May 24, 2024


Choose Automotive

“Collective perception” tech lets connected cars see hidden hazards

While there are now systems that allow cars to see pedestrians or vehicles which their drivers may not notice, such setups typically still can’t detect hazards that aren’t in direct line of sight. A new technology, however, uses other vehicles and roadside cameras to do that job.

The experimental “collective perception” (CP) system is being developed via a collaboration between the University of Sydney and Australian tech company Cohda Wireless, funded by Australia’s iMOVE Cooperative Research Centre. It incorporates both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications.

As a car utilizing the technology approaches an intersection, it receives data transmitted from vehicles ahead of it (which are travelling in all directions), and from camera/LiDAR-equipped roadside ITS (intelligent transportation systems) stations.

If one of those vehicles or stations “sees” a vehicle or pedestrian which is blocked from the approaching car’s view – and that is potentially on a collision course with it – the approaching car’s driver is alerted via an X-ray-style display that shows the location of the hidden danger. If the driver can’t react in time, their vehicle’s collision avoidance system will automatically apply the brakes.

In controlled field tests conducted so far, the system was successfully able detect intersecting pedestrians that were hidden by a building, several seconds before an approaching car’s onboard sensors detected them. And while intersections are provided as an example of where the CP technology would be most useful, it could be utilized along the entire length of city streets, alerting drivers to things like jaywalkers stepping out from between parked cars.

“This is a game changer for both human-operated and autonomous vehicles which we hope will substantially improve the efficiency and safety of road transportation,” says Prof. Eduardo Nebot, from U Sydney’s Australian Centre for Field Robotics.

Source: Story Inception via EurekAlert