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Paper or Conference Session (S)s |
Shifts in Travel Behavior:
Where Are We Going and How Do We Know? Tenth Annual Travel Data User Forum
Ed Christopher, Federal Highway Administration, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems; Committee on Statewide Transportation Data and Information Systems; Committee on National Transportation Data Requirements and Programs
Is our travel behavior changing? Are millennials different from baby boomers? How do we know? What data do we have? What data do we need? Is it all just anecdotal? Come and join in this exciting discussion as the Travel Data Users Forum explores what some believe
may be a real change in travel behavior.
Panel Discussion: Millennials' Travel Behavior (P14-5134)
Steven E. Polzin, University of South Florida
Nancy McGuckin, Consultant
Heather Contrino, Federal Highway Administration
Gregory Mark Spitz, Resource Systems Group, Inc.
Evelyn Blumenberg, University of California, Los Angeles
Brian D. Taylor, University of California, Los Angeles
Open Discussion on Millennials' Travel Data (P14-7028)
Time Prediction and
Data Quality
Michael Daniel Fontaine, Virginia Center for Transportation Innovation and Research, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems; Committee on Highway Traffic Monitoring
This session covers recent research in travel time data. Methods to estimate travel times from point detectors, predict arterial travel times, filter data outliers, and assess data quality of travel time data streams are all reviewed.
Hybrid Model for Motorway Travel Time Estimation- Considering Increased Detector Spacing (14-2516)
Ashish Bhaskar, Queensland University of Technology, Australia
Ming Qu, Queensland University of Technology, Australia
Edward Chung, Queensland University of Technology, Australia
Jinwoo (Brian) Lee, Queensland University of Technology, Australia
Real-Time Prediction of Arterial Roadway Travel Times Using Data Collected by Bluetooth Detectors (14-4910)
Soroush Salek Moghaddam, University of Waterloo, Canada
Bruce Hellinga, University of Waterloo, Canada
Algorithm for Detecting Outliers in Bluetooth Data in Real Time (14-4925)
Soroush Salek Moghaddam, University of Waterloo, Canada
Bruce Hellinga, University of Waterloo, Canada
How Much GPS Data Do We Need? (14-4087)
Anthony D. Patire, Partners for Advanced Transit and Highways
Matthew Wright, Partners for Advanced Transit and Highways
Boris Prodhomme, Smart AdServer, France
Alexandre Bayen, University of California, Berkeley
Urban Transportation
Data Frontiers: New Uses and Applications
Catherine Theresa Lawson, State University of New York, Albany, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems; Committee on Statewide Transportation Data and Information Systems
Transportation has always been a data-rich environment. Now technological advances in storage, retrieval, algorithm development, and integration are opening up new lines of research and the development of cutting-edge applications. Topics covered in this poster
session include new uses of "big data," rail model calibration, freeway performance analysis, automated bottleneck detection, new approaches to data archiving, uses of the General Transit Feed Specification, and much more.
Relationship Between Travel-Related Feelings, On-Trip Activities, and Use of Different Transport Means in Urban Areas (14-4180)
Marco Diana, Politecnico di Torino, Italy
Arriving Next on Track 1: Online Geospatial Transit Performance Data Archive (14-4766)
Jonathan Makler, Oregon Transportation Research and Education Consortium
Morgan Harvey, Portland State University
Steve Callas, Tri-County Metropolitan Transportation District of Oregon
Kristin A. Tufte, Portland State University
Ryan Peterson, Portland State University
Applying General Transit Feed Specification to the Global South: Experiences in Mexico City and Beyond (14-5657)
Emily Eros, Massachusetts Institute of Technology
Shomik Raj Mehndiratta, World Bank
P. Christopher Zegras, Massachusetts Institute of Technology
Kevin Webb, Conveyal
Maria Catalina Ochoa, EMBARQ/World Resources Institute
Time-Space Diagram Revisited (14-1046)
Afian Anwar, Massachusetts Institute of Technology
Wei Zeng, Swiss Federal Institute of Technology, Zurich
Rail Transit Assignment Model Calibration Using Automated Fare Collection Data and Parallel Genetic Algorithm (14-2679)
Wei Zhu, Tongji University, China
Ruihua Xu, Tongji University, China
Yueping Jiang, Tongji University, China
Data-Driven Geospatial-Enabled Transportation Platform for Freeway Performance Analysis (14-3268)
Sa Xiao, University of Washington
Xiaoyue (Cathy) Liu, University of Utah
Yinhai Wang, University of Washington
Novel Approach for Analysis of Weather, Signal, and Recurrent Congestion Impacts on Urban Delay (14-4072)
M. Anil Yazici, City College of New York
Camille Kamga, City College of New York
Yohan Urie, Ecole Nationale des Travaux Publics de l'Etat, France
Current Practice of Acquiring Public Road Inventory Data in the United States (14-4003)
