Yong Zhang - IEEE Xplore Author Profile

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Author details

Yong Zhang

Publications

53

Citations

464

Publications by Year

20122025

Co-Authors:

Jinde CaoJunzhou ChenJiang ChenHuimin ChengYi Chu

Show All Co-Authors (79)

Yong Zhang

Affiliation

Beijing Key Laboratory of Multimedia and Intelligent Software Technology

Beijing Artificial Intelligence Institute

and the Faculty of Information Technology, Beijing University of Technology, Beijing, China

Publication Topics

Graph Convolutional Network,
Convolutional Neural Network,
Graph Convolution,
Neural Network,
Graph Neural Networks,
Convolutional Network,
Traffic Data,
Graph Attention Network,
Root Mean Square Error,
Graph Structure,
Long Short-term Memory,
Spatial Dependence

Biography

Yong Zhang (Member, IEEE) received the Ph.D. degree in computer science from Beijing University of Technology in 2010. He is currently an Associate Professor of computer science with Beijing University of Technology. His research interests include intelligent transportation systems, big data analysis, visualization, and computer graphics.(Based on document published on 26 August 2024).

Publications

53

Citations

464

Publications by Year

20122025

Co-Authors:

Jinde Cao
Junzhou Chen
Jiang Chen
Huimin Cheng
Yi Chu

Show All Co-Authors (79)

Author's Published Works

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Showing 1-4 of 4 results

Journals (2)

Conferences (1)

Early Access Articles (1)

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Jiwan Jiang(4)
Yang Zhou(4)
Xinyue Ye(2)
Sixu Li(2)
Meng Wang(2)
Chair of Traffic Process Automation, Technische Universität Dresden, Dresden, Germany(2)
Zachry Department of Civil & Environmental Engineering, Texas A&M University, College Station, TX, USA(1)
Department of Multidisciplinary Engineering, Texas A&M University, College Station, USA(1)
Department of Landscape Architecture & Urban Planning, Texas A&M University, College Station, TX, USA(1)
Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, USA(1)
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)(1)
IEEE Access(1)
IEEE Transactions on Intelligent Transportation Systems(1)
IEEE Transactions on Intelligent Vehicles(1)
IEEE(4)
Bilbao, Spain(1)
Automated Vehicles(3)
Model Predictive Control(3)
Adaptive Cruise Control(2)
Control Input(2)
Cost Function(2)

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Stochastic Calibration of Automated Vehicle Car-Following Control: An Approximate Bayesian Computation Approach

Jiwan Jiang;Yang Zhou;Ghazaleh Jafarsalehi;Xin Wang;Soyoung Ahn;John D. Lee

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Volume: 26, Issue: 3 | Journal Article |

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This paper presents a stochastic calibration method based on Approximate Bayesian Computation (ABC). This method is applied to calibrate two car-following control models: linear control and model predictive control (MPC). The method is likelihood-function-free, where the likelihood function is replaced by simulation to approximate the posterior distribution of model parameters. This structure affo...Show More

Stochastic Calibration of Automated Vehicle Car-Following Control: An Approximate Bayesian Computation Approach

Jiwan Jiang;Yang Zhou;Ghazaleh Jafarsalehi;Xin Wang;Soyoung Ahn;John D. Lee

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Volume: 26, Issue: 3 | Journal Article |

Sequencing-Enabled Hierarchical Cooperative CAV On-Ramp Merging Control With Enhanced Stability and Feasibility

Sixu Li;Yang Zhou;Xinyue Ye;Jiwan Jiang;Meng Wang

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

This paper develops a sequencing-enabled hierarchical connected automated vehicle (CAV) cooperative on-ramp merging control framework. The proposed framework consists of a two-layer design: the upper-level control sequences the vehicles to harmonize the traffic density across mainline and on-ramp segments, simultaneously enhancing lower-level control efficiency through a mixed-integer linear progr...Show More

Sequencing-Enabled Hierarchical Cooperative CAV On-Ramp Merging Control With Enhanced Stability and Feasibility

Sixu Li;Yang Zhou;Xinyue Ye;Jiwan Jiang;Meng Wang

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

Sequencing-Enabled Hierarchical Cooperative On-Ramp Merging Control for Connected and Automated Vehicles

Sixu Li;Yang Zhou;Xinyue Ye;Jiwan Jiang;Meng Wang

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2023 | Conference Paper |

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This paper develops a sequencing-enabled hierarchical connected automated vehicle (CAV) cooperative on-ramp merging multi-scale control framework. The proposed framework consists of a two-layer design: the upper level control sequences the vehicles to balance the density difference between mainline and on-ramp segments while enhancing lower-level control efficiency through a mixed-integer linear p...Show More

Sequencing-Enabled Hierarchical Cooperative On-Ramp Merging Control for Connected and Automated Vehicles

Sixu Li;Yang Zhou;Xinyue Ye;Jiwan Jiang;Meng Wang

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2023 | Conference Paper |

A Personalized Human Drivers’ Risk Sensitive Characteristics Depicting Stochastic Optimal Control Algorithm for Adaptive Cruise Control

Jiwan Jiang;Fan Ding;Yang Zhou;Jiaming Wu;Huachun Tan

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (10)

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This paper presents a personalized stochastic optimal adaptive cruise control (ACC) algorithm for automated vehicles (AVs) incorporating human drivers' risk-sensitivity under system and measurement uncertainties. The proposed controller is designed as a linear exponential-of-quadratic Gaussian (LEQG) problem, which utilizes the stochastic optimal control mechanism to feedback the deviation from th...Show More

A Personalized Human Drivers’ Risk Sensitive Characteristics Depicting Stochastic Optimal Control Algorithm for Adaptive Cruise Control

Jiwan Jiang;Fan Ding;Yang Zhou;Jiaming Wu;Huachun Tan

Year: 2020 | Volume: 8 | Journal Article |

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