Valeo and Teledyne FLIR, part of Teledyne Technologies Incorporated, have started a strategic collaboration to bring thermal imaging technology to the automotive industry to enhance the safety of road users. Together, the team already secured a major contract in late 2023 from a leading global automotive OEM to deliver their new thermal imaging cameras as part of a new generation of advanced driver-assist systems (ADAS) driver-aide technology to improve vehicle and road safety.

Valeo and Teledyne FLIR will deliver the first Automotive Safety Integrity Level (ASIL) B thermal imaging technology for night vision ADAS. This system will complement Valeo’s large range of sensors and rely on Valeo’s ADAS software stack to support functions such as automatic emergency braking (AEB) at night for passenger and commercial vehicles as well as for autonomous cars.

The collaboration brings together Valeo, a leader in automotive camera technologies, with Teledyne FLIR, a leader in thermal imaging technology, to create the next generation of multispectral sensor fusion systems for automotive safety.

Valeo will leverage its extensive expertise in automotive vision systems to integrate Teledyne FLIR thermal vision technology and supply the OEM with a complete solution for night vision, including perception software based on Valeo’s AI and Graphical Visualization stack.

In the United States, preliminary data from the Governor Highway Safety Association found that 2022 marked the deadliest year on record for pedestrians since the organization began tracking such data in 1981. The record number of pedestrian deaths, with three-quarters occurring at night, highlights the need to do more to protect vulnerable road users, which also includes bicyclists and large mammals.

In response, regulators in the United States are introducing proposed rulemaking for stricter testing standards for automatic emergency braking (AEB) systems, including requiring testing at night. However, existing AEB systems do not include thermal imaging, which the partners say is crucial for detecting and classifying living objects in low-light conditions and inclement weather.