Journal ArticleDOI
Modelling and Control Strategies in Path Tracking Control for Autonomous Ground Vehicles: A Review of State of the Art and Challenges
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TLDR
Critical review of the basic vehicle model usually used; the control strategies usually employed in path tracking control, and the performance criteria used to evaluate the controller’s performance are provided.Abstract:
Autonomous vehicle field of study has seen considerable researches within three decades. In the last decade particularly, interests in this field has undergone tremendous improvement. One of the main aspects in autonomous vehicle is the path tracking control, focusing on the vehicle control in lateral and longitudinal direction in order to follow a specified path or trajectory. In this paper, path tracking control is reviewed in terms of the basic vehicle model usually used; the control strategies usually employed in path tracking control, and the performance criteria used to evaluate the controller's performance. Vehicle model is categorised into several types depending on its linearity and the type of behaviour it simulates, while path tracking control is categorised depending on its approach. This paper provides critical review of each of these aspects in terms of its usage and disadvantages/advantages. Each aspect is summarised for better overall understanding. Based on the critical reviews, main challenges in the field of path tracking control is identified and future research direction is proposed. Several promising advancement is proposed with the main prospect is focused on adaptive geometric controller developed on a nonlinear vehicle model and tested with hardware-in-the-loop (HIL). It is hoped that this review can be treated as preliminary insight into the choice of controllers in path tracking control development for an autonomous ground vehicle.read more
Citations
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Binary integer modeling of the traffic flow optimization problem, in the case of an autonomous transportation system
Gábor Pauer,Árpád Török +1 more
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Multiple objects tracking by a highly decisive three-frame differencing-combined-background subtraction method with GMPFM-GMPHD filters and VGG16-LSTM classifier
TL;DR: A highly efficient and fast multi-object tracking method using three-frame differencing-combined-background subtraction (TFDCBS)-coupled-automatic and fast histogram-entropy-based thresholding (HEBT) method together with GMPFM-GMPHD filters and VGG16-LSTM classifier is developed.
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Robust Control Framework for Lateral Dynamics of Autonomous Vehicle Using Barrier Lyapunov Function
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Human-Machine Shared Driving: Challenges and Future Directions
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A Review on Driving Control Issues for Smart Electric Vehicles
Tansu S. Haque,Md. Hafizur Rahman,Md. Robiul Islam,Md. Abdur Razzak,Faisal R. Badal,Md. Hafiz Ahamed,Sumaya I. Moyeen,Sajal K. Das,Md. Firoz Ali,Zinat Tasneem,Dip Kumar Saha,Ripon K. Chakrabortty,Michael J. Ryan +12 more
TL;DR: In this paper, the authors present a review of driving control systems and algorithms for smart EVs, including the advanced driving assistant system, implementation of sensors, vehicle dynamics, and control algorithms.
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Stanley: The Robot that Won the DARPA Grand Challenge
Sebastian Thrun,Michael Montemerlo,Hendrik Dahlkamp,David Stavens,Andrei Aron,James Diebel,Philip Fong,John Gale,Morgan Halpenny,Gabriel M. Hoffmann,Kenny Lau,Celia M. Oakley,Mark Palatucci,Vaughan R. Pratt,Pascal Stang,Sven Strohband,Cedric Dupont,Lars-Erik Jendrossek,Christian Koelen,Charles Markey,Carlo Rummel,Joe van Niekerk,Eric Jensen,Philippe Alessandrini,Gary Bradski,Bob Davies,Scott M. Ettinger,Adrian Kaehler,Ara V. Nefian,Pamela Mahoney +29 more
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A stable tracking control method for an autonomous mobile robot
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Predictive Active Steering Control for Autonomous Vehicle Systems
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