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Peter J. Jin

Also published under: Peter Jin

Publications

Citations

336

Publications by Year

20132024

Co-Authors:

Alexandre BayenAnjiang ChenYang ChengFan DingYi Ge

Show All Co-Authors (25)

Peter J. Jin

Also published under: Peter Jin

Affiliation

Department of Civil and Environmental Engineering

Rutgers University–New Brunswick

Piscataway, NJ, USA

Publication Topics

Deep Learning Models,
Object Detection,
Road Segments,
Traffic Conditions,
Traffic Data,
Traffic Detection,
Traffic Flow,
Vehicle Trajectory,
3D Data,
3D Object Detection,
Action Units,
Active Links

Biography

Peter Jin received the B.S. degree from the Department of Automation, Tsinghua University, Beijing, China, and the M.S. and Ph.D. degrees from the Department of Civil and Environmental Engineering, University of Wisconsin–Madison, in 2007 and 2009, respectively. He is currently an Assistant Professor with the Rutgers, The State University of New Jersey. He has coauthored more than 30 journal publications and more than 47 peer-reviewed conference papers. His research interests include mobile sensor data, traffic flow theory, freeway operations, active traffic and demand management, connected vehicles, and transportation big data analytics.(Based on document published on 30 September 2020).

Publications

Citations

336

Publications by Year

20132024

Co-Authors:

Alexandre Bayen
Anjiang Chen
Yang Cheng
Fan Ding
Yi Ge

Show All Co-Authors (25)

Author's Published Works

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Showing 1-9 of 9 results

Journals (6)

Conferences (1)

Early Access Articles (1)

Magazines (1)

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Peter J. Jin(8)
Bin Ran(4)
Tianya Terry Zhang(3)
Benedetto Piccoli(1)
Guohui Zhang(1)
Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, WI, USA(2)
Department of Civil and Environmental Engineering, University of New Mexico, Albequeque, New Mexico, USA(1)
Department of Civil and Environmental Engineering, University of Wisconsin, Madison, WI, USA(1)
Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA(1)
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China(1)
IEEE Transactions on Intelligent Transportation Systems(5)
2013 International Conference on Connected Vehicles and Expo (ICCVE)(1)
IEEE Intelligent Transportation Systems Magazine(1)
IEEE Transactions on Computational Social Systems(1)
IEEE Transactions on Intelligent Vehicles(1)
IEEE(9)
Las Vegas, NV, USA(1)
Traffic Flow(6)
Vehicle Trajectory(5)
Mean Absolute Error(3)
Traffic Conditions(3)
Traffic Congestion(3)

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Real-Time Driver and Traffic Data Integration for Enhanced Road Safety

Yufei Huang;Shan Jiang;Mohsen Jafari;Peter J. Jin

IEEE Transactions on Computational Social Systems

Year: 2024 | Volume: 11, Issue: 6 | Journal Article |

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Traditional roadway safety assessment heavily relies on historical crash data, overlooking real-time factors such as driver behaviors and current traffic conditions and lacking forward-looking analysis for predicting future trends. This study introduces an enhanced innovative data fusion method based on the safe route mapping (SRM) methodology with combined use of historical crash data and real-ti...Show More

Real-Time Driver and Traffic Data Integration for Enhanced Road Safety

Yufei Huang;Shan Jiang;Mohsen Jafari;Peter J. Jin

IEEE Transactions on Computational Social Systems

Year: 2024 | Volume: 11, Issue: 6 | Journal Article |

Hash-Based Gaussian Mixture Model (HGMM) for Roadside LiDAR Smart Infrastructure Applications

Tianya Terry Zhang;Yi Ge;Anjiang Chen;Mina Sartipi;Peter J. Jin

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 10 | Journal Article |

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This paper proposes a point cloud background filtering method and explores applications that integrate LiDAR technology into roadside sensor networks, addressing challenges in handling large volumes of sparse and unstructured 3D data. Traditional methods, which classify background points based on descriptive statistics over many frames, are computationally inefficient for roadside LiDAR surveillan...Show More

Hash-Based Gaussian Mixture Model (HGMM) for Roadside LiDAR Smart Infrastructure Applications

Tianya Terry Zhang;Yi Ge;Anjiang Chen;Mina Sartipi;Peter J. Jin

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 10 | Journal Article |

Car-Following Models: A Multidisciplinary Review

Tianya Terry Zhang;Peter J. Jin;Sean T. McQuade;Alexandre Bayen;Benedetto Piccoli

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

Car-following (CF) algorithms are crucial components of traffic simulations and have been integrated into many production vehicles equipped with Advanced Driving Assistance Systems (ADAS). Insights from the model of car-following behavior help researchers to understand the causes of various macro phenomena that arise from interactions between pairs of vehicles. Car-following Models encompass multi...Show More

Car-Following Models: A Multidisciplinary Review

Tianya Terry Zhang;Peter J. Jin;Sean T. McQuade;Alexandre Bayen;Benedetto Piccoli

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

Segmentation is Tracking: Spatial-Temporal Map Vehicle Trajectory Reconstruction and Validation

Tianya Terry Zhang;Peter J. Jin

IEEE Transactions on Intelligent Transportation Systems

Year: 2023 | Volume: 24, Issue: 12 | Journal Article |

Cited by: Papers (1)

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This paper proposed the “Segmentation is traCKing” (SiCK) solution that extract vehicle movements with semantic segmentation for high-resolution trajectory reconstruction and validation. The dynamic mode decomposition (DMD) method extracts vehicle strands by decomposing the spatial-temporal map (STMap) into the sparse foreground and low-rank background. The Res-UNet+ neural networks was designed b...Show More

