Multi-Camera Layout for Vehicle Object Detection at All Ranges
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing camera systems for vehicles lack a comprehensive solution to efficiently detect and identify objects at various distances and angles around the vehicle, which is crucial for safe autonomous or semi-autonomous operation.
Innovation Solution
A system comprising multiple cameras of different types and fields of view, including a first camera type with a narrow field of view, a second camera type with at least 170° yaw, and a third camera type with a 360° yaw, combined with lidar data, to identify objects at close, intermediate, and long ranges and angles relative to the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single camera type with a fixed field of view is used, then the device complexity is reduced, but the ability to detect objects at various distances and angles is insufficient
Solution Approach 1:
The camera system is segmented into three distinct camera types, each optimized for specific detection ranges and angles. Front cameras capture narrow-angle forward views at long distances, side cameras provide wide-angle lateral coverage at intermediate distances, and rear cameras deliver 360-degree panoramic views at close distances. This segmentation allows each camera type to specialize in particular spatial zones, achieving comprehensive detection coverage while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The camera system achieves multi-functionality by deploying multiple camera types that collectively perform various detection functions. The combination of front, side, and rear cameras enables the system to simultaneously detect objects at long ranges, intermediate ranges, and close distances across all directional angles. Each camera type contributes specific functional capabilities that, when integrated, create a universal detection system capable of handling diverse detection scenarios
2Measurement precision
If multiple cameras of different types are used to cover all distances and angles, then object detection accuracy is improved, but the device complexity increases
Solution Approach 1:
Each camera type is assigned specific local quality characteristics optimized for its detection zone. Front cameras use narrow fields of view with longer focal lengths optimized for distant object detection, side cameras employ wide-angle lenses optimized for lateral coverage at intermediate distances, and rear cameras provide 360-degree coverage optimized for close-proximity detection. This local quality optimization ensures that each camera type achieves maximum detection accuracy for its designated spatial region
Solution Approach 2:
The system transitions from two-dimensional detection planes to three-dimensional spatial coverage by combining cameras oriented in different directions (front, side, rear) and at different angles. This dimensional expansion allows the system to detect objects in all spatial directions and at all distance ranges simultaneously, achieving comprehensive volumetric detection accuracy
3Area of stationary object
If cameras with wider fields of view are used, then the coverage area is increased, but the detection precision for distant objects is reduced
Solution Approach 1:
The detection space is segmented into different angular and distance zones, with each camera type assigned to specific segments. Front cameras cover the forward direction with narrow angles optimized for long-distance precision, side cameras cover lateral directions with wide angles optimized for intermediate distances, and rear cameras cover all rear angles for close-distance detection. This spatial segmentation allows each camera to optimize its field of view for its designated zone, maintaining detection precision while achieving comprehensive coverage
Data Source
AI summary
Example embodiments relate to camera arrangements for vehicular object detection and avoidance. An example system includes a vehicle and at least one camera of a first camera type attached to the vehicle. The system also includes a plurality of cameras of a second camera type attached to the vehicle. Further, the system includes a plurality of cameras of a third camera type attached to the vehicle. Moreover, the system includes a computing device communicatively coupled to the at least one camera of the first camera type, plurality of cameras of the second camera type, and plurality of cameras of the third camera type. The computing device is configured to identify objects located within a first range of distances from the vehicle, objects located within a second range of distances from the vehicle, and objects located within a third range of distances from the vehicle.