Vehicle Safe Speed Prediction Under Variable Road Friction
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Solution Overview
Problem
Current methods for determining safe vehicle speed at a future waypoint fail to account for changing environmental conditions, relying on constant maximum coefficient of friction and neglecting dynamic road conditions, which can lead to unstable driving situations and accidents.
Innovation Solution
A method that considers the probability distribution of the maximum coefficient of friction at both the current and future waypoints, using route information and environmental data to calculate a safe speed through statistical quantiles, enabling real-time adjustments and warnings or interventions to prevent excessive speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a constant maximum friction coefficient is assumed for speed calculation, then the calculation is simple, but the accuracy of safe speed determination deteriorates under changing environmental conditions
Solution Approach 1:
The patent applies dynamics by transitioning from a static, constant friction coefficient assumption to a dynamic model that continuously updates the friction coefficient based on real-time environmental conditions (temperature, humidity, road surface state). This allows the safe speed calculation to adapt to changing conditions while maintaining computational feasibility through predefined update triggers and parameter relationships.
Solution Approach 2:
The patent implements parameter changes by introducing multiple environmental parameters (temperature, humidity, road surface condition) that influence the friction coefficient. These parameters are monitored and used to dynamically adjust the friction coefficient value, thereby improving the accuracy of safe speed determination without requiring complete recalculation of the entire control system.
2Device complexity
If environmental conditions are not considered in speed determination, then the control system is simple, but the reliability of vehicle control deteriorates in extreme situations
Solution Approach 1:
The patent applies preliminary action by proactively monitoring environmental conditions and predicting friction coefficient changes before they critically affect vehicle control. The system preemptively adjusts speed recommendations and control parameters based on detected environmental trends, preventing unstable driving situations rather than reacting after problems occur.
Solution Approach 2:
The patent implements feedback by continuously monitoring environmental parameters (temperature, humidity, road surface state) and using this information to dynamically adjust the friction coefficient estimation and safe speed calculation. This closed-loop feedback mechanism ensures the control system adapts to changing conditions, maintaining reliability in extreme situations while avoiding unnecessary complexity through selective parameter monitoring.
3Device complexity
If the driver manually assesses road conditions, then the system is simple, but the response time to changing conditions is delayed
Solution Approach 1:
The patent applies self-service by enabling the vehicle's sensor system to automatically monitor environmental conditions (temperature, humidity, road surface state) and calculate safe speed parameters without driver intervention. The system serves itself by using its own sensors and processing capabilities to assess road conditions and adjust control parameters, eliminating the time delay associated with manual driver assessment while maintaining system simplicity through automated routines.
Data Source
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AI summary
The invention describes a method for determining a safe speed (v*) at a future way point (s*) of a vehicle which is moving along a route. In this step, at least one piece of route information (in particular curve bend κ) characterizing the course of the route is determined. In addition, a first probability distribution (Pges) of a friction coefficient (μ) at the current way point (s) and/or at the future way point (s*) of the vehicle is provided. A second probability distribution (Pv) of a vehicle speed (v) at the future way point (s*) is then determined from the at least one piece of route information (κ) and the first probability distribution (Pges). The safe speed (v*) is determined from the second probability distribution (Pv) by statistical analysis.