Cooperative Spacing Control for Interconnected Vehicle Systems With Input Delays

Liu, Yonggui; Pan, Chao; Gao, Huanli; Guo, Ge

doi:10.1109/tvt.2017.2712146

Cited by 61 publications

(17 citation statements)

References 29 publications

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“…From its birth to the present, the concept of autonomous driving has been given new connotation with the development of science and technology, i.e., changing from the initial autonomous driving system based on an autonomous trajectory tracking system to the present one based on a perception and decision-making system. At present, the motion control in an autonomous vehicle is mainly focused on ACC (Adaptive Cruise Control) [2] and trajectory tracking [3]. For the trajectory tracking problem, it is generally considered as a lateral control, which mainly considers the accuracy of the reference trajectory under a constant velocity.…”

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 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: 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.

View full text Add to dashboard Cite

show abstract

“…Remark 6: Similar to the analysis in Remark 4, it can be known from (32) that the system errors of (31) can also converge to a bounded range for any injection ξ and ξ satisfying (7). Therefore, the stabilization of cooperative CVSs can be guaranteed even if the overall systems are under cyber-attacks.…”

Section: (34)mentioning

confidence: 78%

“…Besides, it is known from Lemma 2 that when increasing Q h and taking small Q s (i.e., all elements in Q h (Q s ) increase (decrease) in the same proportion) to stabilize the interactive systems (22), the absolute value of each non-zero element in P h will become larger and that in P s gets smaller, concurrently (23) can be forced to converge to an arbitrarily small neighborhood around 0 3n . In this case, the system errors can be rewritten as lim k→∞ e(k) = −(G − I 3n ) −1 Y ξ e , which is bounded for any injection ξ satisfying (7). Note that in this case…”

Section: (22)mentioning

confidence: 99%

“…Owing to the interconnection and sharing of information between vehicles, such a platoon can be considered as a cyberphysical system (CPS). Considering the driver behaviors, braking control and input delays, cooperative adaptive cruise control (CACC), a typical application of CPS, is further proposed to ensure the coordination and stability of the vehicle platoon systems [5]- [7]. Flocking theory [8], [9] and consensus control [10]- [12] are widely used to analyze the information interaction between vehicles during the CACC process in CPS.…”

Section: Introductionmentioning

confidence: 99%

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Resilient Control Design of the Third-Order Discrete-Time Connected Vehicle Systems Against Cyber-Attacks

Liu

2020

IEEE Access

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This paper investigates the consensus problems of the third-order discrete-time Connected Vehicle Systems (CVSs) under cyber-attacks. First, the necessary and sufficient conditions for consensus of third-order discrete-time CVSs are derived in the absence of attacks by using algebraic graph and matrix theory. Then the interaction network framework between the original CVSs in the vehicle platoon layer and a virtual system in the hidden layer is established to resist cyber-attacks. Since sufficiently large attacks can be excluded from CVSs through a threshold defense mechanism, such potential attacks considered are bounded and generated by any linear or non-linear finite L2-gain exogenous dynamics system. It is proved that the stability of CVSs can be ensured and the state errors converge to a bounded range whether the attacks exist only in the vehicle platoon layer or in the overall systems (including the vehicle platoon layer and the hidden layer) by using the Lyapunov stability method. Finally, a simulation example containing several scenarios demonstrates the effectiveness and superiority of the proposed methods.

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“…Various control policies have been designed for diverse objectives under certain delays, such as the achievement of consensus [11], the robustness for formation changes and control [12], [13], the consensus of vehicles and their consistency with traffic flow theory [14], coping with the curves and slopes of roads [15], [16], and spacing [17]. There have also been several studies concerning the combination of control and delay bounds under stable conditions [6], [18]- [20].…”

Section: Related Workmentioning

confidence: 99%

Reducing the Standstill Spacing and Duration of Safe Braking Control in Vehicle Platoons With Delays

Meng

Wang

2020

IEEE Access

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Braking control, especially in an emergency, is a key technology that is needed to ensure safety in vehicle platoons. However, delays in vehicle platoons can severely affect braking control. This paper proposes an optimized braking control to reduce the standstill spacing and braking duration during delays so that a platoon will stop within a short time frame with a reduced length, thus improving road utilization while ensuring both inter-vehicle and in-vehicle safety. However, two challenges need to be addressed. First, due to the delay in car-following interactions and the nonlinearity of the control law, an analysis model is needed to quantize the duration and distance during an emergency braking with delays. Second, the optimization of these control parameters is an NP-hard problem. Therefore, delay differential equations are introduced to model the braking process, and a crossing criterion is introduced to establish the relationship between the control law and the braking process. The propositions of standstill spacing and braking duration are then derived based on the Runge-Kutta method. According to these criteria, a particle swarm optimization (PSO) based on a lexicographic method with a penalty function is introduced to provide a solution framework with polynomial complexity. Simulation results verify the accuracy of the braking modeling process. Moreover, the results verify the performance of the proposed algorithm and provide a reference for platoon control.

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Cooperative Spacing Control for Interconnected Vehicle Systems With Input Delays

Cited by 61 publications

References 29 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

Resilient Control Design of the Third-Order Discrete-Time Connected Vehicle Systems Against Cyber-Attacks

Reducing the Standstill Spacing and Duration of Safe Braking Control in Vehicle Platoons With Delays

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