• Transportation Research Board

      TRB 97th Annual Meeting

      January 7–11, 2018

    • Interactive Program

2018

Annual Meeting Event Detail




Poster Session 386

Advanced Modeling, Recognition, and Classification Methods in Transportation Applications

Monday 1:30 PM- 3:15 PM
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Poster
Loukas Dimitriou, University of Cyprus, presiding
Sponsored by:
Standing Committee on Artificial Intelligence and Advanced Computing Applications (ABJ70)

This session presents successful transportation applications of various modeling, recognition, and classification tools to traffic pattern recognition, vehicle and pedestrian recognition, connected vehicles, traffic metering, car following, travel behavior, driver behavior and response pattern, data imputing, transportation network reliability, transportation cost, delivery scheduling, shared mobility and ridesourcing, bridge performance, pavement analysis, and road surface condition classification.  Tools include reinforcement learning, deep Q networks, support vector machines, gradient boosting, long short-term memory, Bayesian regularization neural networks, random forest, convolutional neural networks, and others.


No agenda available

Title Presentation Number
Identifying Multimodal Conflicts with Machine Learning
Nancy Hui, University of Toronto
Matthew Roorda, University of Toronto
Eric Miller, University of Toronto
Show Abstract
18-00140
Automatic Background Filtering Method for Roadside Lidar Data
Jianqing Wu, University of Nevada, Reno
Hao Xu, University of Nevada, Reno
Yuan Sun, University of Nevada, Reno
Jianying Zheng, Soochow University
Rui Yue, University of Nevada, Reno
Show Abstract
18-00286
Rebalancing Shared Mobility-on-Demand Systems: A Reinforcement Learning Approach
Jian Wen, Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)
Patrick Jaillet, Massachusetts Institute of Technology (MIT)
Show Abstract
18-00441
Winter Road Surface Condition Recognition Using a Pretrained Deep Convolutional Neural Network
Guangyuan Pan, University of Waterloo
Liping Fu, University of Waterloo
Ruifan Yu, University of Waterloo
Matthew Muresan, University of Waterloo
Show Abstract
18-00838
An Implementation-Ready Approach for Multiple-Van Multicriteria Dynamic Demand Rebalancing at Bikeshare Stations
Jiangbo Yu, University of California, Irvine
Dingtong Yang, University of California, Irvine
Daisik Nam, University of California, Irvine
Sunghi An, University of California, Irvine
R. Jayakrishnan, University of California, Irvine
Show Abstract
18-01127
Distributed Optimization and Coordination Algorithms for Dynamic Traffic Metering in Urban Street Networks
Rasool Mohebifard, Washington State University
Ali Hajbabaie, Washington State University
Show Abstract
18-01312
A Novel Clustering Algorithm for Traffic Operational Analysis
Mohammed Almannaa, Virginia Polytechnic Institute and State University
Mohammed Elhenawy, Virginia Polytechnic Institute and State University
Hesham Rakha, Virginia Polytechnic Institute and State University
Show Abstract
18-01390
Machine Learning Versus Spatial Econometric Models: Modeling the Impact of Transportation Infrastructure on Real Estate Prices
Dimitrios Efthymiou, Technical University of Munich
Constantinos Antoniou, Technical University of Munich
Show Abstract
18-01718
Artificial Neural Network Models for Predicting Pavement Roughness of Flexible and Rigid Pavements
LEELA SAI PRAVEEN GOPISETTI
Mohammad Hossain, Bradley University
Suruz Miah, Bradley University
Kerrie Schattler, Bradley University
Show Abstract
18-01736
Evaluation of the Gradient Boosting of Regression-Trees Method on Estimating the Car-Following Behavior
Sina Dabiri, Virginia Polytechnic Institute and State University
Montasir Abbas, Virginia Polytechnic Institute and State University
Show Abstract
18-01813
Assessment of Bridge Performance Through Machine Learning Algorithms: A Comparative Study
Fiorella Mete, Northwestern University
Ying Chen, Northwestern University
Amanda Stathopoulos, Northwestern University
David Corr, Northwestern University
Show Abstract
18-02156
