India, Nov. 5 -- IIT Guwahati researchers tracked more than 36,000 vehicles using drones on an eight-lane highway near Delhi.

The study found that gaps between vehicles shrink as traffic increases but widen again near gridlock.

Six mathematical and two machine learning models were tested, with the conventional Underwood model performing best.

Researchers say India-specific traffic data could improve road design, congestion management and traffic forecasting.

Traffic on Indian roads does not always follow the patterns assumed by conventional traffic models. Two-wheelers, three-wheelers, cars, buses and heavy vehicles share road space, often moving at different speeds and changing positions according to available gaps. This diversity ma...