A recent study found that self-driving cars that are communicating with each other, eliminates the need to slow down all the other vehicles and reduce the impact of a road obstruction.
The researchers at the University of Cambridge in the UK, have programmed 16 miniature robotic cars to drive around a two-lane track and observed how the traffic flow changed when one of the cars stopped.
The team observed that when the cars were not driving co-operatively, it becomes necessary for any vehicle behind the stopped car to stop or slow down and wait for a gap in the traffic. It typically happens on the real roads now. A queue formed quickly behind the stopped car and the total traffic flow became slow.
But, when the cars started driving co-operatively, as one car stopped in the inner lane, it sent a signal to all the other vehicles. And the cars in the outer lane that was near to the stopped car slowed down slightly so that vehicles in the inner lane were able to quickly pass the stopped car without having to stop or slow down significantly. The test also showed that how driverless cars could help improve overall road safety.
“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 co-author Michael He, an undergraduate student at St John’s College, who designed the algorithms for the experiment.
Then the researcher team put a human-controlled driver on the road with the self-driving cars and moved around the track in an aggressive manner. They found that the other cars were able to give way to avoid the aggressive driver, reducing the chance of a collision.
“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 co-author Nicholas Hyldmar, an undergraduate student at Downing College, who designed much of the hardware for the experiment.
The results were presented at the International Conference on Robotics and Automation (ICRA) in Montreal, Canada. Hopefully, it will be useful for studying how autonomous cars can communicate with each other, and with cars controlled by human drivers, on real roads in the future.
For the study, the Cambridge researchers adapted the cars with motion capture sensors and a Raspberry Pi, so that the cars could communicate via Wi-Fi. They then adopted a lane-changing algorithm for autonomous cars to work with a fleet of cars.
The original algorithm decides when a car should change lanes, based on whether it is safe to do so and whether changing lanes would help the car move through traffic more quickly. While the adapted algorithm 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 behaviors, and observed how the fleet reacted to a stopped car. In the normal mode, cooperative driving improved traffic flow by 35% over egocentric driving, while for aggressive driving, the improvement was 45%. 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.”
The researchers plan to use the mini fleet to test multi-car systems in more complex scenarios including roads with more lanes, intersections and a wider range of vehicle types.