Adaptive Vehicle Model Driving Control for Load Changes
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Solution Overview
Problem
Conventional travel control systems fail to accurately calculate a steering angle for vehicles when the weight or center-of-mass position changes due to varying occupancy or load, leading to deviations from the target track.
Innovation Solution
A driving control device that acquires real-time vehicle parameters, generates a vehicle model, and calculates a corrected steering angle using an evaluation function to minimize noise, enabling precise track following.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed vehicle model with predetermined weight and center-of-mass position is used, then the device complexity is reduced, but the manufacturing precision of steering angle calculation deteriorates when vehicle load changes
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed vehicle model to a dynamic model that is periodically updated with current vehicle parameters. The control device acquires real-time weight and center-of-mass position data and regenerates the vehicle model accordingly, allowing the system to adapt to changing load conditions while maintaining calculation precision.
Solution Approach 2:
The patent implements parameter changes by updating key vehicle parameters (weight, center-of-mass position) in the vehicle model based on actual measurements. This allows the steering angle calculation to reflect current vehicle conditions, resolving the precision deterioration issue when load changes occur.
2Manufacturing precision
If real-time vehicle parameters are acquired and vehicle model is periodically updated, then the steering angle calculation precision is improved, but the device complexity and measurement requirements increase
Solution Approach 1:
The patent applies self-service by enabling the control device to autonomously acquire its own vehicle parameter data and perform model updates without external intervention. The system uses built-in sensors and processors to automatically regenerate the vehicle model, reducing the need for additional complex external systems.
Solution Approach 2:
The patent implements feedback by continuously monitoring actual vehicle parameters and using this information to update the vehicle model. This closed-loop approach ensures the steering angle calculation remains accurate by incorporating real-time vehicle state information back into the control system.
3Device complexity
If noise in lateral deviation and azimuth deviation is not corrected, then the device complexity is reduced, but the travel control precision deteriorates
Solution Approach 1:
The patent applies taking out by extracting and removing noise components from the lateral deviation and azimuth deviation measurements. The system identifies and separates noise from actual vehicle state data, using only the clean signals for control calculations, thereby improving track following precision without requiring complex noise filtering hardware.
Data Source
AI summary
A driving control device has: a generating section that generates a first vehicle model representing a relationship among the longitudinal speed of the vehicle, the lateral speed of the vehicle, the weight, the center-of-mass position of the vehicle, the steering angle, the lateral deviation of the vehicle, the azimuth deviation and the curvature of a road surface where the vehicle is traveling; calculating section that inputs the lateral deviation, the azimuth deviation and the curvature to an evaluation function corresponding to the first vehicle model corresponding to the longitudinal speed, the lateral speed, the weight and the center-of-mass position, and calculates a corrected steering angle for minimizing or maximizing an output value of the evaluation function; and a travel control section that causes the vehicle to travel on a basis of the corrected steering angle.