ADAS Elevated: Thermal and Radar Technologies Fuse for Greater Detection Capability
Over the past five years, there has been a dramatic increase in the implementation of Advanced Driver Assistance Systems (ADAS). According to the U.S. Department of Transportation, more than 90% of the passenger vehicle fleet produced for the North America market now feature ADAS technologies, including forward collision warning, lane departure warning, automatic emergency braking, and more.
These systems are designed to enhance safety and crash avoidance by providing early warnings that can prompt faster driver reactions or, in some cases, automatic system interventions. While the potential for increased safety is significant, conventional ADAS sensors and camera systems often face limitations in adverse weather and low-visibility conditions such as nighttime, fog, rain, and snow.
Colored boxes represent classifications (vehicle, pedestrian, 2-wheeler) from thermal imaging, while numbers indicate distance measurements from radar, combining the strengths of both systems.
Addressing the challenge of detecting and classifying potential threats in these demanding environments is crucial for the next generation of ADAS. The key to overcoming these limitations may lie in the fusion of thermal imaging and Doppler-type imaging radar. This next-generation technology could augment or even replace conventional detection systems, as well as complex LiDAR-based systems.
This area is a core strength for Magna, a leader in the design, development, and delivery of full vehicle-level ADAS systems, including thermal and radar technologies. Magna’s Thermal Sensing system, for example, uses real-time thermal imaging to extend the driver’s perception up to four times beyond the headlight range, detecting pedestrians, cyclists, and animals up to 200 meters (656 feet) ahead of the vehicle.
By combining the heat-signature-detecting advantages of thermal technology with imaging radar’s ability to determine an object’s location, speed, and direction, this advanced system can provide quicker, more reliable environmental analysis under adverse conditions. This means drivers—or automated intervention systems—can have more time to react and avoid crashes, even in the most challenging weather or driving scenarios.
In addition to multiple sensing modalities, AI-driven machine learning is incorporated to process sensor data earlier through early fusion, and can more accurately track pedestrians, animals, and other objects. This enhances system performance and reliability while reducing false positives.
The result is a more accurate, robust ADAS that can boost driver confidence and reduce anxiety in tough driving conditions. The fusion of thermal and radar technologies offers a significant leap in sophistication and capability, far beyond incremental improvements to current systems.
Moreover, the cost and scalability of imaging radar and thermal sensors are relatively competitive, especially compared to the complexity of LiDAR-based systems, which are primarily seen in premium-segment applications today. This makes the advanced technology more accessible for mass-market adoption.
Future systems may also incorporate elements that evaluate a vehicle’s surroundings and road surface friction to help drivers make more informed decisions about braking and other safety-related actions. Vehicle-to-vehicle communication can further enhance ADAS capabilities by sharing sensor data.
Ultimately, improving safety and reaction times in adverse driving conditions is the goal, and the fusion of thermal imaging and imaging radar has the potential to achieve this like never before.
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