Wireless Relative Position Detection for Collision Avoidance
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Solution Overview
Problem
Existing collision avoidance systems, particularly those using cameras, fail to accurately detect vehicles under bad weather conditions such as thick fog or heavy rain, leading to potential safety hazards.
Innovation Solution
A computer-implemented method and system that uses wireless communication to receive and process metrics like latitude, longitude, elevation, speed, and heading direction from vehicles to calculate relative positions and generate notifications when a predetermined distance and elevation difference are met, allowing for accurate collision detection even in adverse weather.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera-based monitoring is used to detect vehicles, then the system can provide visual detection capability, but the detection accuracy deteriorates under bad weather conditions such as thick fog or heavy rain
Solution Approach 1:
The patent replaces the optical camera-based detection system with a wireless communication-based detection system that uses metric data (latitude, longitude, elevation, speed, heading direction) exchanged between vehicles and infrastructure. This substitution eliminates the reliance on visual detection that fails in bad weather, providing reliable collision risk assessment through computational geometry and metric comparison instead of optical imaging.
2Reliability
If wireless communication metrics are used to calculate relative position, then detection reliability improves under bad weather, but the system complexity increases due to multiple metric processing requirements
Solution Approach 1:
The patent uses universal wireless communication infrastructure and standard metric data (latitude, longitude, elevation, speed, heading direction) that can be obtained from existing GPS and communication systems. By processing these universally available metrics through geometric calculations and threshold comparisons, the system achieves reliable collision detection without requiring specialized hardware, thus managing complexity while maintaining high reliability.
Solution Approach 2:
The patent creates a virtual model of the spatial relationship between vehicles by copying and processing metric data from wireless communications. Instead of directly sensing physical positions, the system constructs a computational representation using latitude, longitude, elevation, speed, and heading direction metrics, then performs collision risk assessment on this virtual model. This approach simplifies the physical system requirements while enabling reliable detection.
3Measurement precision
If multiple metrics (latitude, longitude, elevation, speed, heading direction) are processed, then the precision of relative position calculation improves, but the computational complexity increases
Solution Approach 1:
The patent segments the collision detection process into distinct computational stages: first calculating horizontal distance from latitude and longitude, then calculating vertical distance incorporating elevation, speed, and heading direction, and finally comparing these segmented distance components against threshold values. This segmentation allows the system to process multiple metrics systematically without overwhelming computational complexity, achieving high precision through structured multi-step calculation.
Data Source
AI summary
The present disclosure relates to a computer-implemented method. The method includes: receiving a first metric of a first object; receiving a second metric of a second object; calculating a distance between the first object and the second object based on the first metric and the second metric; comparing the calculated distance with a predetermined distance; identifying whether the second object is approaching the first object based on the first metric and the second metric; calculating an elevational difference between the first object and the second object; and generating a notification responsive to the calculated distance being less than the predetermined distance, the second object being identified as approaching the first object and the calculated elevational difference between the first object and the second object being less than a predetermined value.