• TRB 100th Annual Meeting - A Virtual Event

      January 24–28, 2021

    • Online Program


Annual Meeting Event Detail

Poster Session 1353

1353 - Artificial Intelligence and Machine Learning Methods for Transportation Applications (Part II)

Thursday, January 28 10:00 AM- 11:30 AM ET
Jidong Yang, University of Georgia
Sponsored by:
Standing Committee on Artificial Intelligence and Advanced Computing Applications (AED50)

This session presents a variety of artificial intelligence and machine learning methods and tools that have been recently applied to solve problems and improve the operation and safety in a wide spectrum of transportation applications.  

No agenda available

Title Presentation Number
Modeling Route Choice Behavior: A Federated Learning Approach
Yonghyeon Kweon, University of Virginia
Bingrong Sun, National Renewable Energy Laboratory (NREL)
B. Brian Park, University of Virginia
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Prediction of Lane Change Maneuvers using the SHRP2 Naturalistic Driving Study Data: A Machine Learning Approach
Anik Das, University of Wyoming
Mohamed Ahmed, University of Wyoming
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Deep Learning to Detect Road Distress from Unmanned Aerial System Imagery
Long Truong, California State Polytechnic University, Pomona
Omar Mora, California State Polytechnic University, Pomona
Wen Cheng, California State Polytechnic University, Pomona
Hairui Tang, California State Polytechnic University, Pomona
Mankirat Singh, California State Polytechnic University, Pomona
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Automatic Vehicle Counting and Tracking in Aerial Video Feeds Using Cascade R-CNN and Feature Pyramid Networks
Yomna Youssef, Zewail City of Science and Technology
Mohamed Elshenawy, Zewail City of Science and Technology
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A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention
Muhammad Monjurul Karim, Stony Brook University
Yu Li, Stony Brook University
Ruwen Qin, Stony Brook University
Zhaozheng Yin, Stony Brook University
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A Deep Learning Model for Off-ramp Hourly Flow Estimation
Amir Nohekhan, University of Maryland, College Park
Sara Zahedian, University of Maryland, College Park
Ali Haghani, University of Maryland, College Park
Show Abstract
WeatherNet: Development of a Novel Convolutional Neural Network Architecture for Trajectory-Level Weather Detection Using SHRP2 Naturalistic Driving Data
MD Nasim Khan, University of Wyoming
Mohamed Ahmed, University of Wyoming
Show Abstract
Advancing Association Rule Base on Gini Impurity Statistic for P redicting Transportation Mode Choice
Jiajia Zhang, Dalian Maritime University
Tao Feng, Eindhoven University
Zhengkui Lin (zhengkuilin@dlmu.edu.cn), Dalian Maritime University
Harry Timmermans, Technische Universiteit, Eindhoven
Show Abstract
Evaluating Pedestrian Time-to-death in Fatal Pedestrian Crashes: Application of Explainable Machine Learning Using SHAP Technique
Iman Mahdinia, University of Tennessee, Knoxville
Amin Mohammadnazar, University of Tennessee, Knoxville
Asad J. Khattak, University of Tennessee
Show Abstract
Lane-Based Traffic Arrival Pattern Estimation Using License Plate Recognition Data
Chengchuan An (101300056@seu.edu.cn), Southeast University
Xiaoyu "Sky" Guo, Texas A&M University, College Station
Jingxin Xia, Southeast University
Zhenbo Lu, Southeast University
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Travel Behavior Modeling with Images
Shenhao Wang (shenhao@mit.edu), Massachusetts Institute of Technology (MIT)
Rachel Luo, Massachusetts Institute of Technology (MIT)
Xiaohu Zhang, Massachusetts Institute of Technology (MIT)
Hongzhou Lin, Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)
Joan Walker, University of California, Berkeley
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Quantized Convolutional Neural Network for Edge-based Parking Surveillance
Yifan Zhuang, University of Washington
Ziyuan Pu, University of Washington
Hao Yang, University of Washington
Yinhai Wang (yinhai@uw.edu), University of Washington
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Transportation Barriers and Cancer Patients’ Decision-making:  Investigating the Role of Travel in Continue or Stop Treatments
Roya Etminani-Ghasrodashti (roya.etminani@gmail.com), University of Texas, Arlington
Chen Kan, University of Texas, Arlington
