ADAS Turn-Path Risk Zoning for Pedestrian Collision Avoidance
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Solution Overview
Problem
Current advanced driver assistance systems (ADAS) lack the capability to effectively assess and mitigate collision risks with pedestrians during turns, as they do not adequately account for the positional relationship between vehicles and pedestrians in dynamic driving conditions such as turns, leading to potential accidents.
Innovation Solution
An advanced driver assistance system that utilizes a camera to obtain road images, processes them to generate risk zones, predicts obstacle positions, and adjusts risk levels based on obstacle presence, incorporating obstacle detection and driving information to perform collision avoidance controls, particularly during turns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the ADAS uses basic obstacle detection without considering turn path and positional relationship, then the system complexity is low, but the collision risk assessment accuracy deteriorates
Solution Approach 1:
The system divides the assessment into two distinct risk zones: a first risk of collision region based on the turn path, and a second risk of collision region based on predicted obstacle positions. This segmentation allows the system to evaluate different spatial areas with different assessment criteria, improving overall accuracy without requiring a complete redesign of the detection system.
Solution Approach 2:
The system transitions from basic 2D obstacle detection to 3D spatial assessment by incorporating turn path geometry and predicting future obstacle positions. This dimensional enhancement allows the system to assess collision risk in the context of vehicle motion and environmental dynamics, significantly improving assessment accuracy.
2Measurement precision
If the ADAS implements turn-specific collision assessment with multiple risk zones, then the collision risk assessment accuracy is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system pre-calculates the turn path and establishes the first risk of collision region before detecting obstacles. By preparing the assessment framework in advance, the system reduces real-time computational burden and processing time while maintaining high assessment accuracy.
Solution Approach 2:
The system dynamically adjusts the second risk of collision region based on real-time obstacle detection and turn conditions. This dynamic adaptation allows the system to focus computational resources on relevant areas, reducing overall processing time while maintaining accurate collision risk assessment.
Data Source
AI summary
A method of controlling the vehicle includes determining whether a section to be driven is a turn section; in response to determining that the section to be driven is the turn section, generating a turn path; generating a first risk of collision region based on the generated turn path; predicting a position of an obstacle based on obstacle information detected by an obstacle detector and driving information detected by a driving information detector; generating a second risk of collision region based on the predicted position of the obstacle; based on image information obtained from an imager, determining whether the obstacle exists in the first and second risk of collision regions, respectively; adjusting a risk level based on the presence or absence of the obstacle in the first and second risk of collision regions; and performing a collision avoidance control corresponding to the adjusted risk level.