Collision Prediction Apparatus Using Reliability-Weighted Trajectory Analysis
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Solution Overview
Problem
Existing collision prediction apparatuses face reduced prediction accuracy due to low reliability in positional information detected by radar, which affects the accuracy of collision probability prediction between a target object and a host vehicle.
Innovation Solution
A collision prediction apparatus that utilizes a sensor to obtain positional information of a target object and a processing device to calculate its movement trajectory and predict collision probability based on the number of time points, change in lateral width, and longitudinal position change relative to the host vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If positional information detected by radar is handled equally without reliability assessment, then the processing is simple, but prediction accuracy is reduced due to low reliability detection points
Solution Approach 1:
The patent applies local quality by differentiating the treatment of positional information based on its reliability. Instead of handling all detection points uniformly, the system assigns different weights or reliability levels to individual positional data points. Detection points with higher reliability (e.g., those with stronger radar signals or better geometric conditions) are given greater influence in trajectory calculation, while low-reliability points are downweighted or excluded. This selective processing improves collision probability prediction accuracy without requiring completely complex additional hardware.
2Measurement precision
If more positional information is used to calculate movement trajectory, then prediction accuracy improves, but the influence of low reliability detection points increases
Solution Approach 1:
The patent employs parameter changes by introducing reliability parameters associated with each positional information point. These parameters (such as signal strength, detection confidence, or geometric reliability factors) are used to dynamically adjust the weight or influence of each detection point in the trajectory calculation. By changing the parameter representation from uniform treatment to weighted treatment based on reliability metrics, the system can utilize more positional information while filtering out the harmful influence of low-reliability detections through appropriate weighting schemes.
Data Source
AI summary
A collision prediction apparatus includes a sensor that obtains positional information representing a position of a target object with respect to a host vehicle and a processing device wherein the processing device calculates a movement trajectory of the target object with respect to a vehicle, based on the positional information obtained at time points by the sensor, and the processing device predicts a probability of a collision between the target object and the vehicle, based on the calculated movement trajectory and at least one of three parameters which includes a number of obtainment time points of the positional information used to calculate the movement trajectory, a change manner of a lateral width of the target object related to the positional information between time points, and a change manner of the positional information of the target object with respect to the vehicle in a longitudinal direction of the vehicle.