Vehicle Self-Localization Using Direct Wheel Speed and Yaw Estimation
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Solution Overview
Problem
Conventional driving assistance systems for vehicles face inaccuracies in self-location at low speeds due to insufficient measuring accuracy from wheel impulse counters, leading to imprecise vehicle positioning and orientation, especially during parking.
Innovation Solution
The method involves directly measuring and evaluating instantaneous circumferential wheel speed to determine vehicle speed and yaw rate, using a Moore pseudoinverse to optimize measurements, and compensating for time delays through temporal extrapolation, integrating acceleration data, and applying Bayes and Kalman filters for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wheel impulse counters are used for measuring wheel speed, then the system structure remains simple, but measurement precision deteriorates at low speeds
Solution Approach 1:
The patent replaces the mechanical wheel impulse counter system with an electronic sensor system that directly measures circumferential wheel speed. This substitution enables continuous analog measurement rather than discrete pulse counting, thereby achieving sufficient measurement accuracy at low speeds while maintaining system simplicity through integration with existing vehicle sensors.
2Measurement precision
If circumferential wheel speed sensors are used, then measurement precision improves, but time delay in measurement data increases
Solution Approach 1:
The patent applies temporal extrapolation to predict current wheel speed values based on previously measured values and known vehicle dynamics characteristics. This preliminary action compensates for the inherent time delay in sensor measurements, providing up-to-date speed information for real-time driving assistance operations without requiring instantaneous sensor response.
3Productivity
If temporal extrapolation is applied to compensate time delay, then real-time capability improves, but calculation complexity increases
Solution Approach 1:
The patent transforms the temporal extrapolation problem into a parameter estimation problem by utilizing known vehicle dynamic parameters (mass, moment of inertia, friction coefficients) to predict wheel speed evolution. This approach simplifies the calculation by using pre-characterized vehicle parameters rather than requiring complex real-time differential equation solving, thereby maintaining real-time capability without excessive computational complexity.
4Productivity
If Moore pseudoinversion is used for determining vehicle state, then calculation efficiency improves, but numerical stability may deteriorate
Solution Approach 1:
The patent applies regularization techniques to the Moore pseudoinversion calculation to prevent numerical instability. By adding a small regularization parameter to the diagonal elements of the matrix being inverted, the system cushions against potential singularity or near-singularity conditions, ensuring stable numerical solutions while maintaining calculation efficiency for real-time vehicle state determination.
Data Source
AI summary
A driving assistance method for a vehicle. An instantaneous speed of the vehicle and an instantaneous yaw rate of the vehicle are ascertained. An operation of self-locating of the vehicle is carried out on the basis of the ascertained, instantaneous speed and the ascertained, instantaneous yaw rate of the vehicle. To that end, an instantaneous circumferential wheel speed of one or more wheels of the vehicle is directly measured, evaluated and taken as a basis of the determination of the instantaneous speed and the instantaneous yaw rate of the vehicle.