An Artificial Neural Network to Identify Pedestrians and Vehicles from Roadside 360-Degree Lidar Data
Junxuan Zhao, Texas Tech University
Hao Xu, University of Nevada, Reno
Dayong Wu, Texas Tech University
Hongchao Liu, Texas Tech University
Show Abstract
18-03129
Vehicle Reidentification in a Connected Vehicle Environment Using Machine Learning Algorithms
Zuoyu Miao, University of Arizona
Larry Head, University of Arizona
Byungho Beak, University of Arizona
Show Abstract
18-03664
Integrated Cooperative Adaptive Cruise Control and Machine Learning Algorithms for Intelligent Vehicles Near an Off-Ramp
Changyin Dong, Southeast University
Show Abstract
18-03671
Keeping Score: Incorporating Driver Behavior Scoring System with Connected Vehicles to Improve Traffic Service Quality
Ying Chen, Northwestern University
Zihan Hong, Northwestern University
Yang Wu, Northwestern University
Hani Mahmassani, Northwestern University
Show Abstract
18-03909
A Novel Approach to Missing Ramp Flow Imputation Using Machine Learning
Yuheng Kan, Zhejiang University
Show Abstract
18-04529
Clustering Driver Behavior Using Dynamic Time Warping and Hidden Markov Model
Ying Yao, Beijing University of Technology
Xiaohua Zhao, Beijing University of Technology
Yiping Wu, Beijing University of Technology
Yunlong Zhang, Texas A&M University
Jian Rong
Show Abstract
18-04540
A Novel Method of Mining Driving States via Latent Dirichlet Allocation Model
Zhijun Chen, Wuhan University of Technology
Hao Cai, Wuhan University of Technology
Yishi Zhang, Jinan University
Chaozhong Wu, Wuhan University of Technology
Bin Ran, University of Wisconsin, Madison
Show Abstract
18-04589
Performance Assessment of Urban Streets Adressing Improvement Issues for Automobile Mode of Transport
Suprava Jena, National Institute of Technology, Rourkela
Abhishek Chakraborty, IIT Kharagpur
Prasanta Bhuyan, National Institute of Technology, Rourkela
Show Abstract
18-04773
Gaussian Processes for Imputation of Missing Traffic Volume Data
Fabio Ramos, Federal University of Rio de Janeiro
Douglas Picciani, Federal University of Rio de Janeiro
Glaydston Ribeiro, Federal University of Rio de Janeiro
Heudson Mirandola, Federal University of Rio de Janeiro
Ivani Ivanova, Federal University of Rio de Janeiro
Saul Quadros, Federal University of Rio de Janeiro
Romulo Orrico Filho, Federal University of Rio de Janeiro
Leonardo Perim, DNIT-Brazil
Carlos Abramides, DNIT-Brazil
Show Abstract
18-04912
Accelerating Stochastic Assessment of Postearthquake Transportation Network Connectivity via Machine Learning–Based Surrogates
Mohammad Amin Nabian, University of Illinois, Urbana Champaign
Hadi Meidani, University of Illinois, Urbana Champaign
Show Abstract
18-05162
A Novel Graph Partitioning Technique for High-Performance, Agent-Based Simulation of Fine-Resolution Travel Behavior
Husain Aziz, Oak Ridge National Laboratory
Show Abstract
18-05808
Processing Large-Scale Video Data to Support Transportation Safety, Planning, and Operations: A Flexible Approach to Data Storage and Integration
Venktesh Pandey, University of Texas, Austin
Weijia Xu, University of Texas, Austin
Lei Huang, University of Texas, Austin
Si Liu, University of Texas, Austin
Natalia Ruiz-Juri, University of Texas
Show Abstract
18-06642
Selection of Highway Corridors Using Voronoi-Based Region Approximation and Artificial Intelligence Heuristics
Sushma Mb, Indian Institute of Technology, Bombay
Sandeepan Roy, Indian Institute of Technology, Bombay
Avijit Maji, Indian Institute of Technology, Bombay
Show Abstract
18-06735
Predicting the Number of Uber Pickups by Deep Learning
Chao Wang, University of California, Riverside
Peng Hao, University of California, Riverside
Guoyuan Wu, University of California, Riverside
Xuewei Qi, University of California, Riverside
Matthew Barth, University of California
Show Abstract
18-06738
Scheduling for Timely Passenger Delivery in a Large-Scale Ridesharing System
Yang Zhang, Uber Technologies, Inc.
Husheng Li, University of Tennessee, Knoxville
Hairong Qi, University of Tennessee, Knoxville
Lee Han, University of Tennessee, Knoxville
Christopher Cherry, University of Tennessee, Knoxville
Show Abstract
18-06786