高珍｜同济大学｜学者主页

2024

基于车载视觉的端到端驾驶员疲劳检测模型

高珍，陈超，许靖宁，余荣杰，宗佳琪

《同济大学学报(自然科学版)》

2024

Joint Multi-Agent Trajectory Prediction for Cooperative Vehicle Infrastructure System

Qian Chen, Tan Liu, Zhen Gao, Rongjie Yu, Jian Sun, Peng Hang

CAA International Conference on Vehicular Control and Intelligence (CVCI)

DOI

2024

Robust Hazardous Driving Scenario Detection for Supporting Autonomous Vehicles in Edge-Cloud Collaborative Environments

Zhen Gao, Liyou Wang, Jingning Xu, Hongfei Fan, Rongjie Yu

International Conference on Computer Supported Cooperative Work in Design (CSCWD)

DOI

2023

Hazardous Driving Scenario Identification with Limited Training Samples

Zhen Gao, Liyou Wang, Jingning Xu, Rongjie Yu, Ke Wang

Communications in computer and information science

DOI

2023

Utilizing angle-based outlier detection method with sliding window mechanism to identify real-time crash risk

Zhen Gao, Jingning Xu, Rongjie Yu, Lei Han

Journal of Transportation Safety & Security

DOI

2023

A Comprehensive Vision-Based Model for Commercial Truck Driver Fatigue Detection

Zhen Gao, Xiaowen Chen, Jingning Xu, Rongjie Yu, Jiaqi Zong

Lecture notes in computer science

DOI

2021

A Lightweight VK-Net Based on Motion Profiles for Hazardous Driving Scenario Identification

Zhen Gao, Jingning Xu, Jiang Yu Zheng, Hongfei Fan, Rongjie Yu, Jiaqi Zong, Xinyi Li

DOI

2020

Examining imbalanced classification algorithms in predicting real-time traffic crash risk

Yichuan Peng, Chongyi Li, Ke Wang, Zhen Gao, Rongjie Yu

Accident Analysis And Prevention，Vol. 144

DOI

2020

基于车辆方波脉冲时序图的交通流参数实时检测算法

高珍，黄钰琳，郑绛宇，王雪松

《同济大学学报(自然科学版)》

2020

Identifying High Risk Driving Scenarios Utilizing a CNN-LSTM Analysis Approach

Rongiie Yu, Haoan Ai, Zhen Gao

IEEE International Conference on Intelligent Transportation Systems (ITSC)

DOI

2020

Detecting Vehicle Interactions in Driving Videos via Motion Profiles

Zheyuan Wang, Jiang Yu Zheng, Zhen Gao

IEEE International Conference on Intelligent Transportation Systems (ITSC)

DOI

2020

Driving Style Recognition Based on Lane Change Behavior Analysis Using Naturalistic Driving Data

Zhen Gao, Yongchao Liang, Jiang Yu Zheng, Junyi Chen

CICTP 2020

DOI

2020

Roadway Risk Map Establishment Based on Features of Roadway Design and Traffic Situation

Zhen Gao, Jingning Xu, Jiang Yu Zheng, Rongjie Yu

CICTP 2020

DOI

2020

Perceiving Driving Hazards in a Data-fusion Way Using Multi-Modal Net and Semantic Driving Trajectory

Zhen Gao, Mingfeng Ou, Yajun Liu, Jiang Yu Zheng

International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)

DOI

2019

Exploring crash mechanisms with microscopic traffic flow variables: A hybrid approach with latent class logit and path analysis models

Rongjie Yu, Yin Zheng, Mohamed Abdel-Aty, Zhen Gao

Accident Analysis And Prevention，Vol. 125

DOI

2018

连续数据环境下的道路交通事故风险预测模型

高珍，高屹，余荣杰，黄智强，王雪松

《中国公路学报》

2018

Speeding Behavior Estimation Using Stop-and-Go Events Based on Velocity Data

Mingxi Chen, Zhen Gao, Rongjie Yu, Xuesong Wang

IEEE International Conference on Communication Systems (ICCS)

DOI

2018

Driver Identification Based on Stop-and-Go Events Using Naturalistic Driving Data

