Optical Sensor Fusion With Infrared Activation for Low-Light ADAS
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Solution Overview
Problem
Modern vehicles equipped with onboard sensors face performance limitations in adverse weather conditions, leading to disengagement of automated driver-assistance systems (ADAS) due to hardware constraints of visible light cameras, such as blinding from headlights and ineffectiveness in extreme low light conditions.
Innovation Solution
Integration of visible light cameras with shortwave infrared (SWIR) and longwave infrared (LWIR) cameras, along with LiDAR technology, to generate fused images that enhance object detection and recognition capabilities, proactively predicting and reacting to road hazards like black ice and organic materials, and alternating between technologies to optimize energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visible light cameras are used for environmental sensing, then the system performs well under normal lighting conditions, but the camera becomes ineffective in extreme low light conditions or when blinded by headlights
Solution Approach 1:
The patent combines multiple imaging sensors including visible light cameras, infrared cameras (SWIR and LWIR), and LiDAR systems into an integrated sensor suite. This merging allows the system to leverage the strengths of each sensor type - visible light cameras provide high-resolution imagery under normal conditions, while infrared sensors maintain effectiveness in low light and adverse weather, and LiDAR provides reliable depth information regardless of lighting conditions.
Solution Approach 2:
The patent implements a multi-functional sensing system where different sensors serve multiple purposes. The same sensor suite operates across diverse environmental conditions (day/night, clear/foggy/rainy weather), and individual sensors can function independently or in combination. For example, infrared cameras can detect thermal signatures for object detection in darkness, while also providing imagery capabilities during daytime when combined with visible light cameras.
2Measurement precision
If multiple imaging sensors are integrated to improve performance in adverse conditions, then object detection accuracy improves, but system complexity and energy consumption increase
Solution Approach 1:
The patent implements dynamic sensor activation and fusion strategies where the system adapts its operational mode based on environmental conditions. The processor continuously monitors sensor data quality and dynamically adjusts which sensors are active and how their data is fused. This allows the system to achieve high measurement precision when needed while reducing complexity during normal operating conditions.
Solution Approach 2:
The system employs periodic sensing and data fusion cycles, where sensors are activated in sequences or cycles rather than continuously operating at full capacity. This periodic action allows the system to gather necessary data for accurate object detection while managing power consumption and processing loads, thereby reducing effective system complexity without sacrificing detection accuracy.
3Reliability
If multiple imaging sensors operate continuously to ensure reliable detection, then detection confidence increases, but energy consumption increases
Solution Approach 1:
The patent implements periodic sensing cycles where sensors are activated only when needed based on environmental conditions and detection requirements. Rather than continuous operation, the system periodically samples the environment using appropriate sensors, fuses the data, and updates object detections. This periodic action maintains high detection confidence for critical functions while significantly reducing overall energy consumption compared to continuous operation.
Solution Approach 2:
The system dynamically adjusts sensor activation states based on real-time environmental assessments and detection needs. When adverse conditions are detected (low light, fog, rain), the system activates additional sensors and increases fusion processing to maintain reliable detection confidence. During normal conditions, the system reduces sensor activation and processing intensity, thereby managing energy consumption while preserving detection reliability when required.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The integrated sensor system significantly improves the accuracy and confidence of object detection and recognition, reducing ADAS disengagement, enabling safer and more reliable autonomous vehicle operation in adverse conditions while conserving energy.
Implementation Method 1
receiving, by a processor, a first image captured by a visible light camera
Implementation Method 2
activating an infrared camera in response to the environmental condition, capturing a third image by the infrared camera
Implementation Method 3
light detection and ranging (LiDAR) systems
Implementation Method 4
light detection and ranging (LiDAR) systems
Data Source
AI summary
An optical sensor system operative for receiving, by a processor, a first image captured by a visible light camera, determining a value of a characteristic of the first image, determining an environmental condition in response to the value being less than a threshold, activating an infrared camera in response to the environmental condition, capturing a second image by the visible light camera and a third image by the infrared camera, generating a fused image in response to the second image and the third image, detecting an object in response to the fused image, and controlling a vehicle in response to the detection of the object.