Yuxiao Zhou, Jackson State University
Yan Qi, University of Montana
James Fairly, Jackson State University
Feng Wang, Jackson State University
Automated Congestion Bottleneck Identification for MAP-21 Performance Measure Reporting Using Large Statewide Speed Data
Sets (14-4356)
John Wikander, Texas A&M Transportation Institute
William L. Eisele, Texas A&M Transportation Institute
David Lynn Schrank, Texas A&M Transportation Institute
Large-Scale Intelligent Transportation System Traffic Detector Data Archiving (14-5448)
Tao Qu, University of Wisconsin, Madison
Steven Parker, University of Wisconsin, Madison
Yang Cheng, University of Wisconsin-Madison
Bin Ran, University of Wisconsin, Madison
David A. Noyce, University of Wisconsin, Madison
Stretching Scarce Dollars Through Streamlined Processes and Partnerships: Prototype Implementation for a Unified, Intelligent,
and Sustainable Geolocation Process for Roadway Incidents (14-3207)
Ilir Bejleri, University of Florida
Daniel Brown, University of Florida
Preparing for MAP-21:
Measuring Travel Time and Travel Time Reliability
Karl Petty, Iteris, Inc., presiding
Sponsored by Committee on Urban Transportation Data and Information Systems; Committee on Highway Traffic Monitoring; Committee on Statewide Transportation Data and Information Systems
Because of the recent mandates in MAP-21, there is an increasing interest at the agency level in the accurate measurement and estimation of travel time and travel time reliability. This session covers research into the measurement, modeling, and prediction
of travel time and travel time reliability from different sensor sources; methods to detect and filter outlier data; and assessment of overall system data quality.
Stochastic Volatility Modeling Approach to Account for Uncertainties in Travel Time Reliability Forecasting (14-1066)
Yanru Zhang, University of Maryland, College Park
Ali Haghani, University of Maryland, College Park
Ranye Sun, Texas A&M University, College Station
Application of Finite Mixture of Regression Model with Varying Mixing Probabilities to Urban Arterial Travel Time Estimation (14-3924)
Peng Chen, Nagoya University, Japan
Kai Yin, Texas A&M University
Jian Sun, Tongji University, China
Highway Versus Urban Roads: Analysis of Travel Time and Variability Patterns Based on Facility Type (14-0768)
M. Anil Yazici, City College of New York
Camille Kamga, City College of New York
Kaan Ozbay, Rutgers University
Link and Route Travel Time Prediction Including Corresponding Reliability in an Urban Network Based on Taxi Floating-Car
Data (14-5560)
Mirsad Tulic, Austrian Institute of Technology
Dietmar Bauer, Austrian Institute of Technology
Wolfgang Scherrer, Vienna University of Technology, Austria
Agent-Based Modeling Approach to Predict Experienced Travel Times (14-3851)
Hao Chen, Virginia Polytechnic Institute and State University
Hesham Rakha, Virginia Polytechnic Institute and State University
Evaluation of Freeway Sensor Placement Based on Aggregation of Cellular Probe System and Loop Detectors (14-2734)
Shanglu He, Southeast University, China
Wei Wang, Southeast University,China
Jian Zhang, Southeast University,China
Fengping Zhan, Southeast University, China
Bin Ran, Southeast University, China
Travel Time Reliability using Hasofer Lind-Rackwitz Fiessler Algorithm and Kernel Density Estimation (14-3545)
Shu Yang, The University of Arizona
Arif Malik, Saint Louis University
Yao-Jan Wu, University of Arizona
Novel Three-Stage Framework for Short-Term Travel Time Prediction Under Normal and Abnormal Traffic Conditions (14-1114)
Fangce Guo, Imperial College London, United Kingdom
Rajesh Krishnan, Imperial College London, United Kingdom
John W. Polak, Imperial College London, United Kingdom
Framework to Predict Freeway Traffic Speed in Snowy Weather: Integration of Historical and Real-Time Patterns (14-1545)
Eunbi Jeong, Hanyang University, South Korea
Cheol Oh, Hanyang University, South Korea
Youngho Kim, Korea Transport Institute
Jisun Lee, Korea Transport Institute
Soyoung Jung, Hanyang University, South Korea
Recursive-Bayesian Inference Model for Dynamic Travel Time Estimation Using Fusion of Simulated Loop Detector and Probe
Data (14-3278)
Cui Mengying, Dalian University of Technology, China
Kai Liu, Dalian University of Technology, China
Jin Chen, Dalian University of Technology, China
Urban Arterial Road Travel Time Variability Modeling Using Burr Regression (14-5654)
Susilawati Susilawati, Padang Polytechnic, Indonesia
Michael Taylor, University of South Australia
Sekhar Venkata Chandra Somenahalli, University of South Australia
Retrieving Dynamic Origin-Destination Matrices from Bluetooth Data (14-1184)
Gabriel Michau, Queensland University of Technology, Australia
Alfredo Nantes, Queensland University of Technology, Australia
Edward Chung, Queensland University of Technology, Australia
Patrice Abry, Ecole Normale Superieure de Lyon, France
Pierre Borgnat, Ecole Normale Superieure de Lyon, France
Ashish Bhaskar, Queensland University of Technology, Australia