Zhen Gao, Longqi Li, Jinsong Feng, Rongjie Yu, Xuesong Wang, Changqing Yin

International Symposium on Computational Intelligence and Design

DOI

2018

Utilizing Multilayer Perceptron Neural Network for Crash Risk Prediction Based on a Full Set of Data

Yi Gao, Zhen Gao, Rongjie Yu, Zhiqing Huang, Jinsong Feng

CICTP 2018

DOI

2018

Utilizing Ensemble Learning Methods in Real-Time Traffic Crash Prediction

Mengdi Xue, Jie Huang, Zhen Gao, Sun Ping

CICTP 2018

DOI

2018

The Impacts of Data on Spatial Transferability on a Crash Risk Prediction Model

Zhen Gao, Shuyun Yu, Min Wang, Rongjie Yu, Xuesong Wang

CICTP 2018

DOI

2018

Research on Automated Modeling Algorithm Using Association Rules for Traffic Accidents

Zhen Gao, R Martin Du Pan, Rongjie Yu, Xuesong Wang

IEEE International Conference on Big Data and Smart Computing (BigComp)

DOI

2017

Utilizing latent class logit model to predict crash risk

Zhiqiang Huang, Zhen Gao, Rongjie Yu, Xuesong Wang, Kui Yang

IEEE/ACIS International Conference on Computer and Information Science (ICIS)

DOI

2017

A hybrid approach for urban expressway traffic incident duration prediction with Cox regression and random survival forests models

Axiang Ke, Zhen Gao, Rongjie Yu, Min Wang, Xuesong Wang

IEEE/ACIS International Conference on Computer and Information Science (ICIS)

DOI

2016

Macro-level accident fatality prediction using a combined model based on ARIMA and multivariable linear regression

Zeyang Chen, Zhen Gao, Rongjie Yu, Min Wang, Ping Sun

DOI

高珍

精选作品

期刊论文

基于车载视觉的端到端驾驶员疲劳检测模型

Joint Multi-Agent Trajectory Prediction for Cooperative Vehicle Infrastructure System

Robust Hazardous Driving Scenario Detection for Supporting Autonomous Vehicles in Edge-Cloud Collaborative Environments

Hazardous Driving Scenario Identification with Limited Training Samples

Utilizing angle-based outlier detection method with sliding window mechanism to identify real-time crash risk

A Comprehensive Vision-Based Model for Commercial Truck Driver Fatigue Detection

A Lightweight VK-Net Based on Motion Profiles for Hazardous Driving Scenario Identification

Examining imbalanced classification algorithms in predicting real-time traffic crash risk

基于车辆方波脉冲时序图的交通流参数实时检测算法

Identifying High Risk Driving Scenarios Utilizing a CNN-LSTM Analysis Approach

Detecting Vehicle Interactions in Driving Videos via Motion Profiles

Driving Style Recognition Based on Lane Change Behavior Analysis Using Naturalistic Driving Data

Roadway Risk Map Establishment Based on Features of Roadway Design and Traffic Situation

Perceiving Driving Hazards in a Data-fusion Way Using Multi-Modal Net and Semantic Driving Trajectory

Exploring crash mechanisms with microscopic traffic flow variables: A hybrid approach with latent class logit and path analysis models

连续数据环境下的道路交通事故风险预测模型

Speeding Behavior Estimation Using Stop-and-Go Events Based on Velocity Data

Driver Identification Based on Stop-and-Go Events Using Naturalistic Driving Data

Utilizing Multilayer Perceptron Neural Network for Crash Risk Prediction Based on a Full Set of Data

Utilizing Ensemble Learning Methods in Real-Time Traffic Crash Prediction

The Impacts of Data on Spatial Transferability on a Crash Risk Prediction Model

Research on Automated Modeling Algorithm Using Association Rules for Traffic Accidents

Utilizing latent class logit model to predict crash risk

A hybrid approach for urban expressway traffic incident duration prediction with Cox regression and random survival forests models

Macro-level accident fatality prediction using a combined model based on ARIMA and multivariable linear regression

研究方向