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Yongjie Lin

Publications

Citations

Publications by Year

20182025

Co-Authors:

Zefei ChenYao ChengBin FengWei HaoZilin Huang

Show All Co-Authors (23)

Yongjie Lin

Affiliation

School of Civil Engineering & Transportation

South China University of Technology

Guangzhou, China

Publication Topics

Objective Function,
Phase Sequence,
Average Delay,
Average Delay Time,
Control Variables,
Cycle Length,
Equality Constraints,
Light Signal,
Traffic Flow,
Traffic Volume,
Accuracy Of Model,
Actual Point

Biography

Yongjie Lin (Member, IEEE) received the Ph.D. degree from the School of Control Science and Engineering, Shandong University, China, in 2014. During his Ph.D. program, he has studied with the University of Maryland at College Park, College Park, USA, for one year as a Visiting Student which was supported by the China Scholarship Council, China. He held a one-year post-doctoral position with the Department of Civil and Environmental Engineering, Northwestern University, USA. He is currently an Assistant Professor with the Department of Transportation, South China University of Technology, China. He has published over 30 journal and conference academic articles about traffic data analysis, and traffic operations and control.(Based on document published on 10 August 2020).

Publications

Citations

Publications by Year

20182025

Co-Authors:

Zefei Chen
Yao Cheng
Bin Feng
Wei Hao
Zilin Huang

Show All Co-Authors (23)

Author's Published Works

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Showing 1-9 of 9 results

Journals (6)

Conferences (3)

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Yongjie Lin(9)
Jianmin Xu(5)
Kai Lu(3)
Bin Feng(2)
Zefei Chen(2)
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China(5)
School of Civil Engineering & Transportation, South China University of Technology, Guangzhou, China(2)
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China(1)
Institute for Transportation and Development Policy, Guangzhou, China(1)
Traffic Police Detachment, Zhongshan, China(1)
IEEE Access(2)
IEEE Transactions on Intelligent Transportation Systems(2)
2019 5th International Conference on Transportation Information and Safety (ICTIS)(1)
2020 7th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)(1)
2023 China Automation Congress (CAC)(1)
IEEE(9)
Chongqing, China(1)
Guangzhou, China(1)
Liverpool, UK(1)
Light Signal(4)
Objective Function(4)
Traffic Flow(4)
Traffic Volume(4)
Phase Sequence(3)

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Detecting Pedestrian With Incomplete Head Feature in Crowded Situation Based on Transformer

Zefei Chen;Yongjie Lin;Jianmin Xu;Kai Lu;Yanfang Shou

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

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Pedestrian detection in crowded situation is a challenging task. This study presents a straightforward and effective method called Det RCNN to detect pedestrians in crowded situation, while also pairing the body and head of individual pedestrian. On the one hand, pedestrians' heads have their characteristics of stable shape and distinct feature. On the other hand, their heads are usually positione...Show More

Detecting Pedestrian With Incomplete Head Feature in Crowded Situation Based on Transformer

Zefei Chen;Yongjie Lin;Jianmin Xu;Kai Lu;Yanfang Shou

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

Path Curvature Based Variable Weight Multi-Constraint MPC for Smart Vehicle Trajectory Tracking Control

Jianmin Xu;Yunxun Wu;Yongjie Lin

2023 China Automation Congress (CAC)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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In order to balance the accuracy and stability of trajectory tracking for intelligent driving vehicles under the com-plex working conditions, this study proposes trajectory tracking control strategy based on path curvature variable weight model predictive control. model predictive control is established with front wheel steering angle and front wheel speed as control variables, using real-time lat...Show More

Path Curvature Based Variable Weight Multi-Constraint MPC for Smart Vehicle Trajectory Tracking Control

Jianmin Xu;Yunxun Wu;Yongjie Lin

2023 China Automation Congress (CAC)

Year: 2023 | Conference Paper |

Bandwidth-Based Traffic Signal Coordination Models for Split or Mixed Phasing Schemes in Various Types of Networks

