Vehicular Vision System Door Collision Detection
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Solution Overview
Problem
Current vehicle vision systems fail to effectively detect pedestrians or bicycles in the path of a parked vehicle's side door, leading to potential collisions and door damage, especially in varying lighting conditions.
Innovation Solution
A vehicle vision system utilizing CMOS cameras and a Gaussian mixture model for foreground segmentation, combined with block matching and distance estimation algorithms, to detect and track objects, and generate alerts or restrict door opening when a collision is likely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional vehicle vision systems are used, then the system structure is simple, but the detection reliability of pedestrians and bicycles is insufficient
Solution Approach 1:
The system segments the detection task into multiple specialized algorithms: a first algorithm for rapid object finding, a second algorithm for accuracy enhancement with adaptive search area selection, and a third algorithm for detecting fast-moving objects in extended areas. This segmentation allows each algorithm to optimize for specific detection scenarios, improving overall reliability without requiring a complete system redesign.
Solution Approach 2:
The system dynamically adjusts the search area and algorithm selection based on detected objects and their motion characteristics. The second algorithm adaptively determines where to search based on the first algorithm's results, and the third algorithm activates for faster moving objects. This dynamic adaptation improves detection reliability while maintaining reasonable system complexity through conditional execution.
2Measurement precision
If image processing algorithms are enhanced for better object detection, then the detection precision improves, but the processing time increases
Solution Approach 1:
The system applies partial processing by using the first algorithm to quickly identify potential objects, then selectively applying the more computationally intensive second algorithm only to regions of interest identified by the first algorithm. This partial application of advanced processing maintains high detection precision while minimizing overall processing time by avoiding exhaustive analysis of the entire image.
Solution Approach 2:
The second algorithm enhances search accuracy in specific local areas by adaptively determining search areas based on the first algorithm's results. Instead of uniformly processing the entire image with high precision, the system concentrates computational resources on local regions where objects are likely to be found, improving detection precision where needed while reducing overall processing time.
3Area of stationary object
If the search area is expanded to detect faster moving objects, then the detection coverage improves, but the processing speed decreases
Solution Approach 1:
The system dynamically adjusts the search area based on object motion characteristics. The third algorithm is specifically activated for faster moving objects and operates in a larger search area, while the first two algorithms handle slower or stationary objects in more limited areas. This dynamic adjustment ensures comprehensive coverage for fast objects while maintaining processing speed through conditional algorithm selection.
Solution Approach 2:
Different algorithms are applied to different spatial regions based on object characteristics. The third algorithm with its larger search area is selectively applied only when fast-moving objects are detected, rather than uniformly processing the entire image area. This localized application of expanded search coverage maintains processing efficiency while improving detection capability for specific scenarios.
Data Source
AI summary
A vehicular vision system includes a camera at a side of a vehicle and having a field of view exterior of the vehicle. With the vehicle parked, the system processes via an image processor image data captured by the camera to detect an object present in a detection zone at least partially along the side of the vehicle. With the vehicle parked, the system tracks the detected object to determine movement of the object relative to the parked vehicle. Responsive to tracking the detected object, the system is operable to determine that the object is in a danger zone at a side door of the parked vehicle that includes a sweep area that the side door swings through when opening. With the side door closed, and at least in part responsive to determination that the object is in the danger zone, the system limits opening of the side door.