A Review of Estimation for Vehicle Tire-Road Interactions Toward Automated Driving

被引：80

作者：

Guo, Hongyan ^{[1
]}

Yin, Zhenyu ^{[1
]}

Cao, Dongpu ^{[2
]}

Chen, Hong ^{[1
]}

Lv, Chen ^{[3
]}

机构：

[1] Jilin Univ, Dept Control Sci & Engn, State Key Lab Automot Simulat & Control, Campus NanLing, Changchun 130025, Jilin, Peoples R China

[2] Univ Waterloo, Mech & Mechatron Engn Dept, Waterloo, ON N2L 3G1, Canada

[3] Cranfield Univ, Dept Automot Engn, Cranfield MK43 0AL, Beds, England

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2019年 / 49卷 / 01期

关键词：

Automated driving; extended Kalman filter (EKF); road bank angle estimation; sensor configuration; tire-road interaction estimation; vehicle dynamics model; MODEL-PREDICTIVE CONTROL; EXTENDED KALMAN FILTER; REAL-TIME ESTIMATION; INTELLIGENT TRANSPORTATION SYSTEMS; FRICTION-COEFFICIENT; SIDESLIP ANGLE; STATE ESTIMATION; VELOCITY ESTIMATION; NONLINEAR OBSERVER; FORCES ESTIMATION;

D O I：

10.1109/TSMC.2018.2819500

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes an extensive overview of the tire-road interaction estimation issue as it relates to automated driving from the prospectives of sensor configuration, tire modeling, and estimation approaches. The tire-road interactions needed for estimation are first determined and classified. Then, the sensor configuration schemes of different types of tire-road interactions are presented and analyzed. The following introduces various types of tire models and provides the limitations and advantages of different estimation approaches based on categorizing and summarizing those techniques. Moreover, some interesting perspectives for future research are listed based on the extensive experience of the authors.

引用

页码：14 / 30

页数：17

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