Binbin Jing;Quan Shi;Cong Huang;Peng Ping;Yongjie Lin

IEEE Open Journal of Intelligent Transportation Systems

Year: 2023 | Volume: 4 | Journal Article |

Cited by: Papers (1)

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Bandwidth-based traffic signal coordination has long been an effective technique to make traffic flows within a network more efficient, smoother, and safer. Existing network bandwidth optimization models mainly focus on maximizing the bandwidth under NEMA phasing. The network bandwidth maximization under other typical phasing schemes, namely the split or mixed phasing, has not been intensively stu...Show More

Bandwidth-Based Traffic Signal Coordination Models for Split or Mixed Phasing Schemes in Various Types of Networks

Binbin Jing;Quan Shi;Cong Huang;Peng Ping;Yongjie Lin

IEEE Open Journal of Intelligent Transportation Systems

Year: 2023 | Volume: 4 | Journal Article |

Optimization Model of Regional Green Wave Coordination Control for the Coordinated Path Set

Kai Lu;Xin Tian;Shuyan Jiang;Yongjie Lin;Weibin Zhang

IEEE Transactions on Intelligent Transportation Systems

Year: 2023 | Volume: 24, Issue: 7 | Journal Article |

Cited by: Papers (4)

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An optimization model of regional green wave coordination control for the coordinated path set is proposed based on the network’s directional and asymmetric actual coordination control demands. The model in this paper selects the coordinated path set as the optimization object and takes the best regional coordination control effect as the optimization objective. By selecting signal timing paramete...Show More

Optimization Model of Regional Green Wave Coordination Control for the Coordinated Path Set

Kai Lu;Xin Tian;Shuyan Jiang;Yongjie Lin;Weibin Zhang

IEEE Transactions on Intelligent Transportation Systems

Year: 2023 | Volume: 24, Issue: 7 | Journal Article |

Pband: A General Signal Progression Model With Phase Optimization Along Urban Arterial

Binbin Jing;Yongjie Lin;Yanfang Shou;Kai Lu;Jianmin Xu

IEEE Transactions on Intelligent Transportation Systems

Year: 2022 | Volume: 23, Issue: 1 | Journal Article |

Cited by: Papers (16)

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Overlapping phase and split phase are two typical phase patterns at signalized intersections in practice. The existing bandwidth-oriented progression control schemes mainly focus on overlapping phase to adopt the various layout of intersections and volumes rather than split phase. To address this issue, a two-way signal progression model, namely Pband, is developed to simultaneously optimize phase...Show More

Pband: A General Signal Progression Model With Phase Optimization Along Urban Arterial

Binbin Jing;Yongjie Lin;Yanfang Shou;Kai Lu;Jianmin Xu

IEEE Transactions on Intelligent Transportation Systems

Year: 2022 | Volume: 23, Issue: 1 | Journal Article |

Traffic Flow Prediction based on Time Information

Zefei Chen;Jianmin Xu;Yongjie Lin;Bin Feng;Dongmei Liao;Hongtao Lin

2020 7th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)

Year: 2020 | Conference Paper |

Cited by: Papers (1)

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With the increasing number of urban vehicles, traffic congestion has become increasingly serious. Predicting traffic flow and take corresponding measures, which plays a pivotal role in easing traffic congestion. At present, many researchers have done a lot of research on the temporal and spatial correlation of traffic flow in the traffic network. Meanwhile, the traffic flow has a strong periodicit...Show More

Traffic Flow Prediction based on Time Information

Zefei Chen;Jianmin Xu;Yongjie Lin;Bin Feng;Dongmei Liao;Hongtao Lin

2020 7th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)

Year: 2020 | Conference Paper |

A Period-Specific Combined Traffic Flow Prediction Based on Travel Speed Clustering

Bin Feng;Jianmin Xu;Yongjie Lin;Penghao Li

IEEE Access

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (9)

