The Indian Institute of Science (IISC) Bangalore researchers have come up with a solution to solve traffic woes in the city by using AI. This has happened with respect to the many challenges faced by the people in the city due to traffic congestion.
Tajasvi Surya, recently had a meeting with two professors of IISC Bangalore- Professor Ashish Verma and Professor Abdul Pinjari from the Civil Engineering dept in IISC Bangalore. The motive was to brainstorm alternative ways of technology to solve the traffic problem in the city.
The team of IISC has come out with various Traffic Flow Models and analysis of Adaptive Traffic Signals based on Travel Demand estimates by using Artificial Intelligence and Machine Learning to predict congestion on road. Some studies related to elevated corridor project and sustainable transport measures have also been analysed.
The expansion of road spaces according to them will lead to more vehicles on the road. The road infrastructure may not improve the situation but can continue to degrade it. Proper management of public transport and private vehicles both should fall in place for better traffic management in Bangalore.
Personal and public transport must complement each other not compete with each other. As reported, BMTC is planning to have a bus lane on a pilot basis from the silk road to Hebbal.
The citizens are also giving their views and suggestions on the same and addressing the problems and sending them to MP Deepika. Suggestions like 'four days a week work culture' have come to the forefront. Also, people are suggesting to execute and encourage the concept of 'green days' wherein on that day citizens can only use public transport. Carpooling should be promoted and footpaths should be made available to pedestrians.
The Bengaluru’s traffic is in a bad state and according to surveys- from the past many years, the traffic in the city has increased drastically. Therefore, it is high time to look into the matter and find the solution so that people do not end up spending half of their lives stuck in traffic.