Forward Collision Warning Using Adaptive Braking Distance
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Solution Overview
Problem
Conventional forward collision avoidance systems fail to accurately calculate braking distances based on vehicle conditions and driving environments, leading to ineffective collision warnings and potential collisions, and generate unnecessary warnings that desensitize drivers.
Innovation Solution
An apparatus and method that calculates braking distance by considering the mass of the host vehicle, road surface friction, and driver braking tendencies using sensors and an artificial neural network model to determine appropriate collision warnings and autonomous emergency braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional uniform collision risk measurement rules are used, then the system is simple to implement, but it cannot accurately reflect various risk situations and leads to ineffective collision warnings
Solution Approach 1:
The system dynamically changes multiple parameters including braking distance (based on vehicle mass and road friction), safe distance (based on relative speed), and collision risk level (based on TTC and DTC). This allows the collision warning system to adapt to various driving conditions and accurately reflect different risk situations, resolving the contradiction between measurement precision and system complexity.
2Reliability
If conventional collision warning systems issue warnings based on fixed rules, then the system is easy to operate, but drivers become insensitive to warnings or feel uncomfortable when warnings are issued even during normal driving
Solution Approach 1:
The system dynamically adjusts warning issuance based on real-time calculation of braking distance, safe distance, and collision risk level. Instead of using fixed rules, the system adapts to current driving conditions and driver behavior patterns, ensuring warnings are issued only when truly necessary. This maintains warning effectiveness while improving driver acceptance by reducing false alarms.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring driving conditions, vehicle parameters, and driver responses. This allows the system to learn from driver behavior and adjust warning thresholds accordingly, improving both reliability and driver acceptance over time.
3Measurement precision
If the braking distance is not accurately calculated considering vehicle conditions and road surface, then the system is simple to implement, but collision cannot be avoided when brakes are suddenly applied
Solution Approach 1:
The system calculates braking distance by dynamically considering multiple parameters including vehicle mass, road surface friction coefficient, and environmental conditions. This accurate calculation is essential for determining whether collision can be avoided when brakes are suddenly applied, resolving the contradiction between measurement precision and calculation complexity.
Data Source
AI summary
An apparatus for forward collision avoidance of a host vehicle includes a first sensor configured to detect a front of a vehicle; a second sensor configured to a speed of the host vehicle; and a controller that is communicatively connected to the first sensor and the second sensor and is configured to generate a collision warning based on a braking distance of the host vehicle and a braking tendency of a driver of the host vehicle.