Intelligent Vehicle Platoon Research Articles

Research on Intelligent Platoon Formation Control Based on Kalman Filtering and Model Predictive Control

Recently, the intelligent platoon has attracted a lot of attention in both academic and industrial research. For each intelligent platoon, all vehicles drive sequentially in a line, which helps to improve fuel economy and road capacity. Consider two adjacent vehicles in the intelligent platoon, and there is no mechanical boundary between them. However, an intelligent platoon may still suffer from the issues of poor vehicle-following performance during the process of vehicle-following, especially when it obtains its own position and other parameters inaccurately. To address this issue, this paper proposes a model predictive control method based on an improved version of Kalman filtering, aiming to enhance the anti-interference capacity of intelligent platoons in scenarios where the following vehicles have acquired inaccurate parameters resulting from environmental disturbances and sensor noise. Firstly, this paper establishes a three-degree-of-freedom single-track model for the following vehicle, conducting dynamic analysis of its lateral, longitudinal, and yaw movements. Then, this paper develops a horizontal and longitudinal formation driving control frame of the intelligent vehicle platoon. Moreover, this paper also has employed Kalman filtering for interference reduction of state parameters and designs an improved model predictive controller. The proposed scheme is verified and evaluated through a joint simulation within Carsim and MATLAB/Simulink, and the results demonstrate that the longitudinal following error is reduced by 37% and the lateral following error is reduced by 51% compared to traditional algorithms, effectively improving the stability of intelligent vehicle platoons during following driving.

Lane-Changing Control of Vehicle Platoon Based on OS-ELM Environmental Parameter Identifier

A sliding mode control strategy is presented based on the online sequential extreme learning machine (OS-ELM) environmental parameter identifier. The aim is to eliminate the effects of uncertain environmental parameters in the lane-changing control of the intelligent vehicle platoon. Firstly, the vehicle platoon dynamics model is established considering the communication topology between the vehicle platoon. Then, the vehicle platoon distance error model is obtained based on the constant time distance strategy. Moreover, a sliding mode control strategy based on OS-ELM environmental parameter identifier is proposed to deal with the uncertainty of some environment parameters. Furthermore, finite-time stability and string stability of the system are analyzed by constructing a Lyapunov function. Finally, Carsim/Simulink simulations further verify the effectiveness of the method in this research. The results show that the proposed method estimates the uncertainty parameters accurately in this vehicle platoon. Meanwhile, it guarantees the string stability, and realizes the rapid convergence of errors.

Cooperative distributed predictive control for collision‐free vehicle platoons

The rapidly developing computing and communication technologies improve the autonomy of individual vehicles on the one hand and facilitate the coordination among vehicles on the other. In the context of dynamic speed management, this study considers a platoon of intelligent vehicles that are required to maintain desired inter-vehicle spaces and to respond to speed changes in a collision-free, stable and cooperative way. The platoon is modelled as a cascaded network with linear longitudinal vehicle dynamics, independent physical constraints, and coupling safety constraints. In the case of global information sharing, the authors first propose a centralised collision-free solution on the basis of model predictive control that guarantees asymptotic platoon tracking of speed changes and satisfaction of system constraints during the transient process. A cooperative distributed approach is then further proposed on the basis of the alternating direction method of multipliers resulting in a scheme involving communication only with the roadside infrastructure, e.g. the speed manager. Vehicles in a platoon conduct parallel computation while still achieving global optimal performance and coordination with respect to the collision avoidance constraints. Convergence properties of the distributed solutions are established for the concerned vehicle platoon problem. Simulation results show satisfactory platoon performance and demonstrate the effectiveness of the proposed algorithms.

The VisLab Intercontinental Autonomous Challenge: an extensive test for a platoon of intelligent vehicles

This paper presents the VisLab Intercontinental Autonomous Challenge (VIAC), an autonomous vehicles test carried out from Parma to Shanghai between July and October 2010 by the VisLab team. The vehicle equipment is explained introducing the sensing systems which were tested during the journey. Trip details and the first statistics are presented as well.

Speed Tracking Control for a Simulated Intelligent Vehicle Platoon under Variable Road Conditions

Autonomous driving for intelligent vehicle and platoon is achieved by improving the intelligent control level of single vehicle and the ability of information interaction between vehicle and highway in intelligent vehicle-highway system,in which traffic flow is adjusted to the best and highway capacity,road safety is improved by means of increasing speed and reducing the space between vehicles,thus the increasingly serious traffic problems are solved.The intelligent vehicle platoon driving simulation experiment system is constructed under the coordination between vehicle and highway by means of one-tenth of model cars,simulated road and the technology of intelligent control and wireless communication.Among them,intelligent control for single vehicle is the most important.Sliding mode variable structure control method is a simple and fast,robust,and most reliable control method.On the basis of the intelligent vehicle simulation system by adding acceleration sensor,the speed tracking controller is designed by fuzzy sliding mode control based on equivalent control.A given reference speed can be globally stably tracked when the intelligent vehicle drives in variable road conditions.The simulation results show the effectiveness and stability of the controller,the study on the control for a platoon of autonomous vehicles under the coordination between vehicle and highway can be promoted by theories and experiments.

Research on Intelligent Vehicle platoon Driving Simulation Experiment System under the Coordination between Vehicle and Highway

Intelligent vehicle platoon driving is a process of the flexible formation based on the coordination between vehicle and highway in the intelligent vehicle-highway system, which can increase the controllability of traffic, simplify the complexity of traffic control, and ease the traffic pressure. It has been constructed that the intelligent vehicle platoon driving simulation experiment system under the coordination between vehicle and highway by means of the one-tenth of model cars, simulated road and the technology about intelligent control and wireless communication. On the basis of the experimental platform and analysis, it has been studied that the autonomous driving technology for intelligent vehicle, and that the information interaction between vehicle and highway as well as that with the main console by the wireless communication networks built, providing the technical and experimental basis for further research on intelligent vehicle platoon driving control under the coordination between vehicle and highway.