TRB 2016 Session Information
Doctoral Student Research in Transportation Safety (Workshop 146)
Sunday, January 10, 2016 9:00AM - 12:30PM Convention Center, 103A
Peter Savolainen, Iowa State University, presiding
Sponsored By:
Section - Safety (ANB00)
Standing Committee on Statistical Methods (ABJ80)
Standing Committee on Transportation Safety Management (ANB10)
Standing Committee on Safety Data, Analysis and Evaluation (ANB20)
Standing Committee on Truck and Bus Safety (ANB70)
Program Details
This workshop provides an opportunity for doctoral students who have completed, or are nearing completion of, their dissertations to present their cutting-edge transportation safety research findings to a broad audience. For practitioners and researchers in attendance, this session presents a snapshot of some of the ongoing, state-of-the-art safety research that is being conducted at top universities and research institutes around the world.
Presentations
Older Driver Crash Risk and Dementia
Laura Blanar, University of Washington, Presentation Number P16-2083
Bicyclist Exposure Estimation Based on Heterogeneous Demand Data Sources
Frank Proulx, University of California, Berkeley, Presentation Number P16-2084
Guidance as to Appropriate Sample Sizes for the Calibration or Estimation of Safety Performance Functions for Local Conditions
Timothy Barrette, Iowa State University, Presentation Number P16-2085
Causal Inference in Traffic Safety: Developing a Modified Empirical Bayes Before-After Methodology for Estimating Generalizable Crash Modification Factors
Jonathan Wood, Pennsylvania State University, Presentation Number P16-2086
A Multivariate Poisson Lognormal Model of Crashes by Crash Type and Crash Severity on Rural Two Lane Highway in Connecticut
Kai Wang, University of Connecticut, Presentation Number P16-2087
Microscopic Safety Evaluation and Prediction for Special Expressway Facilities
Ling Wang, University of Central Florida (UCF), Presentation Number P16-2088
Potential Effectiveness of Liability Rules and Automated Vehicles in Reducing Rear-End Crashes on Congested Freeways
Indrajit Chatterjee, University of Minnesota, Twin Cities, Presentation Number P16-2089
New Methods to Quantify the Effects of Red-Light Cameras at Signalized Intersections
Fatemeh Baratian Ghorghi, Auburn University, Presentation Number P16-2090
Traffic Signal Recognition from On-Board Front-View Videos
Dongxi Zheng, University of Wisconsin, Madison, Presentation Number P16-2091
Examining the Use of Regression Models for Developing Crash Modification Factors
Lingtao Wu, Texas A&M Transportation Institute, Presentation Number P16-2092
Improving the Methodology of Estimating Safety Effects of Proposed/Implemented Actions
Taha Saleem, Ryerson University, Presentation Number P16-2093
Effectiveness of Inexpensive Crash Countermeasures to Improve Traffic Safety
Subasish Das, University of Louisiana, Lafayette, Presentation Number P16-2094
Roadside Features in Crash Prediction Models: Data Collection and Evaluation
Mohammad Jalayer, Auburn University, Presentation Number P16-2095
Data-Driven Bayesian Method-Based Traffic Crash Driver Injury Severity Formulation, Analysis, and Inference
Cong Chen, University of New Mexico, Presentation Number P16-2096
Doctoral Student Research in Transportation Safety (Workshop 146)
Sunday, January 10, 2016 9:00AM - 12:30PM Convention Center, 103A
Peter Savolainen, Iowa State University, presiding
Sponsored By:
Section - Safety (ANB00)
Standing Committee on Statistical Methods (ABJ80)
Standing Committee on Transportation Safety Management (ANB10)
Standing Committee on Safety Data, Analysis and Evaluation (ANB20)
Standing Committee on Truck and Bus Safety (ANB70)
Program Details
This workshop provides an opportunity for doctoral students who have completed, or are nearing completion of, their dissertations to present their cutting-edge transportation safety research findings to a broad audience. For practitioners and researchers in attendance, this session presents a snapshot of some of the ongoing, state-of-the-art safety research that is being conducted at top universities and research institutes around the world.
