A unique AI method that uses AI’s ability to predict the future to find risks on the road and a collision alert system to warn drivers in time. The backers are talking with the government of Telangana about putting the technology in a fleet of highway-traveling buses.
- A new AI technique that employs predictive power to identify road risks and a collision alert system to inform drivers improves road safety.
- The project’s supporters are in talks with the Telangana government to implement the technology in a fleet of highway buses.
- The research will also discover grey regions by analyzing data and monitoring dynamic road risks.
- The dataset comprises 10,000 pictures labeled with 34 classifications from 182 driving sequences on Indian highways taken from a front-facing camera on a car driven around Hyderabad and Bengaluru and their suburbs.
- The public domain dataset is becoming the de facto standard for road analysis.
Solutions based on artificial intelligence (AI) could soon make roads safer to drive on. A unique AI approach that uses AI’s ability to predict and find risks on the road and a collision alert system to send drivers timely warnings can improve road safety. Intelligent Solutions for Road Safety through Technology and Engineering (iRASTE) is the project’s name. Its backers are talking with the Telangana government about putting the technology in a fleet of highway buses.
The project will also find grey spots by using data analysis and mobility analysis to keep a close eye on the road network’s dynamic risks. Grey spots are places on roads that, if not fixed, could turn into blackspots (locations with fatal accidents). The system also keeps an eye on the roads and comes up with engineering fixes to fix trouble spots for preventative maintenance and better road infrastructure.
The iRASTE project is run by the I-Hub Foundation, IIIT Hyderabad, a Technology Innovation Hub (TIH) set up in the technology vertical- Data Banks & Data Services. It is supported by the Department of Science and Technology (DST) under its National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) along with INAI (Applied AI Research Institute). The dataset is the first of its kind. It comprises 10,000 images from 182 drive sequences on Indian roads. The images came from a front-facing camera on a car driven around Hyderabad, Bengaluru, and their surrounding areas. The dataset is in the public domain, which means anyone can use it. It is also becoming the standard dataset for all road analyses.