Driver Assistance Risk Control Under Weather and Backlight
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Solution Overview
Problem
Existing driver assistance systems fail to adequately consider natural phenomena such as weather and backlight when assessing collision risks, leading to inappropriate avoidance maneuvers that can annoy or anxiety drivers.
Innovation Solution
A driver assistance system that extracts risk target information and natural phenomenon information to determine a risk parameter, which is used to calculate a manipulated variable for actuator control, thereby reducing collision risks while minimizing driver annoyance and anxiety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the avoidance preparation operation is excessively performed to reduce collision risk, then the collision risk is reduced, but the driver feels annoyed
Solution Approach 1:
The system dynamically adjusts the risk parameter by incorporating natural phenomenon information (weather conditions, backlight) to modify the avoidance preparation operation threshold. When adverse natural phenomena are detected, the system lowers the threshold for triggering avoidance operations, enabling more frequent interventions to compensate for reduced visibility or increased pedestrian unpredictability, thereby resolving the contradiction between excessive avoidance and collision risk reduction
Solution Approach 2:
The system continuously monitors natural phenomenon conditions and adjusts the avoidance preparation operation in real-time based on this feedback. By integrating environmental sensor data with risk assessment, the system adapts its behavior to current conditions, preventing both excessive avoidance in safe conditions and insufficient avoidance in hazardous conditions
2Ease of operation
If the avoidance preparation operation is not performed to avoid driver annoyance, then driver comfort is improved, but the driver may feel anxious due to increased collision risk
Solution Approach 1:
The system modifies the risk assessment parameters by incorporating natural phenomenon information, which dynamically adjusts when avoidance preparation operations are triggered. In adverse conditions like rain or backlight, the system becomes more proactive, reducing driver anxiety by ensuring safety interventions occur when needed, while in normal conditions it maintains comfort by avoiding unnecessary interventions
Solution Approach 2:
The system performs preliminary risk assessment by detecting natural phenomena before collisions occur. By anticipating hazardous conditions and preparing avoidance operations in advance, the system ensures safety interventions are ready when needed, reducing driver anxiety without causing unnecessary interruptions during safe driving
3Device complexity
If natural phenomenon information is not considered in risk assessment, then the system complexity is reduced, but the collision risk assessment accuracy is insufficient
Solution Approach 1:
The system uses a multi-functional approach where existing sensors (cameras, weather sensors) serve dual purposes: their primary functions for general driving assistance and an additional function for detecting natural phenomena that affect collision risk. This integrates environmental awareness into the existing risk assessment framework without requiring completely separate detection systems, thus managing complexity while improving accuracy
Data Source
AI summary
The driver assistance system of the present disclosure is configured to execute processing comprising following four processes. The first process is to extract risk target information related to a risk target that causes a collision risk to a vehicle from information related to a peripheral situation of the vehicle. The second process is to obtain natural phenomenon information related to a natural phenomenon that affects the risk target. The third process is to determine a risk parameter that quantifies the collision risk based on the risk target information and the natural phenomenon information. The fourth process is to determine a manipulated variable of an actuator for controlling movement of the vehicle to reduce the collision risk based on the risk parameter.