Ladan Mozaffarian, University of Texas, Arlington
Show Abstract
Extraction of Construction Quality Requirements from Textual Specifications via Natural Language Processing
JungHo Jeon, Purdue University
Xin Xu, Purdue University
Yuxi Zhang, Purdue University
Liu Yang, Purdue University
Hubo Cai, Purdue University
Show Abstract
Fine-Tuning Time-of-Day Signal Timing Using Signal Performance Measures
Abolfazl Karimpour (karimpour@email.arizona.edu), University of Arizona
Mohammad Razaur Rahman Shaon, University of Connecticut
Yao-Jan Wu, University of Arizona
Show Abstract
Uncertainty Quantification with Deep Learning for Spatio-Temporal Travel Demand Prediction
Qingyi Wang, Massachusetts Institute of Technology (MIT)
Shenhao Wang (shenhao@mit.edu), Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)
Show Abstract
Deep Deterministic Policy Gradient based Cooperative Platoon Logitudinal Control Strategy
Yiming Yang, Chang'an University
Wuqi Wang, Chang'an University
Haigen Min (hgmin@chd.edu.cn), Chang'an University
Siyuan Gong, Chang'an University
Xiangmo Zhao, Chang'an University
Show Abstract
Deep Learning for the Detection and Recognition of Rail Defects in Ultrasound B-scan Images
Zhengxing Chen, Southwest Jiaotong University
Qihang Wang, Southwest Jiaotong University
Kanghua Yang, Southwest Jiaotong University
Jidong Yao, Shanghai Dongfang Maritime Engineering
Yong Liu, China Railway Chengdu Group Co
Ping Wang, Southwest Jiaotong University
Qing He, Southwest Jiaotong University
Show Abstract
TrafficNet: A Deep Neural Network for Traffic Monitoring Using Distributed Fiber-Optic Sensing
Chaitanya Prasad Narisetty, NEC Corporation
Tomoyuki Hino, NEC Corporation
Ming-Fang Huang, NEC Laboratories America Inc
Hitoshi Sakurai, NEC Corporation
Toru Ando, NEXCO Expressway Research Institute Company Limited
Shinichiro Azuma, Central Nippon Expressway Company Limited
Show Abstract
Driving Behavior Detection Using Semi-supervised LSTM and Smartphone Sensors
Pei Li, University of Central Florida
Mohamed Abdel-Aty, University of Central Florida
Zubayer Islam, University of Central Florida
Show Abstract
Network-wide Spatiotemporal Traffic Speed Imputation Using a Generative Adversarial Network
Garyoung Lee, Seoul National University
Eui-Jin Kim, Seoul National University
Dong-Kyu Kim (dongkyukim@snu.ac.kr), Seoul National University
Show Abstract
Computational Graph-based Framework for Integrating Econometric Models and Machine Learning Algorithms in Emerging Data-Driven Analytical Environments
Taehooie Kim (taehooie.kim@asu.edu), Arizona State University
Xuesong (Simon) Zhou, Arizona State University
Ram Pendyala, Arizona State University
Show Abstract
A novel spatio-temporal feature extraction method for short-term travel time predition in an urban network
Leilei Kang, Southwest Jiaotong University
Hao Huang, Southwest Jiaotong University
Guojing Hu, Jackson State University
Weike Lu, University of Alabama
Lan Liu, Southwest Jiaotong University
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Predicting Coordinated Actuated Traffic Signal Change Times using LSTM Neural Networks
Seifeldeen Eteifa, Virginia Polytechnic Institute and State University (Virginia Tech)
Hesham Rakha, Virginia Polytechnic Institute and State University (Virginia Tech)
Hoda Eldardiry, Virginia Polytechnic Institute and State University (Virginia Tech)
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Anisotropic Kernels for Deep Convolutional Neural Network based Traffic Speed Reconstruction
Bilal Thonnam Thodi, New York University, Abu Dhabi
Zaid Khan, New York University, Abu Dhabi
Saif Jabari (sej7@nyu.edu), New York University, Abu Dhabi
Monica Menendez, New York University, Abu Dhabi
Show Abstract
Mode Choice Modelling with Machine Learning: A Sequential Tour-based Approach for Addressing Imbalanced Datasets
Dimitrios Pappelis (d.pappelis.19@ucl.ac.uk), University College London
Emmanouil Chaniotakis, University College London
Maria Kamargianni, University College London
Show Abstract
Mining Heterogeneous Impact of Destination Attributes in Travel Demand Forecast for Different Urban Districts: A Deep Learning Approach
Shunhua Bai, University of Texas, Austin
Junfeng Jiao, University of Texas, Austin
Show Abstract
Modern Public Infrastructure Development Needs and Evaluation
Austin Dikas, Prairie View A&M University
Sarhan Musa, Prairie View A&M University
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