Assessment of Speed Information Based on Probe Vehicle Data: Case Study in New Jersey (14-4464)
Kitae Kim, New Jersey Institute of Technology
Dennis Motiani, New Jersey Department of Transportation
Lazar N. Spasovic, New Jersey Institute of Technology
Branislav Dimitrijevic, New Jersey Institute of Technology
Steven I-Jy Chien, New Jersey Institute of Technology
New Methods for Quality Assessment of Real-Time Traffic Information (14-2918)
Gerhard Huber, University of the German Federal Armed Forces, Munich
Klaus Bogenberger, University of the German Federal Armed Forces, Munich
Robert Lawrence Bertini, Portland State University
Enhanced Travel Time Outlier Filter for Real-Time Applications (14-0652)
Yaxin Hu, University of Waterloo, Canada
Bruce Hellinga, University of Waterloo, Canada
Virtual Sensors: Web-Based Real-Time Data Collection Methodology for Transportation Operation Performance Analysis (14-4119)
Ender Faruk Morgul, Rutgers University
Hong Yang, New York University
Abdullah Kurkcu, Rutgers State University
Kaan Ozbay, Rutgers University
Bekir Bartin, Rutgers University
Camille Kamga, City College of New York
Richard Salloum, Nokia
Big Data and Open Data
for Transportation Services and Public Engagement
Piyushimita (Vonu) Thakuriah, University of Glasgow, United Kingdom; Harvey
J. Miller, Ohio State University, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems; Committee on Geographic Information Science and Applications; Committee on Visualization in Transportation; Committee on Artificial Intelligence and Advanced Computing Applications;
Committee on Intelligent Transportation Systems
The workshop focuses on how open big data can facilitate transportation services and engagement through self-organization, cooperation, and activism. Sponsoring committee chairs are invited to give their perspectives. Topics include data analytics, information
extraction from user-generated content, machine-to-machine communications and Internet of Things, open data and civic hacking, volunteered geographic information, visualization of massively large data sets, and open source social software.
Perspectives on Big Data and Open Data (P14-5725)
Catherine Theresa Lawson, State University of New York, Albany
Adel W. Sadek, State University of New York, Buffalo
Matthew G. Karlaftis, National Technical University of Athens, Greece
James P. Hall, University of Illinois, Springfield
Panel 1: Open Data and Civic Hacking (P14-5728)
Harvey J. Miller, Ohio State University
Urban Digital Infomediaries (P14-6091)
Piyushimita (Vonu) Thakuriah, University of Glasgow, United Kingdom
New Approaches to Public Involvement: Open Source and Crowdsourcing (P14-5729)
Frank Hebbert, OpenPlans
Mission Possible: Convincing MPOs and DOTs to Open Their Data with Carrots, Not Sticks! (P14-5730)
Michael L. Pack, University of Maryland, College Park
Panel 2: Research in Open Big Data (P14-5731)
Piyushimita (Vonu) Thakuriah, University of Glasgow, United Kingdom
M2M Communications and Implications for Future Mobility (P14-5732)
Glenn Geers, National ICT Australia
Extracting Activity Patterns from Cellphones, Points of Interest, and Travel Survey Data (P14-5735)
Joseph Ferreira, Massachusetts Institute of Technology
Shan Jiang, Massachusetts Institute of Technology
Yi Zhu, Massachusetts Institute of Technology
Mi Diao, National University of Singapore
Investigating Spatial Big Data for Eco-routing Services (P14-5736)
Shashi Shekhar, University of Minnesota
Viswanath Gunturi, University of Minnesota
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Published Meeting - Committee (M)s |
TPM14-005
Urban Transportation
Data and Information Systems Committee
Catherine Theresa Lawson, State University of New York, Albany, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems
TPM14-017
Census for Transportation
Planning Subcommittee, ABJ30(1)
Clara Reschovsky, Metropolitan Washington Council of Governments; Mara
Kaminowitz, Baltimore Metropolitan Council, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems
The Subcommittee is a forum for those that use Federal demographic statistics in transportation planning, policy, and analysis. Our subjects include the U.S. Census, the American Community Survey, Census Transportation Planning Products (CTPP), and the Census
API. We discuss applications, data access, accuracy issues, and share innovative uses of data products. Subcommittee members work with data providers to ensure that Federal data products meet the needs of the transportation community.
TPM14-028
Computational Transportation
and Society Subcommittee, ABJ30(2)
Piyushimita (Vonu) Thakuriah, University of Glasgow, United Kingdom; Harvey
J. Miller, Ohio State University, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems
TPM14-030
Travel Time, Speed and
Reliability Joint Subcommittee of ABJ30, ABJ35
Karl Petty, Iteris, Inc.; Michael
Daniel Fontaine, Virginia Center for Transportation Innovation and Research, presiding
Sponsored by Committee on Urban Transportation Data and Information Systems
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