A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon

Nie, Guangming; Xie, Bo; Hao, Zixu; Hu, Hang‐Wei; Tian, Yantao

doi:10.1177/09544070211070526

Cited by 9 publications

(3 citation statements)

References 36 publications

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“…In recent years, the research on CACC mainly focuses on longitudinal single-lane control, including stability analysis [ 30 , 31 , 32 , 33 , 34 ], communication problem analysis [ 35 , 36 , 37 , 38 ], heterogeneous problem analysis [ 39 , 40 , 41 , 42 ], etc. The control algorithm is mainly aimed at improving the original single-vehicle control algorithm, such as PID control, sliding mode control, and distributed model predictive control.…”

Section: Related Workmentioning

confidence: 99%

Research on a Cooperative Adaptive Cruise Control (CACC) Algorithm Based on Frenet Frame with Lateral and Longitudinal Directions

Ping-li

Jiang

2023

Sensors

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Research on the cooperative adaptive cruise control (CACC) algorithm is primarily concerned with the longitudinal control of straight scenes. In contrast, the lateral control involved in certain traffic scenes such as lane changing or turning has rarely been studied. In this paper, we propose an adaptive cooperative cruise control (CACC) algorithm that is based on the Frenet frame. The algorithm decouples vehicle motion from complex motion in two dimensions to simple motion in one dimension, which can simplify the controller design and improve solution efficiency. First, the vehicle dynamics model is established based on the Frenet frame. Through a projection transformation of the vehicles in the platoon, the movement state of the vehicles is decomposed into the longitudinal direction along the reference trajectory and the lateral direction away from the reference trajectory. The second is the design of the longitudinal control law and the lateral control law. In the longitudinal control, vehicles are guaranteed to track the front vehicle and leader by satisfying the exponential convergence condition, and the tracking weight is balanced by a sigmoid function. Laterally, the nonlinear group dynamics equation is converted to a standard chain equation, and the Lyapunov method is used in the design of the control algorithm to ensure that the vehicles in the platoon follow the reference trajectory. The proposed control algorithm is finally verified through simulation, and validation results prove the effectiveness of the proposed algorithm.

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Section: Related Workmentioning

confidence: 99%

Research on a Cooperative Adaptive Cruise Control (CACC) Algorithm Based on Frenet Frame with Lateral and Longitudinal Directions

Ping-li

Jiang

2023

Sensors

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“…In this distributed controller design, the authors model the input and output errors as penalty functions and also introduce the idea of consensus control to keep the state of the vehicle close to the state of neighboring vehicles. Similarly, Nie et al [69] proposes a DMPC algorithm to solve the cruise control problem for a heterogeneous MVS. The vehicles in the MVS are dynamically decoupled with different dynamic parameters, which means that this DMPC controller can cope with unintended switching of the IFT.…”

Section: Optimization-based Controlmentioning

confidence: 99%

A Review of Multi-vehicle Cooperative Control System in Intelligent Transportation

Xie,

Li,

Arvin

et al. 2023

IJAMM

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Review A Review of Multi-vehicle Cooperative Control System in Intelligent Transportation Songtao Xie 1, Zhenhong Li 1, Farshad Arvin 2, and Zhengtao Ding 1,* 1 Department of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK 2 Swarm & Computational Intelligence Laboratory (SwaCIL), Department of Computer Science, Durham University, Durham DH1 3LE, UK * Correspondence: zhengtao.ding@manchester.ac.uk Received: 25 April 2023 Accepted: 19 September 2023 Published: 25 September 2023 Abstract: Multi-vehicle cooperative control (MVCC) system has the potential to improve traffic flow, reduce congestion, and increase safety. This paper reviews the progress achieved by researchers worldwide regarding different aspects of MVCC systems. Research works of MVCC system architectures and strategies are reviewed, which explain how this system works. Several control methodologies utilized in the MVCC system and their related issues are discussed and compared, and research achievements about string stability and system degradation caused by unreliable communication are also reviewed. Applications of the MVCC system are demonstrated with detailed literature, which draws an overall landscape of the MVCC system and points out current opportunities and challenges. Finally, future research directions for the MVCC system are proposed based on the latest social and technological developments.

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“…Some new control methods have been utilized in this area. [1][2][3][4][5] For different traffic scenarios, Sawant and Chaskar developed a non-linear disturbance observerbased sliding mode control method to alleviate the peaking of control input. 6 Shojaei proposed a new control method for multiple Ackermann steering vehicle formation by combining an adaptive neural network robust controller.…”

Section: Introductionmentioning

confidence: 99%

Dynamics control of topology switching for multi-functional unmanned ground vehicle platoon with VCBDL topology

Zhao

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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With the development of Unmanned Ground Vehicles (UGVs), a variety of civilian missions could be carried out by UGVs. The utilization of UGV in Intelligent Transportation System (ITS) has received significant attention in recent year. However, single UGV can’t satisfy the requirement of enormous complex work in civil use. It requires UGV to be grouped as a platoon to complete different mission with different formation and information topology. Therefore, a novel coordination control method is needed to solve the topology switch problem. In this paper, a switchable form of Vehicle-Cloud Bidirectional Leader (VCBDL) topology is proposed. Within this information topology, the formation topology of UGV platoon is formed by following the order of cloud brain and can be switched for different requirement. To obtain stable performance of the platoon in switch process, this paper analyzes the design of the platoon controller. The range of controller gain is obtained through the Lyapunov stability analysis. The above conclusions are verified by the experiments based on a shuttle UGV testbed platoon.

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A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon

Cited by 9 publications

References 36 publications

Research on a Cooperative Adaptive Cruise Control (CACC) Algorithm Based on Frenet Frame with Lateral and Longitudinal Directions

Research on a Cooperative Adaptive Cruise Control (CACC) Algorithm Based on Frenet Frame with Lateral and Longitudinal Directions

A Review of Multi-vehicle Cooperative Control System in Intelligent Transportation

Dynamics control of topology switching for multi-functional unmanned ground vehicle platoon with VCBDL topology

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