Ribbon model based path tracking method for autonomous ground vehicles

Qing-yang Chen , Zhen-ping Sun , Da-xue Liu , Xiao-hui Li

Journal of Central South University ›› 2014, Vol. 21 ›› Issue (5) : 1816 -1826.

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Journal of Central South University ›› 2014, Vol. 21 ›› Issue (5) : 1816 -1826. DOI: 10.1007/s11771-014-2127-9
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Ribbon model based path tracking method for autonomous ground vehicles

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Abstract

To resolve the path tracking problem of autonomous ground vehicles, an analysis of existing path tracking methods was carried out and an important conclusion was got. The vehicle-road model is crucial for path following. Based on the conclusion, a new vehicle-road model named “ribbon model” was constructed with consideration of road width and vehicle geometry structure. A new vehicle-road evaluation algorithm was proposed based on this model, and a new path tracking controller including a steering controller and a speed controller was designed. The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller. To verify the performance of the novel method, simulation and real vehicle experiments were carried out. Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible, so it can adjust the control strategy, such as safety, amenity, and rapidity criteria autonomously according to the road situation. This is important for the controller to adapt to different kinds of environments, and can improve the performance of autonomous ground vehicles significantly.

Keywords

autonomous ground vehicle / path tracking / ribbon model

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Qing-yang Chen, Zhen-ping Sun, Da-xue Liu, Xiao-hui Li. Ribbon model based path tracking method for autonomous ground vehicles. Journal of Central South University, 2014, 21(5): 1816-1826 DOI:10.1007/s11771-014-2127-9

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References

[1]

SniderJ MAutomatic steering methods for autonomous automobile path tracking [R], 2009, Pittsburgh, PA, Robotics Institute, Carnegie Mellon University

[2]

FentonR, MayhanR. Automated highway studies at the Ohio state university-An overview [J]. IEEE Transaction on Vehicular Technology, 1991, 40(1): 100-113

[3]

MacadamC C. An optimal preview control for linear systems [J]. Journal of Dynamical System, Measurement, Control, 1980, 102: 188-190

[4]

MacadamC C. Application of an optimal preview control for simulation of closed-loop automobile driving [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1981, 11: 393-399

[5]

ShladoverS, DesoerC, HedrickJ, TomizukaM, WalrandJ, ZhangW B, McmahonD H, PengH, SheikholeslamS, MckeownN. Automatic vehicle control developments in the PATH program [J]. IEEE Transaction on Vehicular Technology, 1991, 40(1): 114-130

[6]

SalvucciD D, GrayR. A two-point visual control model of steering [J]. Perception, 2004, 33: 1233-1248

[7]

MarinoR, ScalziS, NettoM. Nested PID steering control for lane keeping in autonomous vehicles [J]. Control Engineering Practice, 2011, 19(12): 1459-1467

[8]

GaoF-d, PanC-y, HanY-y, ZhangXiang. Nonlinear trajectory tracking control of a new autonomous underwater vehicle in complex sea conditions [J]. Journal of Central South University, 2012, 19: 1859-1868

[9]

FernandezL D, MilanesV, ParraA I, GavilanM, GarciaD I, PerezJ, SoteloM A. Autonomous pedestrian collision avoidance using a fuzzy steering controller [J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12: 390-401

[10]

PerezJ, MilanesV, OnievaE. Cascade architecture for lateral control in autonomous vehicles [J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(1): 73-82

[11]

OhS Y, LeeJ H, ChoiD H. A new reinforcement learning vehicle control architecture for vision-based road following [J]. IEEE Transactions on Vehicular Technology, 2000, 49(3): 997-1005

[12]

RaffoG V, GomesG K, Normey-ricoJ E, KelberC R, BeckerL B. A predictive controller for autonomous vehicle path tracking [J]. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(1): 92-102

[13]

HowardT M, GreenC J, KellyA. Receding horizon model-predictive control for mobile robot navigation of intricate paths [J]. Field and Service Robotics, Springer Tracts in Advanced Robotics, 2010, 62: 69-78

[14]

KimB A, LeeY O, LeeS H, ChungC. MPC-based active steering control using multi-rate kaiman filter for autonomous vehicle systems with vision [J]. Transactions of the Korean Institute of Electrical Engineers, 2012, 61(5): 735-743

[15]

OnievaE, NaranjoJ E, MilanesV, AlonsoJ, GarciaR, PerezJ. Automatic lateral control for unmanned vehicles via genetic algorithms [J]. Applied Soft Computing Journal, 2011, 11(1): 1303-1309

[16]

GuoJ-h, HuP, LiL-h, WangR-ben. Design of automatic steering controller for trajectory tracking of unmanned vehicles using genetic algorithms [J]. IEEE Transactions on Vehicular Technology, 2012, 61(7): 2913-2924

[17]

NejatP H, MahboobiS H, AlastyA. Optimum synthesis of fuzzy logic controller for trajectory tracking by differential evolution [J]. Scientia Iranica, 2011, 18(2): 261-267

[18]

LucaA D, OrioloG, SamsonC. Feedback control of a nonholonomic car-like robot [J]. Robot Motion Planning and Control, Lecture Notes in Control and Information Sciences, 1998, 229: 171-249

[19]

ThrunS, MontemerloM, DahlkampH, StavensD, AronA, DiebelJ, FongP, GaleJ, HalpennyM, HoffmannG, LauK, OakleyC, PalatucciM, PrattV, StangP, StrohbandS, DupontC, JendrossekL E, KoelenC, MarkeyC, RummelC, VanN J, JensenE, AlessandriniP, BradskiG, DaviesB, EttingerS, KaehlerA, NefianA, MahoneyP. Stanley: The robot that won the DARPA grand challenge [J]. Journal of Field Robotics, 2006, 23(9): 661-692

[20]

HoffmannG M, TomlinC J, MontemerloM, ThrunS. Autonomous automobile trajectory tracking for off-road driving: controller design, experimental validation and racing [C]. Proceedings of the American Control Conference. New York, United States, 20072296-2301

[21]

UrmsonC, AnhaltJ, BagnellD, BakerC, BittnerR, ClarkM N, DolanJ, DugginsD, GalataliT, GeyerC, GittlemanM, HarbaughS, HebertM, HowardT M, KolskiS, KellyA, LikhachevM, McnaughtonM, MillerN, PetersonK, PilnickB, RajkumarR, RybskiP, SaleskyB, SeoY W, SinghS, SniderJ, StentzA, WhittakerW, WolkowickiZ, ZiglarJ, BaeH, BrownT, DemitrishD, LitkouhiB, NickolaouJ, SadekarV, ZhangW-d, StrubleJ, TaylorM, DarmsM, FergusonD. Autonomous driving in urban environments: Boss and the urban challenge [J]. Journal of Field Robotics, 2008, 25(8): 425-466

[22]

SharpR S. Driver steering control and a new perspective on car handling qualities [J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2005, 219(10): 1041-1051

[23]

HowardT M, KnepperR A, KellyA. Constrained optimization Path following of wheeled robots in natural terrain [J]. Springer Tracts in Advanced Robotics, 2008, 39: 343-352

[24]

AiH-z, ZhangBo. Path planning for mobile robots [J]. Pattern Recognition and Artificial Intelligence, 1991, 4(1): 51-57

[25]

GuoK-huiVehicle handling dynamics [M], 1991, Changchun, Jilin Science and Technology Press: 31-32

[26]

WillumeitH PVehicle dynamics: simulation and methods [M], 1998, Beijing, Beijing Institute of Technology Press: 127-130

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