Segmentation is Tracking: Spatial-Temporal Map Vehicle Trajectory Reconstruction and Validation

Tianya Terry Zhang;Peter J. Jin

IEEE Transactions on Intelligent Transportation Systems

Year: 2023 | Volume: 24, Issue: 12 | Journal Article |

A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data

Shen Li;Yang Cheng;Peter Jin;Fan Ding;Qing Li;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2022 | Volume: 23, Issue: 2 | Journal Article |

Cited by: Papers (4)

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Most existing cellular probe-based freeway congestion detection methods rely on on-call WLT (Wireless Location Technologies) signal transition data. However, these techniques facing difficulties such as small sample size, frequent road tests, safety, and privacy issues. This article presents a novel approach using the FCA data for traffic congestion detection on freeways. Two cellular activity fea...Show More

A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data

Shen Li;Yang Cheng;Peter Jin;Fan Ding;Qing Li;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2022 | Volume: 23, Issue: 2 | Journal Article |

Autonomous Vehicle-Intersection Coordination Method in a Connected Vehicle Environment

Peiqun Lin;Jiahui Liu;Peter J. Jin;Bin Ran

IEEE Intelligent Transportation Systems Magazine

Year: 2017 | Volume: 9, Issue: 4 | Magazine Article |

Cited by: Papers (116) | Patents (1)

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In response to the need for developing coordinated schemes of autonomous vehicles (AVs) at an intersection. This paper presents a novel coordination method for intersection management in a connected vehicle environment. The road network is divided into three logical sections, namely, buffer area, core area and free driving area. In addition, a buffer-assignment mechanism is developed to cooperativ...Show More

Autonomous Vehicle-Intersection Coordination Method in a Connected Vehicle Environment

Peiqun Lin;Jiahui Liu;Peter J. Jin;Bin Ran

IEEE Intelligent Transportation Systems Magazine

Year: 2017 | Volume: 9, Issue: 4 | Magazine Article |

Short-Term Traffic Prediction Based on Dynamic Tensor Completion

Huachun Tan;Yuankai Wu;Bin Shen;Peter J. Jin;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2016 | Volume: 17, Issue: 8 | Journal Article |

Cited by: Papers (178)

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Short-term traffic prediction plays a critical role in many important applications of intelligent transportation systems such as traffic congestion control and smart routing, and numerous methods have been proposed to address this issue in the literature. However, most, if not all, of them suffer from the inability to fully use the rich information in traffic data. In this paper, we present a nove...Show More

Short-Term Traffic Prediction Based on Dynamic Tensor Completion

Huachun Tan;Yuankai Wu;Bin Shen;Peter J. Jin;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2016 | Volume: 17, Issue: 8 | Journal Article |

Reducing the Error Accumulation in Car-Following Models Calibrated With Vehicle Trajectory Data

Peter J. Jin;Da Yang;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2014 | Volume: 15, Issue: 1 | Journal Article |

Cited by: Papers (31)

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With the development of probe vehicle technologies and the emerging connected vehicle technologies, applications and models using trajectory data for calibration and validation significantly increase. However, the error accumulation issue accompanied by the calibration process has not been fully investigated and addressed. This paper explores the mechanism and countermeasures of the error accumula...Show More

Reducing the Error Accumulation in Car-Following Models Calibrated With Vehicle Trajectory Data

Peter J. Jin;Da Yang;Bin Ran

IEEE Transactions on Intelligent Transportation Systems

Year: 2014 | Volume: 15, Issue: 1 | Journal Article |

Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment

Peter J. Jin;Guohui Zhang;C. Michael Walton;Xiaowen Jiang;Amit Singh

2013 International Conference on Connected Vehicles and Expo (ICCVE)

Year: 2013 | Conference Paper |

Cited by: Papers (6)

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With the rapid development of connected vehicle (CV) technologies, cyber security issues in the vehicular network has emerged as serious concerns for successful deployment of CV systems. In the existing literature, the analysis of the cyber security impacts has been primarily focused from the computer science perspectives investigating potential attacking scenarios and counter-measures through net...Show More

Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment

Peter J. Jin;Guohui Zhang;C. Michael Walton;Xiaowen Jiang;Amit Singh

2013 International Conference on Connected Vehicles and Expo (ICCVE)

Year: 2013 | Conference Paper |

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Author details

Peter J. Jin

Peter J. Jin

Affiliation

Publication Topics

Biography

Showing 1-9 of 9 results

Show

Real-Time Driver and Traffic Data Integration for Enhanced Road Safety

Real-Time Driver and Traffic Data Integration for Enhanced Road Safety

Hash-Based Gaussian Mixture Model (HGMM) for Roadside LiDAR Smart Infrastructure Applications

Hash-Based Gaussian Mixture Model (HGMM) for Roadside LiDAR Smart Infrastructure Applications

Car-Following Models: A Multidisciplinary Review

Car-Following Models: A Multidisciplinary Review

Segmentation is Tracking: Spatial-Temporal Map Vehicle Trajectory Reconstruction and Validation

Segmentation is Tracking: Spatial-Temporal Map Vehicle Trajectory Reconstruction and Validation

A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data

A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data

Autonomous Vehicle-Intersection Coordination Method in a Connected Vehicle Environment

Autonomous Vehicle-Intersection Coordination Method in a Connected Vehicle Environment

Short-Term Traffic Prediction Based on Dynamic Tensor Completion

Short-Term Traffic Prediction Based on Dynamic Tensor Completion

Reducing the Error Accumulation in Car-Following Models Calibrated With Vehicle Trajectory Data

Reducing the Error Accumulation in Car-Following Models Calibrated With Vehicle Trajectory Data

Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment

Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment

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