Lateral Collision Avoidance Control Using Risk-Based Vehicle Steering
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Solution Overview
Problem
Existing autonomous emergency brake (AEB), forward vehicle collision mitigation system (FVCMS), and pedestrian detection and collision mitigation system (PDCMS) do not consider the level of risk or possibility of collision when avoiding a forward object, leading to unnecessary or excessive vehicle control.
Innovation Solution
A lateral movement system for collision avoidance using sensors to detect objects, a processor to judge the risk of collision, and actuators to execute lateral vehicle movement based on predetermined conditions, including vehicle speed, object speed, and lane markings, allowing collision avoidance through steering without deceleration braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AEB, FVCMS, or PDCMS activates brake or steering when collision possibility is detected, then collision avoidance capability is improved, but driving comfort deteriorates due to unnecessary or excessive vehicle control
Solution Approach 1:
The system changes the control parameter from binary (activate/deactivate) to continuous risk level assessment. It evaluates multiple parameters including distance to object, relative speed, object type, and environmental conditions to determine a continuous risk score, enabling proportional response rather than threshold-based activation
Solution Approach 2:
The system applies partial action by activating collision avoidance measures only when the assessed risk exceeds predetermined thresholds. It uses a hierarchical approach where lower-risk situations receive minimal or no intervention, while higher-risk situations receive progressively stronger control actions, avoiding unnecessary braking or steering in low-risk scenarios
2Measurement precision
If the system uses multiple sensors and complex judgment criteria to assess collision risk, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the collision risk assessment into distinct modules: object detection module, distance calculation module, relative speed calculation module, object type classification module, and risk level determination module. Each module processes specific parameters independently, making the complex assessment manageable and maintainable
Solution Approach 2:
The system uses multi-functional sensors that can detect multiple types of objects (vehicles, pedestrians, cyclists) and provide multiple parameters (distance, speed, angle) simultaneously. The processor applies universal judgment criteria that work across different object types and scenarios, reducing the need for separate specialized systems
Data Source
AI summary
The present disclosure relates to an autonomous vehicle system or a driver assistance system that detects an object in front of the vehicle, judges whether a condition calls for an operation of a lateral movement system for collision avoidance, determines a direction of the lateral movement, and executes the lateral movement.