Vehicle Control Apparatus Using Multi-Point Object Tracking
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Solution Overview
Problem
Existing vehicle control systems face errors in detecting object positions due to the shape and pattern of objects, leading to incorrect movement tracks and unnecessary operations during collision avoidance, which can result in improper collision avoidance control.
Innovation Solution
A vehicle control apparatus that detects objects ahead using an imaging section and radar sensor, calculates movement directions for specific points, and adjusts collision avoidance control based on differences in these directions to prevent unnecessary operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If collision avoidance control is performed based on detected object positions, then traveling safety is improved, but unnecessary operations occur due to detection errors
Solution Approach 1:
The system calculates movement directions from historical position data and uses this information as feedback to verify detection accuracy. When movement directions are inconsistent, the system adjusts control actions, creating a closed-loop verification mechanism that prevents unnecessary operations while maintaining safety.
Solution Approach 2:
The system performs preliminary calculations of movement directions based on historical position data before executing collision avoidance control. This preliminary action allows the system to predict object behavior and verify detection accuracy in advance, preventing unnecessary control operations.
2Difficulty of detecting and measuring
If object position is detected from image, then object detection is achieved, but position error occurs due to object shape and pattern
Solution Approach 1:
The system divides the object detection task into multiple specific points (at least two different points) rather than detecting a single position. This segmentation allows verification of detection accuracy by comparing movement directions of multiple points, reducing the impact of shape and pattern variations on position accuracy.
Solution Approach 2:
The system introduces movement direction calculation as an intermediary verification step between position detection and collision avoidance control. By calculating movement directions from historical position data and comparing them, the system creates an intermediate check that filters out position errors caused by object shape and pattern variations.
3Extent of automation
If movement track is calculated from position history, then collision avoidance control is enabled, but incorrect control results from position errors
Solution Approach 1:
The system uses movement direction consistency as feedback to verify the reliability of calculated movement tracks. When movement directions from multiple specific points are inconsistent, the system identifies detection errors and adjusts control actions, ensuring reliable automated collision avoidance control.
Solution Approach 2:
The system performs preliminary verification of movement track accuracy by calculating and comparing movement directions before executing collision avoidance control. This preliminary check ensures that only accurate movement tracks based on consistent position data are used for automated control.
Data Source
AI summary
A driving assist ECU acquires, based on an image, positions of at least two specific points of an object that are different in a lateral direction with respect to a vehicle traveling direction. The driving assist ECU also performs collision avoidance control for avoiding a collision with the object based on a movement track of the object obtained from a history of the positions of the specific points, and calculates, for each of the specific points, a movement direction of each of the specific points based on the history of the position of each of the specific points. The driving assist ECU then changes how to perform the collision avoidance control based on a difference between the movement directions at the respective specific points.