

    LRNet observes lane and road parameters. It measures the road quality score and allows the authorities to improve road quality based on the score.

  • ✔️Why is MCDP important?

    A Mobility Car Data Platform contains sensors that can capture important data and determine the effectiveness of algorithms and navigation approaches.

  • ✔️How to reduce black spots and grey spots?

    AI, using deep data analysis and mobility analysis, can recognise grey spots and black spots, where there are high chances of fatal accidents.