Vehicle Radar System Dynamic Threshold for Curve Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle environment detection systems face challenges in accurately classifying oncoming versus crossing traffic, especially in curves, which can lead to false positives and inefficient collision prevention measures.
Innovation Solution
A vehicle environment detection system that includes a vehicle radar system with a main control unit, which determines the ego direction and oncoming direction of tracked vehicles, calculates a difference angle, and compares it to a threshold angle that adapts based on the vehicle's rotational velocity, to differentiate between oncoming and crossing traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed threshold angle is used to classify oncoming versus crossing traffic, then the classification process is simple and fast, but the accuracy deteriorates in curved roads causing false positives
Solution Approach 1:
The patent applies the dynamics principle by transforming the static threshold angle into a dynamic parameter that adapts to the ego vehicle's rotational velocity. The threshold angle is no longer fixed but varies according to the vehicle's motion state, allowing the system to maintain high classification accuracy across different driving conditions including curved roads, while avoiding false positives that would occur with a fixed threshold
Solution Approach 2:
The patent implements parameter changes by modifying the threshold angle parameter based on the ego vehicle's rotational velocity. When the vehicle rotates (e.g., navigating a curve), the threshold angle is adjusted proportionally to the rotational speed, thereby maintaining accurate classification of oncoming versus crossing traffic despite the changing geometric relationship between the vehicle and detected objects
2Reliability
If the threshold angle is increased to avoid false positives in curves, then classification reliability improves, but the system becomes less sensitive to actual collision risks
Solution Approach 1:
The patent resolves this contradiction by dynamically adjusting the threshold angle parameter based on the ego vehicle's rotational velocity. Instead of using a uniformly high threshold that reduces sensitivity, the system adapts the threshold to match the vehicle's motion state - increasing it during rotation to reduce false positives, while maintaining appropriate sensitivity levels when the vehicle is stationary or moving straight, thus balancing reliability and detection sensitivity
3Measurement precision
If radar cycles are used to measure oncoming direction over time, then measurement accuracy improves, but the response time for collision prevention increases
Solution Approach 1:
The patent applies partial action by using a minimal number of radar cycles (exactly two) to obtain sufficient directional information. Instead of continuously accumulating radar data over extended periods, the system uses just two measurements taken at different positions of the oncoming object to calculate its direction, thereby achieving adequate measurement precision while minimizing the time delay for collision prevention responses
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and reliability of determining whether an oncoming vehicle will collide with the ego vehicle, allowing for timely and appropriate safety measures to be applied, such as emergency braking or steering, thereby improving collision prevention.
Implementation Method 1
a vehicle radar system with a radar sensor arrangement arranged to distinguish and/or resolve single targets from the surroundings by transmitting signals and receiving reflected signals and using a Doppler effect
Implementation Method 2
transmitting signals and receiving reflected signals and using a Doppler effect
Data Source
AI summary
A vehicle environment detection system (40) in an ego vehicle (1), including a sensor arrangement (4) and a main control unit (8) is arranged to detect and track at least one oncoming vehicle (9), and to determine whether the ego vehicle (1) has entered a curve (17). When this is the case. The main control unit (8) is arranged to, determine an ego direction (21) along which the ego vehicle (1) travels with a corresponding ego direction angle (γego) with respect to a predetermined axis (xglob), determine a measured oncoming direction (18) of the tracked oncoming vehicle (9) with a corresponding oncoming angle (θtrack, glob) with respect to the predetermined axis (xglob) during a plurality of radar cycles, determine a difference angle (δ) between the measured oncoming direction (18) and the ego direction (21), and compare the difference angle (δ) with a threshold angle (θmax), and to determine that the oncoming vehicle (9) is crossing if the difference angle (δ) exceeds the threshold angle (θmax).