Vehicle Obstacle Control Using Adaptive SVM Collision Detection
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Solution Overview
Problem
Existing vehicle safety control systems rely heavily on specific situations and limited reliability of Surround View Monitoring (SVM) for obstacle detection, which can lead to inadequate prevention of collision accidents.
Innovation Solution
A vehicle safety control system that includes a sensing unit to detect obstacles, a determination unit to operate SVM and determine distances, and a controller to pre-store warning and danger ranges, transmit warnings, and control vehicle deceleration or braking based on the distance and collision danger.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If SVM is operated only in specific situations (e.g., parking), then device complexity is reduced, but reliability of obstacle detection deteriorates
Solution Approach 1:
The SVM system dynamically adjusts its operation based on real-time driving conditions and obstacle proximity. The controller activates SVM not only during parking but also when obstacles are detected within predetermined distances during normal driving, making the system adaptive to varying operational contexts rather than static.
Solution Approach 2:
The system changes operational parameters by adjusting SVM activation thresholds based on driving mode and obstacle characteristics. When radar or camera sensors detect obstacles within specific distance ranges, the controller modifies SVM operation intensity and frequency, optimizing detection reliability without continuously operating at full complexity.
2Use of energy by moving object
If SVM is driven only when obstacles are adjacent to the vehicle, then energy consumption is reduced, but measurement precision of obstacle distance deteriorates
Solution Approach 1:
The system performs preliminary obstacle detection using radar and camera sensors at longer ranges before activating SVM for precise distance measurement. This preliminary screening allows the system to prepare for potential SVM activation, ensuring measurement precision is maintained when obstacles are detected within critical distance thresholds while avoiding unnecessary continuous SVM operation.
3Reliability
If obstacle detection range is expanded beyond SVM capability, then reliability of obstacle recognition is improved, but device complexity increases
Solution Approach 1:
The system merges multiple sensing technologies (radar sensor, camera sensor, and SVM) into an integrated obstacle detection system. Each sensor type compensates for the limitations of others, with radar providing long-range detection, camera offering visual recognition, and SVM delivering precise近距离 measurement, creating a complementary multi-sensor architecture that improves reliability without requiring a single complex system.
Solution Approach 2:
The controller acts as an intermediary that coordinates between different sensing units and the SVM system. It processes data from radar and camera sensors to determine when SVM activation is necessary, managing the interaction between multiple sensors and optimizing their combined output to improve obstacle recognition reliability while maintaining manageable system complexity.
Data Source
AI summary
The present disclosure introduces a vehicle safety control system and a vehicle safety control method, which recognize, in advance, an obstacle approaching the vehicle around the vehicle, and, when the vehicle and the obstacle come near each other in distance, operate SVM to determine the possibility of collision between the vehicle and the obstacle in advance, and prevent a collision accident by controlling the vehicle on the basis of the possibility of collision between the vehicle and the obstacle.