Adaptive Driver Assistance via Sensor Probability Estimation
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Solution Overview
Problem
Existing driver assistance systems face challenges in accurately responding to short-term environmental changes and varying quality of electronic horizon information, leading to potential risks such as steering into pedestrians or failing to detect obstacles, particularly in diverse geographical areas.
Innovation Solution
A method and device that utilize a combination of sensors like cameras, radar, and lidar to detect environmental features and estimate probabilities of criteria like pedestrian presence, allowing for adaptive calibration and configuration of driver assistance functions, such as hands-off driving and ACC stop-and-go, to ensure safer operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electronic horizon information is used to adapt driver assistance functions, then the system can make assumptions about pedestrian probability in certain areas, but the system does not respond to short-term environmental changes and has varying quality and reliability across different geographical areas
Solution Approach 1:
The system dynamically adapts driver assistance functions by continuously detecting current environmental features (pedestrians, vehicles, roadworks, traffic lights) and adjusting function availability in real-time based on detected conditions, rather than relying on static electronic horizon data. This allows the system to respond to short-term changes while maintaining reliability across diverse geographical areas.
Solution Approach 2:
The system uses sensor feedback (cameras, radar, lidar) to continuously monitor the environment and adjust driver assistance function availability accordingly. The detection unit provides real-time feedback about environmental features, enabling the system to adapt to changing conditions and maintain reliable operation in diverse geographical areas without depending on electronic horizon information quality.
2Reliability
If electronic horizon system is used to provide environmental information, then assumptions about pedestrian probability can be made, but additional costs are incurred and quality and reliability differ for different areas
Solution Approach 1:
The system uses the vehicle's own sensors (cameras, radar, lidar) to detect environmental features and determine function availability, rather than relying on external electronic horizon systems. This self-service approach eliminates additional costs while maintaining reliable environmental information through direct sensor detection of pedestrians, vehicles, roadworks, and traffic lights.
Solution Approach 2:
Instead of using electronic horizon data that copies environmental information from external sources with varying quality, the system directly detects environmental features using onboard sensors, creating accurate real-time copies of the actual environment. This provides reliable information without the geographical quality variations and additional costs of electronic horizon systems.
3Device complexity
If driver assistance functions operate without environmental adaptation, then system complexity is reduced, but risks increase such as steering into pedestrians or failing to detect obstacles
Solution Approach 1:
The system segments the driver assistance functionality into multiple independent functions (steering assistance, ACC stop-and-go, lane keeping) and adapts each function's availability separately based on detected environmental features. This segmentation allows targeted adaptation that reduces safety risks for specific functions without requiring complex system-wide changes, maintaining manageable complexity while improving safety.
Solution Approach 2:
The system performs preliminary detection of environmental features (pedestrians, vehicles, roadworks, traffic lights) and pre-adapts driver assistance function availability before potential hazards occur. By detecting conditions in advance and adjusting function availability proactively, the system prevents safety risks rather than reacting after problems arise, reducing harmful factors without requiring overly complex real-time intervention systems.
Data Source
AI summary
A method is disclosed to operate a motor vehicle using a driver assistance system. The driver assistance system includes, for at least one driver assistance system function, at least one criterion relating to a vehicle environment. The at least one criterion is defined for an adaptation of the driver assistance system function, a number of features of the environment of the vehicle are detected, a probability of the occurrence of at least one criterion is estimated on the basis of a combination of the detected features, and the driver assistance system function is adapted on the basis of the estimated probability.