Vehicle Speed Proposal Using Real-Time Grip Potential Estimation
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Solution Overview
Problem
Current driving assistance systems fail to accurately estimate tire-road grip potential in real-time, especially in conditions with low grip levels, and are unable to account for complex driving maneuvers, leading to insufficient safety margins.
Innovation Solution
A method that estimates tire-road grip potential by determining influential parameters such as road texture, water depth, and tire conditions, using mathematical models and charts, and selects a secure driving style to propose an optimized speed for the driver, ensuring comfort and safety by interpolating speed profiles based on GPS location and predetermined routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If grip potential is estimated by stressing it up to half the maximum potential, then the grip potential can be determined, but the safety margin for the driver is insufficient
Solution Approach 1:
The system performs preliminary estimation of the maximum grip potential before actual driving maneuvers occur. By using measured parameters (road texture, water depth, temperature) and tyre features to calculate the grip number in advance, the system establishes a safety margin before the driver needs to react, rather than waiting to stress the grip potential during critical moments.
Solution Approach 2:
The invention introduces an intermediary computational model that processes multiple measured parameters (road grip number, sand patch depth, water depth, temperature, tyre features) to derive the maximum grip potential. This intermediary system acts as a mediator between raw sensor data and safety-critical speed recommendations, enabling accurate estimation without direct stress testing.
2Measurement precision
If vehicle equilibrium models and trajectory tracking hypotheses are used, then grip potential can be estimated, but the system cannot account for complex driving maneuvers and driver behavior
Solution Approach 1:
The system changes from using fixed trajectory tracking hypotheses to dynamically adjusting the grip number based on measured parameters. By continuously updating the grip number according to actual road conditions (water depth, texture, temperature) and tyre state, the system adapts to complex maneuvers without relying on predetermined cartographic trajectories that cannot capture real-world driving complexity.
3Measurement precision
If multiple parameters are measured and processed in real-time, then accurate grip potential estimation is achieved, but the computational complexity increases
Solution Approach 1:
The computational system is segmented into distinct functional modules: a measurement module that collects parameters (road texture, water depth, temperature, tyre features), a computation module that calculates the grip number using these parameters, and an application module that uses the grip number for speed recommendations. This segmentation allows each module to be optimized independently, reducing overall system complexity while maintaining measurement precision.
Data Source
AI summary
A method for proposing a driving speed for a driver at the steering wheel of a vehicle comprises the following steps: estimating the maximum available grip potential at a given instant between a tyre of the vehicle and the roadway on a predetermined upcoming route; determining, among a set of predetermined driving styles, secure styles for which the grip requirement on the predetermined route remains lower than the grip potential; selecting, among said secure styles, a secure comfortable style according to a driver profile; and determining, according to said secure comfortable style and to a location of the vehicle, a basic proposed driving speed on an upcoming section of route.