Autonomous driving vehicle traveling status information estimation method

Abstract

The invention discloses an autonomous driving vehicle traveling status information estimation method. The method comprises the steps that 1, a vehicle traveling status modular estimator is designed based on a simplified vehicle model and used for estimating other traveling status information of a vehicle according to measurement signals of a vehicle sensor, wherein the first step comprises the substeps that a longitudinal tire force observer is designed and used for estimating the longitudinal tire force of the vehicle, a lateral tire force estimator is designed and used for calculating the lateral tire force of the vehicle, a vehicle speed nonlinear full-dimensional status estimator is designed and used for estimating the longitudinal speed and the lateral speed of the vehicle, and the designed estimators designed in the substeps are integrated to obtain the vehicle traveling status modular estimator; 2, the signals measured by the sensor of the vehicle are input into the vehicle traveling status modular estimator obtained in the first step, and the estimation information of the tire force and speed of the vehicle is estimated through the vehicle traveling status modular estimator.

Description

technical field [0001] The invention relates to a method for estimating vehicle state information, in particular to a method for estimating driving state information of an autonomous driving vehicle, which can be used not only for theoretical research on estimating vehicle state information, but also for various working conditions of actual vehicle operation. Background technique [0002] Aiming at the problems of traffic congestion and accidents, the development of automobile control is becoming more and more information-based and intelligent, and autonomous driving vehicles are the product of the development of intelligent transportation networks. Because the electronic control system of automobiles, especially autonomous driving vehicles, mostly implements corresponding control logic according to the driving state of the vehicle. Vehicle acceleration, deceleration, cruise and steering control all depend on the magnitude of the driving friction between the road and the tir...

AI Technical Summary

Problems solved by technology

Vehicle acceleration, deceleration, cruise and steering control all depend on the magnitude of the driving friction between the road and the tires and the driving speed of the vehicle. In order to improve the active safety of the vehicle, the tire force and speed information of the vehicle can be obtained accurately and in real time It is an important basis for self-driving vehicles to realize motion control, complete specific route driving and early warning of dangerous situations, but the above information cannot be directly measured by sensors. Even if it can be measured, usually measuring instruments have problems such as large measurement errors and high production costs

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