Presentations
Older Driver Crash Risk and Dementia
Laura Blanar, University of Washington, Presentation Number P16-2083
Bicyclist Exposure Estimation Based on Heterogeneous Demand Data Sources
Frank Proulx, University of California, Berkeley, Presentation Number P16-2084
Guidance as to Appropriate Sample Sizes for the Calibration or Estimation of Safety Performance Functions for Local Conditions
Timothy Barrette, Iowa State University, Presentation Number P16-2085
Causal Inference in Traffic Safety: Developing a Modified Empirical Bayes Before-After Methodology for Estimating Generalizable Crash Modification Factors
Jonathan Wood, Pennsylvania State University, Presentation Number P16-2086
A Multivariate Poisson Lognormal Model of Crashes by Crash Type and Crash Severity on Rural Two Lane Highway in Connecticut
Kai Wang, University of Connecticut, Presentation Number P16-2087
Microscopic Safety Evaluation and Prediction for Special Expressway Facilities
Ling Wang, University of Central Florida (UCF), Presentation Number P16-2088
Potential Effectiveness of Liability Rules and Automated Vehicles in Reducing Rear-End Crashes on Congested Freeways
Indrajit Chatterjee, University of Minnesota, Twin Cities, Presentation Number P16-2089
New Methods to Quantify the Effects of Red-Light Cameras at Signalized Intersections
Fatemeh Baratian Ghorghi, Auburn University, Presentation Number P16-2090
Traffic Signal Recognition from On-Board Front-View Videos
Dongxi Zheng, University of Wisconsin, Madison, Presentation Number P16-2091
Examining the Use of Regression Models for Developing Crash Modification Factors
Lingtao Wu, Texas A&M Transportation Institute, Presentation Number P16-2092
Improving the Methodology of Estimating Safety Effects of Proposed/Implemented Actions
Taha Saleem, Ryerson University, Presentation Number P16-2093
Effectiveness of Inexpensive Crash Countermeasures to Improve Traffic Safety
Subasish Das, University of Louisiana, Lafayette, Presentation Number P16-2094
Roadside Features in Crash Prediction Models: Data Collection and Evaluation
Mohammad Jalayer, Auburn University, Presentation Number P16-2095
Data-Driven Bayesian Method-Based Traffic Crash Driver Injury Severity Formulation, Analysis, and Inference
Cong Chen, University of New Mexico, Presentation Number P16-2096
Big Data Analytics and Applications: Role of Artificial Intelligence and Machine Learning (Workshop 109)
Sunday, January 10, 2016 9:00AM - 12:00PM Convention Center, 152B
Mecit Cetin, Old Dominion University, presiding
Sponsored By:
Standing Committee on Artificial Intelligence and Advanced Computing Applications (ABJ70)
Standing Committee on Travel Survey Methods (ABJ40)
Standing Committee on Information Systems and Technology (ABJ50)
Standing Committee on Geographic Information Science and Applications (ABJ60)
Standing Committee on Statistical Methods (ABJ80)
Standing Committee on Transportation Demand Forecasting (ADB40)
Program Details
This workshop focuses on artificial intelligence and machine learning techniques for turning high volumes of fast-moving and diverse transportation data into useful information. Advanced data survey and analytics techniques and their applications to emerging big data sets (e.g., trajectory, social media, mobile sensing, and connected and automated vehicles) and the potential of big data in supporting needs such as performance measurement, forecasting, and real-time control are explored.
