Dynamic Detection Area Generation for Traveling Vehicle Interference Avoidance
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Solution Overview
Problem
Existing obstacle detection systems in traveling vehicles often use excessively wide detection areas to ensure safety, leading to inefficient inter-vehicle distances and potential dead angles, as they struggle to optimize detection patterns and differentiate between relevant and irrelevant obstacles.
Innovation Solution
A system that generates real-time detection areas based on the vehicle's position and velocity, using a map to determine optimal interference ranges and adjust detection zones dynamically, ensuring no dead angles and minimizing inter-vehicle distance by prioritizing efficient obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a wide detection area is used to ensure safety, then the reliability of obstacle detection is improved, but the inter-vehicle distance becomes excessively large and travel efficiency decreases
Solution Approach 1:
The detection area is divided into multiple regions with different detection sensitivities and priorities. The front detection area has higher priority for obstacle detection compared to side areas, allowing the system to focus computational resources on critical zones while reducing unnecessary detection in less critical areas, thus improving efficiency without compromising safety
Solution Approach 2:
The detection area is segmented into multiple distinct regions (front detection area, side detection areas, etc.) with different angular ranges and priorities. This segmentation allows the system to optimize detection parameters for each region independently, reducing the overall detection burden while maintaining comprehensive safety coverage
2Productivity
If the detection area is narrowed to improve travel efficiency, then the inter-vehicle distance is shortened, but dead angles are created where obstacles cannot be detected
Solution Approach 1:
The detection area parameters (angular range, detection sensitivity) are dynamically adjusted based on the vehicle's current state including position, speed, and acceleration requirements. As the vehicle approaches an obstacle or changes speed, the detection area automatically adapts to maintain optimal coverage without creating dead angles, ensuring both efficiency and comprehensive detection
Solution Approach 2:
The detection system uses a universal detection framework that can adapt to different vehicle positions, speeds, and route conditions. The same detection apparatus serves multiple functions by adjusting its parameters dynamically, providing both narrow focused detection when needed and wider coverage when safety requires it, eliminating dead angles while maintaining efficiency
3Reliability
If multiple patterns of detection areas are stored to cover different vehicle positions, then the detection coverage is improved, but the device complexity increases due to the large number of patterns required
Solution Approach 1:
Instead of storing multiple static detection patterns, the system dynamically generates detection area parameters in real-time based on the vehicle's current position, speed, and route information. This dynamic approach eliminates the need for extensive pattern storage while maintaining comprehensive detection coverage across all possible vehicle states
Solution Approach 2:
The detection system automatically adjusts its own parameters based on real-time vehicle state information without requiring pre-stored patterns or external configuration. The system serves itself by calculating optimal detection areas on-the-fly using the vehicle's current position, speed, and route data, simplifying the overall system architecture
Data Source
AI summary
A traveling vehicle is equipped with an obstacle sensor to detect a distance to an obstacle and an orientation relative to the obstacle. A map of a travel route of the traveling vehicle is stored. A detection area where deceleration of the traveling vehicle is required if there is any obstacle in the detection area is repeatedly generated based on the position of the traveling vehicle from the map. Among obstacles detected by the obstacle sensor, an obstacle in the detection area is detected. Deceleration control of the traveling vehicle is implemented to prevent interference with the detected obstacle.