Epileptic Cars? How Emergency Lights Confuse Automated Driving Systems

Emergency lights can disrupt automated driving systems, causing detection failures. Researchers developed “Caracetamol” to fix this issue, highlighting broader AI safety concerns.

New research suggests that camera-based automated driving systems, designed to make driving safer, could fail to recognize objects on the road when exposed to flashing emergency lights, posing significant risks, as first reported by WIRED.

Researchers from Ben-Gurion University of the Negev and Fujitsu Limited discovered a phenomenon called a “digital epileptic seizure” or “epilepticar.”

As reportd by WIRED, this issue causes systems to falter in identifying objects in sync with the flashes of emergency vehicle lights, particularly in darkness. This flaw could lead vehicles using such systems to misidentify or fail to detect cars or other obstacles, increasing the likelihood of accidents near emergency scenes.

The study was inspired by reports of Tesla vehicles with Autopilot colliding with stationary emergency vehicles between 2018 and 2021.

While the research does not specifically link the issue to Tesla’s system, the findings highlight potential vulnerabilities in camera-based object detection technology, a key component of many automated driving systems, notes WIRED.

The experiments used five commercial dashcams with automated driving features and ran their images through open-source object detectors.

The researchers note these systems may not reflect those used by automakers and acknowledge that many vehicles employ additional sensors like radar and lidar to enhance obstacle detection, as reported by WIRED.

The U.S. National Highway Traffic Safety Administration (NHTSA) has also acknowledged challenges with advanced driver assistance systems (ADAS) responding to emergency lights, says WIRED.

However, WIRED reports that the researchers emphasize they do not claim a direct connection between their findings and past Tesla crashes. To address the issue, the team developed a software solution called “Caracetamol,” which enhances object detectors’ ability to identify vehicles with flashing lights.

While experts like Earlence Fernandes from UC San Diego view the fix as promising, Bryan Reimer from MIT’s AgeLab warns of broader concerns.

He stresses the need for robust testing to address blind spots in AI-based driving systems, cautioning that some automakers may be advancing technology faster than they can validate it, as reported by WIRED.

The study underscores the complexities of ensuring safety in automated driving and calls for further research to mitigate such risks.