Self-driving cars bring the promise to keep traffic flowing and to help us optimise our journeys. The argument is that smart robot cars could communicate with each other, better sense obstacles and generally create a more organised flow of traffic.

But much of this technology is being developed for the orderly streets of the West. Uber’s former CEO Travis Kalanick has said India would be the last place to get driverless cars after experiencing Delhi traffic.

That hasn’t deterred design firm Tata Elxsi, which is building a self-driving system that could be retrofitted to any car, and have started testing prototypes on a test track near their Bangalore headquarters.

Road testing is far away though and they’re under no illusions about the challenges. “Driving behaviour is a lot more erratic here,” says Nitin Pai, head of marketing and strategy. “Rules are not rules, they're more guidelines.”

And that’s exactly why thinking about Indian roads in particular could help us come up with the best ideas.

Self-driving cars rely heavily on machine learning – that’s when AI uses mountains of data to train itself to do things like recognise vehicles and predict their trajectories over time. So far, such cars have been tested across the globe in places like San Francisco and Pittsburgh in the US, and in smaller cities in countries like Japan and China.

But most research has been done in the West, where driver behaviour could be argued to be more predictable and roads are reliable with clear signs.

"These are the foundations on which you lay the system of a driverless car,” says Pai.

The group has been training their system on third party data collected by researchers at the Karlsruhe Institute of Technology in Germany. This was done on German roads using a car equipped with high resolution cameras, GPS and a Lidar sensor – effectively radar using laser light instead of sound for very sensitive distance measurements.