Self-driving cars may ease traffic woes: Study

A fleet of driverless cars can improve overall traffic flow by at least 35 per cent by working together, a study suggests. The researchers, from the University of Cambridge in the UK, programmed a small fleet of miniature robotic cars to drive on a multi-lane track and observed how the traffic flow changed when one of the cars stopped.

When the cars were not driving cooperatively, any cars behind the stopped car had to stop or slow down and wait for a gap in the traffic, as would typically happen on a real road.

A queue quickly formed behind the stopped car and overall traffic flow was slowed.

However, when the cars were communicating with each other and driving cooperatively, as soon as one car stopped in the inner lane, it sent a signal to all the other cars.

“Autonomous cars could fix a lot of different problems associated with driving in cities, but there needs to be a way for them to work together,” said Michael He, an undergraduate student at Cambridge, who designed the algorithms for the experiment.

Cars in the outer lane that were in immediate proximity of the stopped car slowed down slightly so that cars in the inner lane were able to quickly pass the stopped car without having to stop or slow down significantly.

Additionally, when a human-controlled driver was put on the ‘road’ with the autonomous cars and moved around the track in an aggressive manner, the other cars were able to give way to avoid the aggressive driver, improving safety.

“If different automotive manufacturers are all developing their own autonomous cars with their own software, those cars all need to communicate with each other effectively,” said Nicholas Hyldmar, who designed much of the hardware for the experiment.

Starting with inexpensive scale models of commercially-available vehicles with realistic steering systems, the Cambridge researchers adapted the cars with motion capture sensors and a Raspberry Pi, so that the cars could communicate via wifi.

They then adapted a lane-changing algorithm for autonomous cars to work with a fleet of cars. It allows for cars to be packed more closely when changing lanes and adds a safety constraint to prevent crashes when speeds are low.

A second algorithm allowed the cars to detect a projected car in front of it and make space.

They then tested the fleet in ‘egocentric’ and ‘cooperative’ driving modes, using both normal and aggressive driving behaviours, and observed how the fleet reacted to a stopped car.

In the normal mode, cooperative driving improved traffic flow by 35 per cent over egocentric driving, while for aggressive driving, the improvement was 45 per cent.

The researchers then tested how the fleet reacted to a single car controlled by a human via a joystick.

“Our design allows for a wide range of practical, low-cost experiments to be carried out on autonomous cars,” said Prorok.

“For autonomous cars to be safely used on real roads, we need to know how they will interact with each other to improve safety and traffic flow," he said.