Vehicle Spinout Detection Using Lateral Factor Calculation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle spinout detection systems face challenges in accurately calculating lateral velocity due to integration errors and the inability to measure lateral acceleration directly, especially during low visibility conditions, and are hindered by the cost and reliability issues of using additional sensors.
Innovation Solution
A method and system that calculate a lateral factor and spinout factor using past values and existing vehicle signals, such as steering wheel angle, yaw rate, and longitudinal velocity, to generate a warning signal when the spinout factor exceeds a threshold, without requiring additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated measuring devices such as optical sensors and GPS are used to measure vehicle velocities directly, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system uses existing vehicle sensors (wheel speed sensors, steering angle sensors, yaw rate sensors) that are already installed on the vehicle to calculate lateral and longitudinal velocities through mathematical algorithms. This self-service approach eliminates the need for additional dedicated measuring devices while maintaining measurement capability.
Solution Approach 2:
The patent replaces direct mechanical/optical measurement systems with a computational approach using mathematical models and algorithms that process signals from existing sensors to derive velocity information indirectly through calculation rather than direct measurement.
2Measurement precision
If lateral acceleration is measured directly with dedicated sensors, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system calculates lateral acceleration indirectly using mathematical relationships between existing sensor measurements (steering angle, yaw rate, longitudinal velocity) rather than using dedicated lateral acceleration sensors, thereby avoiding additional hardware complexity.
Solution Approach 2:
The patent introduces mathematical algorithms and computational models as intermediaries that transform measurements from existing sensors into estimates of lateral acceleration, serving as a virtual mediator between available sensor data and the desired measurement.
3Ease of operation
If mathematical integration of lateral acceleration is used to calculate lateral velocity, then ease of operation is improved, but reliability deteriorates due to integration errors
Solution Approach 1:
The system continuously monitors the calculated lateral velocity and spinout factor, comparing them against threshold values and using this feedback to trigger warnings or reset calculations when spinout conditions are detected, thereby maintaining reliability despite integration errors accumulating over time.
Solution Approach 2:
The patent implements periodic resetting or recalibration of the integration process based on detected spinout events or threshold exceedances, preventing error accumulation from compromising the system's reliability over extended operation periods.
Data Source
AI summary
A method for vehicle spinout detection is described. The method includes monitoring a set of conditions. If the conditions meet a set of criteria, the method calculates a lateral factor, employing one or more past values of the lateral factor. The lateral factor indicates the vehicle's lateral velocity. Then, a spinout factor is computed based on the calculated lateral factor. The spinout factor indicates the difference between the direction of vehicle travel and the direction the vehicle is heading. If the spinout factor is above a predefined threshold value, the method generates a warning signal. A system for vehicle spinout detection is also described.