EaseMyTrip co-founder stuck in Bengaluru traffic for 2 hours, pledges ₹1 crore to map chokepoints using AI
Bengaluru's notorious traffic has long been a growing concern in India's tech capital. After experiencing it firsthand, Pitti has pledged ₹ 1 crore to identify choke points and help address the issue.
Pitti announced on X (formerly Twitter) that he has a proposal to find Bangalore chokepoints using Google Maps, artificial Intelligence and Machine learning.
'I was stuck at one choke-point at ORR, where I spent 100 mins struggling to understand why there is no traffic-light or cop here,' Pitti said in his post.
Pitti's initiative aims to move beyond mere complaints and towards tangible solutions as he firmly stated, 'I don't want one more Bengaluru Traffic Memes or Rant. I WANT TO FIX IT.'
Pitti has put forward a proposal on X, which talks about potential solutions to identify and fix the traffic bottlenecks in the city. Google Maps data and AI: Utilising Google Maps' 'Road Management Insight', city-level data in Big Query format, along with satellite imagery.
Chokepoint identification: The goal is to list down all the chokepoints and their exact timings in a month.
This retrieved data will then be shared with the traffic department, who in turn will focus their efforts on those areas specifically.
To bring the vision to life, Pitti is committing ₹ 1 crore, which will fund the following: Senior ML/AI engineers: Hiring 1-2 experienced machine learning and artificial intelligence professionals to join the cause.
Technological Infrastructure: Covering the budget for using Google Maps API calls, Satellite Imagery access and powerful GPU infrastructure required for data processing and model training.
Pitti emphasises that the success of this project depends on collaboration from local authorities. He is also actively seeking support from others on X. Government Partnership: The project will commence only when the Bengaluru Traffic Police (BTP) or Bruhat Bengaluru Mahanagara Palike (BBMP) provide access to raw data feeds or APIs and designates a dedicated team to act on the generated insights.
ML/AI community to act: he urged professionals to comment 'IN' if they are willing to contribute their expertise in a part-time setup, and end this menace.
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