A Disturbance Activation Approach to Collision Avoidance Autonomous Driving
Result description
A very challenging control task for operating autonomous vehicles is to avoid collision with approaching pedestrians or vehicles while tracking a reference trajectory. This paper proposes a Linear-Quadratic Regulator (LQR)-based collision avoidance trajectory tracking controller for an autonomous driving scenario. In this approach, simply the control module activates a designed disturbance when there is a collision situation. A proper design of the disturbance causes the vehicle to prevent the collision and safely maneuver on the road. The asymptotic stability of this feedback LQR-based controller under an infinite horizon is shown. Simulation experiments are carried out to illustrate the performance of the proposed controller. (C) 2019 IEEE.
Keywords
trajectory trackingLinear-Quadratic Regulatordisturbancecollision avoidanceautonomous driving
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
A Disturbance Activation Approach to Collision Avoidance Autonomous Driving
Original language description
A very challenging control task for operating autonomous vehicles is to avoid collision with approaching pedestrians or vehicles while tracking a reference trajectory. This paper proposes a Linear-Quadratic Regulator (LQR)-based collision avoidance trajectory tracking controller for an autonomous driving scenario. In this approach, simply the control module activates a designed disturbance when there is a collision situation. A proper design of the disturbance causes the vehicle to prevent the collision and safely maneuver on the road. The asymptotic stability of this feedback LQR-based controller under an infinite horizon is shown. Simulation experiments are carried out to illustrate the performance of the proposed controller. (C) 2019 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
5th Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2019
ISBN
978-1-72815-350-6
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Shahrood
Event date
Dec 18, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000570801800029
Basic information
Result type
D - Article in proceedings
OECD FORD
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Year of implementation
2019