MPC-based Lateral Controller with Look-Ahead Design for Autonomous Multi-vehicle Merging into Platoon

Goli, Mohammad; Eskandarian, Azim

doi:10.23919/acc.2019.8814967

Cited by 20 publications

(12 citation statements)

References 20 publications

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“…In [101], a combined PID controller and MPC-based controller with a look-ahead design are proposed to control the longitudinal and lateral motion of the nonlinear vehicle dynamics model separately. The controller is used to allow multiple vehicles to join an existing platoon using variablegap 5th order polynomial lateral desired trajectory.…”

Section: Maneuver Controlmentioning

confidence: 99%

Platoon Transitional Maneuver Control System: A Review

et al. 2021

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Connectivity and autonomy are considered two of the most promising technologies to improve mobility, fuel consumption, travel time, and traffic safety in the automated transportation industry. These benefits can be realized through vehicle platooning. A vehicle platoon is composed of a group of connected automated vehicles (CAVs) traveling together at consensual speed, following the leading vehicle (leader) while maintaining a prespecified inter-vehicle distance. This paper reviews the different existing control techniques associated with the transitional platoon maneuvers such as merge/split and lane change. Different longitudinal and lateral vehicle dynamics that are mainly used in the transitional platoon maneuvers are discussed. The most used control algorithms for both longitudinal and lateral control used for transitional platoon maneuvers are reviewed and the advantages and limitations of each control strategy are discussed. The most recent articles on platoon control maneuvers have been analyzed based on the proposed control algorithm, homogeneously or heterogeneously of platoon members, type of platoon maneuver, the aim of control problem, type of implementation, and used simulation tools. This paper also discusses different trajectory planning techniques used in lateral motion control and studies the most recent research related to trajectory planning for automated vehicles and summarizes them based on the used trajectory planning technique, platoon or/and lane change, the type of traffic, and the cost functions. Finally, this paper explores the open issues and directions for future research.

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Section: Maneuver Controlmentioning

confidence: 99%

Platoon Transitional Maneuver Control System: A Review

et al. 2021

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“…Besides, MPC has succeeded in the field of industrial process control (Yu-Geng et al , 2013). Therefore, in recent years, it has been widely used in the field of autonomous driving (Goli and Eskandarian, 2019; Quan and Chung, 2019; Li et al , 2010). However, MPC often shows low efficiency in solving real-time tasks due to a large amount of calculation (Yu-Geng et al , 2013).…”

Section: Introductionmentioning

confidence: 99%

FPGA accelerated model predictive control for autonomous driving

Jia

et al. 2022

JICV

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Purpose The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research. Design/methodology/approach In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method. Findings This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method. Research limitations implications Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment. Originality value This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.

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“…Goli and Eskandarian designed a lateral controller based on model predictive control to solve the problem of vehicles merging into a platoon in another lane. This controller features a look‐ahead design so that it can improve the tracking objective [42]. Based on the model predictive control, Ni et al.…”

Section: Introductionmentioning

confidence: 99%

A cooperative lane change approach for heterogeneous platoons under different communication topologies

Nie

Xie

et al. 2021

IET Intelligent Trans Sys

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To improve the platoon's passability and traffic efficiency, a cooperative lane change approach is proposed when the platoon encounters a slow obstacle vehicle ahead in this paper. The algorithm is designed for the heterogeneous platoon, that is, the vehicles are dynamically decoupled and have different parameters. The vehicles in the platoon can have different communication topologies. To complete the lane change process quickly, all vehicles in the platoon perform simultaneously. The approach is mainly divided into two parts: trajectory planning and cooperative control. In the trajectory planning part, combined with the polynomial method and the optimization method, the leading vehicle plans an optimal lane change trajectory according to its own states and the obstacle vehicle's states. A distributed model predictive control algorithm is designed in the cooperative control part to meet the requirement that all vehicles should change lanes simultaneously. Besides, the sufficient conditions to achieve the asymptotic stability are also given, and the simulation results can show the effectiveness of the algorithm.

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MPC-based Lateral Controller with Look-Ahead Design for Autonomous Multi-vehicle Merging into Platoon

Cited by 20 publications

References 20 publications

Platoon Transitional Maneuver Control System: A Review

Platoon Transitional Maneuver Control System: A Review

FPGA accelerated model predictive control for autonomous driving

A cooperative lane change approach for heterogeneous platoons under different communication topologies

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