Vehicle Collision Avoidance System Using Rotating Coordinate Transformation
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Solution Overview
Problem
Existing collision avoidance systems in vehicles fail to accurately assess collision threats during turns due to the rotation of the vehicle coordinate system, leading to false positive identifications and inadequate threat evaluations.
Innovation Solution
A system that predicts the heading angle of a host vehicle during a turn and adjusts threat assessments based on lateral and longitudinal distances in a rotated coordinate system, incorporating brake delay time, target speed, and vehicle width to actuate brakes or steering accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional collision avoidance systems use sensors to detect target objects and calculate collision probability based on current position and speed, then the system can identify potential collision threats, but the system produces false positive identifications and inadequate threat evaluations during vehicle turns due to coordinate system rotation
Solution Approach 1:
The system dynamically transforms collision threat calculations from the vehicle's rotating coordinate system to a fixed global coordinate system during turns. This resolves the contradiction by making the measurement system adaptive to vehicle motion states, eliminating false positives caused by coordinate rotation while maintaining accurate threat detection throughout the maneuver
Solution Approach 2:
The system changes the reference frame parameter from vehicle-relative coordinates to global fixed coordinates during turn operations. This parameter transformation eliminates the rotational distortion that causes measurement errors, improving both assessment accuracy and reliability by using a stable reference system that doesn't change with vehicle orientation
2Reliability
If the system actuates brakes or steering to avoid collision, then collision risk is reduced, but unnecessary actuations occur due to false positive threat identifications
Solution Approach 1:
The dynamic coordinate transformation ensures that brake and steering actuation decisions are based on accurate collision probability calculations in a fixed reference frame. This eliminates false positive triggers during turns, reducing unnecessary component actuations while maintaining reliable collision avoidance when actual threats are detected
3Reliability
If the system considers vehicle turn dynamics and coordinate rotation for threat assessment, then false positive identifications are reduced, but the computational complexity increases
Solution Approach 1:
The system pre-calculates and stores transformation parameters and collision probability models before turns occur. During actual turns, the system applies pre-prepared transformation matrices and algorithms, reducing real-time computational complexity while maintaining high assessment accuracy through advance preparation of computational resources
Data Source
AI summary
A computer includes a processor and a memory, the memory storing instructions executable by the processor to identify an initial lateral distance and an initial longitudinal distance of a host vehicle in a turn at an initiation of the turn, predict a heading angle of the host vehicle at a specified time after the initiation of the turn, predict a final lateral distance and a final longitudinal distance between the host vehicle and a target at the specified time based on the identified lateral distance, the identified longitudinal position, and the predicted heading angle, determine a lateral offset at a longitudinal time to collision based on the final lateral distance and the final longitudinal distance, and actuate a brake of the host vehicle according to a threat assessment based on the lateral offset.