Map-Based Emergency Braking for Variable Road Conditions
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Solution Overview
Problem
Existing autonomous emergency braking systems face challenges in accurately determining braking distances and recognizing targets on various road environments, leading to potential erroneous controls and malfunctions, especially in low-frequency scenarios like highways.
Innovation Solution
An autonomous emergency braking method utilizing map data to classify road types and targets, adjusting braking strategies based on real-time road conditions, and implementing enhanced filtering for low-probability targets to reduce misrecognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the autonomous emergency braking system operates on the same basis regardless of pavement level differences, then the system structure remains simple, but the braking distance becomes inconsistent across different road conditions
Solution Approach 1:
The patent applies local quality by adjusting braking parameters according to specific road conditions. The controller modifies braking force and distance based on the detected pavement level, allowing the system to adapt its characteristics to local road conditions rather than using a uniform braking strategy for all surfaces.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting braking parameters (such as braking force, deceleration rate, and stopping distance) based on the detected road condition. The system changes its operational parameters according to the pavement level, transitioning from a fixed-parameter system to a variable-parameter system that responds to environmental conditions.
2Device complexity
If the autonomous emergency braking system uses only sensor data without map data, then the system complexity remains low, but it cannot distinguish between different road types and may malfunction in low-frequency scenarios
Solution Approach 1:
The patent merges sensor data with map data to create a comprehensive road condition assessment system. By combining real-time sensor information with pre-stored map information about road types and characteristics, the system achieves more reliable target recognition and braking decisions, particularly in rare or low-frequency scenarios where sensor data alone may be insufficient.
Solution Approach 2:
The patent applies preliminary action by pre-storing map data containing road type information, pavement characteristics, and typical hazard patterns before the vehicle reaches those locations. This advance preparation allows the system to anticipate road conditions and adjust its braking strategy proactively rather than reactively, improving reliability in scenarios that may not be immediately apparent from sensor data alone.
3Device complexity
If the autonomous emergency braking system applies the same braking strategy for all targets, then the control logic remains simple, but it cannot provide sensitive braking for priority targets in child protection zones
Solution Approach 1:
The patent applies local quality by implementing differentiated braking strategies for different target types and locations. The system identifies priority targets (such as children in protection zones) and applies enhanced braking responses specifically to those cases, while maintaining standard braking for ordinary targets. This creates localized adjustments in control behavior based on target characteristics and environmental context.
Solution Approach 2:
The patent segments the control logic into multiple decision layers: first identifying target type and location, then determining the appropriate braking strategy based on that classification. The system divides the braking control into different modes (standard braking, sensitive braking, emergency braking) and selects the appropriate mode based on the detected scenario, allowing for nuanced responses to different situations.
Data Source
AI summary
In an autonomous emergency braking method based on map data of the present disclosure, warning and braking may be performed based on different standards depending on a pavement condition of the road and a braking time point may be turned according to a road pavement condition.In addition, the present disclosure enables a sensitive operation and filtering exception processing for a target that occurs frequently or requires additional attention in driving road conditions.