Odometry-Based Driver Assistance Without External Data
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Solution Overview
Problem
Existing driver assistance systems rely on complex and unreliable external data sources, requiring satellite or internet connections and user interaction, limiting their functionality and operability in various traffic situations and environments.
Innovation Solution
A method utilizing odometry sensors to record and recognize vehicle movement patterns, allowing for the automatic or suggested activation of vehicle functions without user intervention, using self-learning functional logic that operates independently of external data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assistance systems use external data sources (satellite, internet, navigation systems), then the system can provide situation-dependent control of vehicle functions, but the system becomes unreliable when external signals are interrupted (e.g., in tunnels or underground garages) and requires complex special equipment
Solution Approach 1:
The patent introduces odometry sensors as an intermediary data source that provides reliable position and movement information without requiring external satellite or internet connections. These sensors measure vehicle movement directly, serving as a mediator between the driver assistance system and the environment, ensuring continuous operation even when external data sources are unavailable.
Solution Approach 2:
The system uses the vehicle's own movement data captured by odometry sensors to determine when to activate vehicle functions, rather than relying on external navigation systems. The vehicle essentially serves itself by using its own movement patterns and position information to trigger appropriate functions automatically.
2Ease of operation
If the system requires user interaction to activate learning mode or define functions, then the system can be customized to user preferences, but the ease of operation decreases and requires additional user input
Solution Approach 1:
The system performs preliminary learning of the driver's preferences and behavior patterns automatically during normal operation, without requiring explicit user programming. The learning process occurs in advance and continuously, storing preferences that are then automatically applied when similar situations arise, eliminating the need for manual customization while maintaining personalization.
Solution Approach 2:
The system incorporates feedback mechanisms where the learned preferences and activation patterns are continuously refined based on actual usage. The system monitors whether automatic activations align with driver expectations and adjusts its learning accordingly, creating a closed-loop system that improves ease of operation while adapting to individual user preferences over time.
Data Source
AI summary
A method provides driver assistance in a vehicle. The method records at least one movement pattern of a vehicle together with activated vehicle functions, wherein the movement pattern is created via odometry sensors. The method provides the respective vehicle function on the basis of detection of at least one part of the movement pattern previously recorded during a journey of the vehicle.