Simulation Validation of Three Nonlinear Model-Based Controllers in the Adaptive Cruise Control System

Shakouri, Payman; Czeczot, Jacek; Ordys, Andrzej

doi:10.1007/s10846-014-0128-4

Cited by 33 publications

(15 citation statements)

References 35 publications

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“…The work in Ref. [12] proposed longitudinal control based on a gain scheduling technique. In fact, for an internal combustion engine vehicle, the engine and characteristic of the transmission system are the key issues for vehicle control.…”

Section: Open Accessmentioning

confidence: 99%

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Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

Lin

Zhang

Zhao

et al. 2019

Chin. J. Mech. Eng.

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The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal-lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.

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Section: Open Accessmentioning

confidence: 99%

“…In most of the current literature, the trajectory tracking and velocity tracking are considered separately [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] and an automatic steering algorithm mainly solves the problem of trajectory tracking. Research shows that the realization of a steering strategy is largely affected by the…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

Lin

Zhang

Zhao

et al. 2019

Chin. J. Mech. Eng.

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“…The distance d min saf ety is minimal distance to maintain at full stop of both vehicles. The distance d v is defined by the constant time headway policy [18]:…”

Section: Fig 3 Accwsg Conceptmentioning

confidence: 99%

Efficient ACC with Stop&Go maneuvers for hybrid vehicle with online sub-optimal energy management

Abdrakhmanov

Adouane

2017

2017 11th International Workshop on Robot Motion and Control (RoMoCo)

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This paper presents an Adaptive Cruise Control with Stop&Go (ACCwSG) maneuvers aiming to improve the fuel economy of a Hybrid Electric Vehicle (HEV). Within the scope of the given subject, an optimal offline optimization, based on Dynamic Programming (DP), is proposed in this work, permitting to have simultaneous speed profile optimization and optimal power split strategy of a series-parallel hybrid bus. Afterwards, the basis of the offline optimal strategy has been adapted in order to deal online with the current road profile and driver velocity demand. The proposed online and suboptimal strategy uses mainly a Multi-Dimensional Database (MDD, which gives as output the speed profile and powersplit set-points) and an appropriate interpolation technique in order to cope with the current bus situations. The MDD is obtained based on offline DP, while using specific protocol which cover a large possible space state of the vehicle situations and their corresponding optimal set-points. The developed strategy finds its practical application in ACCwSG for a heavy urban bus, which is subject to frequent highly energy consuming starts and stops phases. The present work is conducted on a dedicated high-fidelity dynamical model of the hybrid bus that was developed on MATLAB/TruckMaker software. Several simulations were performed to prove the efficiency of the proposed navigation strategy.

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“…Many ACC researches have been done, with different control theories being applied, such as MPC [3] and Fuzzy [4]. Some papers also do a comparison between different control technics, like [5] and [6]. Most of those papers, however, do not have a practical implementation, validating only via computer simulations or implement the system via an actuator directly on the pedals, like is done on [7], and not by communicating to the electronic control units from the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Development and Implementation of an Adaptive Cruise Control System with a Customized Engine Control Unit

Kapelius¹,

Gatti²,

M³

et al. 2019

Blucher Engineering Proceedings

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This paper describes the development of an adaptive cruise control system (ACC), a driving assistant system, whose purpose is to control the vehicle's speed, determined by a setpoint inputted by the driver. Simultaneously, the system must also monitor the environment and adjust the car's velocity in order to maintain a safety distance from the other vehicles driving on the lane. This system's main purpose is to increase the driver's comfort, thus making it so he will no longer be required to control the throttle pedal and therefore be able to focus on the other tasks involved in driving. For the speed control to be possible, the system communicates with an open engine control unit (ECU), developed by the Automotive Engineering Group (group formed by researchers members of Escola Politécnica da USP and of Faculdade de Tecnologia de Santo André) as well as with an automotive radar, installed on the vehicle's front bumper, responsible for measuring relative distance and relative speed to the other vehicles driving on the road. As the vehicle used does not have brake-bywire technologies implemented, the speed reducing is done via engine breaking. After its development, the system was implemented on a Volkswagen Polo 2004 and its performance was validated with tests on an inertial dynamometer and with road tests.

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Simulation Validation of Three Nonlinear Model-Based Controllers in the Adaptive Cruise Control System

Cited by 33 publications

References 35 publications

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

Efficient ACC with Stop&Go maneuvers for hybrid vehicle with online sub-optimal energy management

Development and Implementation of an Adaptive Cruise Control System with a Customized Engine Control Unit

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