Feedforward Compensation-Based Finite-Time Traffic Flow Controller for Intelligent Connected Vehicle Subject to Sudden Velocity Changes of Leading Vehicle

Optimal velocity (OV)-based car-following model can be easily applied to the transportation system composed of intelligent connected vehicle (ICV) via vehicle-to-vehicle (V2V) communication, since this model only requires space headway and velocity differences of preceding vehicles. However, the sud...

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Published inIEEE transactions on intelligent transportation systems Vol. 21; no. 8; pp. 3357 - 3365
Main Authors Yan, Ruidong, Yang, Diange, Wijaya, Benny, Yu, Chunlei
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract Optimal velocity (OV)-based car-following model can be easily applied to the transportation system composed of intelligent connected vehicle (ICV) via vehicle-to-vehicle (V2V) communication, since this model only requires space headway and velocity differences of preceding vehicles. However, the sudden velocity changes of the leading vehicle will decrease the control performance of following vehicles. Particularly, the farther the distance between the following vehicle and the leading vehicle is, the worse the control performance of the following vehicle is. Besides this problem, the nonlinear information of OV-based car-following models is often not fully utilized due to the linearization for the convenience of stability analysis and controller design. To address these problems, the factors related to velocity sudden changes are taken into account for each ICV simultaneously and compensated by the proposed feedforward compensator. Based on the compensator, a finite-time traffic flow controller is designed for each ICV to smooth the space headway in traffic flow subject to sudden velocity changes and make full use of the nonlinear information of OV-based model. Finally, the theoretical analysis via Lyapunov approach and the numerical simulations are carried out to verify the effectiveness of the proposed method.
AbstractList Optimal velocity (OV)-based car-following model can be easily applied to the transportation system composed of intelligent connected vehicle (ICV) via vehicle-to-vehicle (V2V) communication, since this model only requires space headway and velocity differences of preceding vehicles. However, the sudden velocity changes of the leading vehicle will decrease the control performance of following vehicles. Particularly, the farther the distance between the following vehicle and the leading vehicle is, the worse the control performance of the following vehicle is. Besides this problem, the nonlinear information of OV-based car-following models is often not fully utilized due to the linearization for the convenience of stability analysis and controller design. To address these problems, the factors related to velocity sudden changes are taken into account for each ICV simultaneously and compensated by the proposed feedforward compensator. Based on the compensator, a finite-time traffic flow controller is designed for each ICV to smooth the space headway in traffic flow subject to sudden velocity changes and make full use of the nonlinear information of OV-based model. Finally, the theoretical analysis via Lyapunov approach and the numerical simulations are carried out to verify the effectiveness of the proposed method.
Author Wijaya, Benny
Yu, Chunlei
Yan, Ruidong
Yang, Diange
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SubjectTerms Automobiles
Car following
Computational modeling
Computer simulation
Control stability
Control systems design
Controllers
Feedforward control
Feedforward systems
Finite-time control
Headways
Mathematical models
Measurement errors
Numerical models
optimal velocity (OV) car-following model
Space vehicles
Stability analysis
sudden velocity change
Traffic control
Traffic flow
traffic flow control
Transportation systems
two velocity difference model
Vehicles
Vehicular ad hoc networks
Velocity
Title Feedforward Compensation-Based Finite-Time Traffic Flow Controller for Intelligent Connected Vehicle Subject to Sudden Velocity Changes of Leading Vehicle
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