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Short-term traffic flow forecasting has always been an interesting research at the fields of Intelligent Transportation Systems. This paper presents a time-based combined traffic flow prediction model based on field data collected by loop detectors at signalized intersections, which are used to signal optimization, route choice, traffic monitoring, etc. Firstly, the traffic flow and corresponding ...Show More

A Period-Specific Combined Traffic Flow Prediction Based on Travel Speed Clustering

Bin Feng;Jianmin Xu;Yongjie Lin;Penghao Li

IEEE Access

Year: 2020 | Volume: 8 | Journal Article |

A Novel WIFI-Oriented RSSI Signal Processing Method for Tracking Low-Speed Pedestrians

Zilin Huang;Xianyuan Zhu;Yongjie Lin;Lunhui Xu;Yadong Mao

2019 5th International Conference on Transportation Information and Safety (ICTIS)

Year: 2019 | Conference Paper |

Cited by: Papers (13)

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The accurate estimation of pedestrian movement location is one of hot research topics among Intelligent Transportation Systems. In the real-time pedestrian tracking application, the WiFi-based localization method is seriously affected by environmental noise, which results in the large positioning error. Aiming at this issue, this paper first analyzed the localization technologies based on the Rece...Show More

A Novel WIFI-Oriented RSSI Signal Processing Method for Tracking Low-Speed Pedestrians

Zilin Huang;Xianyuan Zhu;Yongjie Lin;Lunhui Xu;Yadong Mao

2019 5th International Conference on Transportation Information and Safety (ICTIS)

Year: 2019 | Conference Paper |

Signal Progression Model for Long Arterial: Intersection Grouping and Coordination

Wei Hao;Yongjie Lin;Yao Cheng;Xianfeng Yang

IEEE Access

Year: 2018 | Volume: 6 | Journal Article |

Cited by: Papers (18)

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Signal progression has been proven as an effective way to improve the operational efficiency of traffic signals at local arterial corridors. Conventional two-way progression models have shown their promising in providing desirable green bandwidth to two-way through traffic along the arterial. However, they may not offer an effective progression plan when a long arterial contains many intersections...Show More

Signal Progression Model for Long Arterial: Intersection Grouping and Coordination

Wei Hao;Yongjie Lin;Yao Cheng;Xianfeng Yang

IEEE Access

Year: 2018 | Volume: 6 | Journal Article |

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Yongjie Lin

Yongjie Lin

Affiliation

Publication Topics

Biography

Showing 1-9 of 9 results

Show

Detecting Pedestrian With Incomplete Head Feature in Crowded Situation Based on Transformer

Detecting Pedestrian With Incomplete Head Feature in Crowded Situation Based on Transformer

Path Curvature Based Variable Weight Multi-Constraint MPC for Smart Vehicle Trajectory Tracking Control

Path Curvature Based Variable Weight Multi-Constraint MPC for Smart Vehicle Trajectory Tracking Control

Bandwidth-Based Traffic Signal Coordination Models for Split or Mixed Phasing Schemes in Various Types of Networks

Bandwidth-Based Traffic Signal Coordination Models for Split or Mixed Phasing Schemes in Various Types of Networks

Optimization Model of Regional Green Wave Coordination Control for the Coordinated Path Set

Optimization Model of Regional Green Wave Coordination Control for the Coordinated Path Set

Pband: A General Signal Progression Model With Phase Optimization Along Urban Arterial

Pband: A General Signal Progression Model With Phase Optimization Along Urban Arterial

Traffic Flow Prediction based on Time Information

Traffic Flow Prediction based on Time Information

A Period-Specific Combined Traffic Flow Prediction Based on Travel Speed Clustering

A Period-Specific Combined Traffic Flow Prediction Based on Travel Speed Clustering

A Novel WIFI-Oriented RSSI Signal Processing Method for Tracking Low-Speed Pedestrians

A Novel WIFI-Oriented RSSI Signal Processing Method for Tracking Low-Speed Pedestrians

Signal Progression Model for Long Arterial: Intersection Grouping and Coordination

Signal Progression Model for Long Arterial: Intersection Grouping and Coordination

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