Autonomous Vehicle Sensor Layout With Multi-Focal Camera Coverage
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Solution Overview
Problem
Current autonomous vehicle technology is reactive and lacks the ability to make real-world judgment calls, struggles to predict human driver behaviors, and has limited capacity to assess risks, leading to potential accidents due to inadequate sensor layouts.
Innovation Solution
An optimized sensor layout for autonomous vehicles, including a combination of forward-facing cameras with varying focal lengths and LiDAR/RADAR systems, providing a 360-degree field of view to accurately perceive the environment, pedestrians, other vehicles, and debris, enabling the vehicle to make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to perceive the surrounding environment, then the accuracy and completeness of environmental perception is improved, but the complexity of the sensor system and data processing increases
Solution Approach 1:
The sensor system is segmented into multiple specialized camera modules (forward-facing, right-side, left-side cameras) with different focal lengths, each optimized for specific detection tasks. This segmentation allows the system to cover various detection ranges and angles while maintaining manageable complexity through functional specialization.
Solution Approach 2:
The camera system is designed with multi-functionality to perform various detection tasks using a unified sensor platform. The same camera hardware can capture images at different focal lengths and angles, serving multiple purposes such as distant object detection, close-range obstacle identification, and panoramic environmental mapping, thereby reducing the need for entirely separate sensor systems.
2Reliability
If sensors provide comprehensive data to algorithm modules, then the decision-making accuracy is improved, but the computational load on algorithm modules increases
Solution Approach 1:
The system extracts and processes critical environmental features using specialized camera modules with different focal lengths before feeding data to algorithm modules. By pre-processing and filtering data at the sensor level, the system extracts only the most relevant information (distant objects, close-range obstacles, environmental context) thereby reducing the computational burden on downstream algorithm modules while maintaining decision-making accuracy.
3Adaptability or versatility
If forward-facing cameras have different focal lengths, then the detection range and detail capability are improved, but the device complexity increases
Solution Approach 1:
Different forward-facing camera modules are equipped with locally optimized qualities through varying focal lengths. Some cameras use wide-angle lenses for broad environmental overview, while others employ telephoto lenses for detailed distant object detection. This local quality differentiation allows each camera to excel at specific detection tasks within the overall system, improving adaptability while managing complexity through specialized functional design.
Data Source
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AI summary
Disclosed are devices and systems for an optimized sensor layout for an autonomous or semi-autonomous vehicle. In one aspect, the system includes a vehicle capable of semi-autonomous or autonomous operation. A plurality of forward-facing cameras is coupled to the vehicle and configured to have a field of view in front of the vehicle. At least three forward- facing cameras of the plurality of forward-facing cameras have different focal lengths. A right- side camera is coupled to the right side of the vehicle, the right-side camera configured to have a field of view to the right of the vehicle. A left-side camera is coupled to the left side of the vehicle, the left-side camera is configured to have a field of view to the left of the vehicle