Feasible And Optimal Trajectories Generation for Autonomous Driving Vehicles

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F23%3A00011190" target="_blank" >RIV/46747885:24220/23:00011190 - isvavai.cz</a>

Alternative codes found

RIV/46747885:24620/23:00011190

Result on the web

<a href="https://www.actapress.com/Abstract.aspx?paperId=55380" target="_blank" >https://www.actapress.com/Abstract.aspx?paperId=55380</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2316/J.2023.201-0286" target="_blank" >10.2316/J.2023.201-0286</a>

Result language

angličtina

Original language name

Feasible And Optimal Trajectories Generation for Autonomous Driving Vehicles

Original language description

Real-time feasible and optimal trajectory generation subject to the vehicle physical constraints, the surrounding obstacles, and the environmental conditions is one of the most important parts of autonomous driving vehicles. This study presents three smooth and fast trajectories generations for autonomous driving vehicles subject to the vehicle physical constraints on speed, acceleration, and steering angle as well as the hard physical limitations of the vehicle speed and the vehicle steering angle. In vehicle safety dynamics, the vehicle steering angle and the vehicle speed are always related in a strict function depending on the surrounding obstacles and the environmental conditions. Three different methods for vehicle feasible trajectory planning generation are introduced and compared. The optimal feasible trajectory is selected based on the smoother curve, the shorter distance, and the smaller tracking errors. Results from this study can be used for online autonomous driving vehicle and for autonomous parking systems. This study provides fundamental mathematical algorithms to online map out optimal feasible paths for ground autonomous vehicles.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20205 - Automation and control systems

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mechatronic systems and control

ISSN

2561-1771

e-ISSN

—

Volume of the periodical

51

Issue of the periodical within the volume

1

Country of publishing house

CA - CANADA

Number of pages

14

Pages from-to

11-24

UT code for WoS article

001021517200002

EID of the result in the Scopus database

2-s2.0-85153387567