9:00AM – 10:00AM Introduction and Big Data Methods
Semantics and the City (9:05AM – 9:24AM)
Dr. Francisco Camara Pereira, ITSLab, Technical University of Denmark (DTU), ITSLab, Massachusetts Institute of Technology (MIT)
9:24AM – 9:42AM Data Science Ontology in the Era of Deep Learning
Dr. Nii O. Attoh-Okine, Professor, Department of Civil and Environmental Engineering, University of Delaware
9:42AM – 10:00AM Social Media and Its Relationship to Transit, Traffic and Accidents
Dr. Qing He, Stephen Still Assistant Professor in Transportation Engineering and Logistics, Department of Civil, Structural and Environmental Engineering, University at Buffalo, The State University of New York
10:00AM – 10:30AM Government Perspectives and Available Data
10:00AM – 10:15AM Safety Data Analysis and Exploring Big Data for Safety
James Pol, PE, PMP, Technical Director, FHWA Office of Safety Research & Development | U.S. Department of Transportation
10:15AM – 10:30AM ITS and Connected Vehicle Research Data Available on the Research Data Exchange
Dale Thompson, Senior Research Engineer, Enabling Technologies Team Leader, FHWA Office of Operations R&D, USDOT
10:30AM – 10:40AM Break
10:40AM – 11:30AM Industry and Applications
10:40AM – 10:57AM Next-Generation Location Services
Dr. Jane Macfarlane, Chief Scientist and Head of Research, HERE
10:57AM – 11:13AM Use of Big Data for Transportation Systems Analysis – Southern California Experience with RIITS Data
Dr. Xudong Jia, Professor and Chair, Department of Civil Engineering, California Polytechnic University, Pomona.
11:13AM – 11:30AM Advanced Modeling techniques to evaluate benefits of Connected Vehicle Technology
Balaji Yelchuru, Senior Associate at Booz Allen Hamilton
11:30AM – 12:00PM Discussion, Research Needs and Directions (all speakers)
Sunday, January 10, 2016 9:00AM - 12:00PM Convention Center, 152B
Mecit Cetin, Old Dominion University, presiding
Sponsored By:
Standing Committee on Artificial Intelligence and Advanced Computing Applications (ABJ70)
Standing Committee on Travel Survey Methods (ABJ40)
Standing Committee on Information Systems and Technology (ABJ50)
Standing Committee on Geographic Information Science and Applications (ABJ60)
Standing Committee on Statistical Methods (ABJ80)
Standing Committee on Transportation Demand Forecasting (ADB40)
Program Details
This workshop focuses on artificial intelligence and machine learning techniques for turning high volumes of fast-moving and diverse transportation data into useful information. Advanced data survey and analytics techniques and their applications to emerging big data sets (e.g., trajectory, social media, mobile sensing, and connected and automated vehicles) and the potential of big data in supporting needs such as performance measurement, forecasting, and real-time control are explored.
9:00AM – 10:00AM Introduction and Big Data Methods
Semantics and the City (9:05AM – 9:24AM)
Dr. Francisco Camara Pereira, ITSLab, Technical University of Denmark (DTU), ITSLab, Massachusetts Institute of Technology (MIT)
9:24AM – 9:42AM Data Science Ontology in the Era of Deep Learning
Dr. Nii O. Attoh-Okine, Professor, Department of Civil and Environmental Engineering, University of Delaware
9:42AM – 10:00AM Social Media and Its Relationship to Transit, Traffic and Accidents
Dr. Qing He, Stephen Still Assistant Professor in Transportation Engineering and Logistics, Department of Civil, Structural and Environmental Engineering, University at Buffalo, The State University of New York
10:00AM – 10:30AM Government Perspectives and Available Data
10:00AM – 10:15AM Safety Data Analysis and Exploring Big Data for Safety
James Pol, PE, PMP, Technical Director, FHWA Office of Safety Research & Development | U.S. Department of Transportation
10:15AM – 10:30AM ITS and Connected Vehicle Research Data Available on the Research Data Exchange
Dale Thompson, Senior Research Engineer, Enabling Technologies Team Leader, FHWA Office of Operations R&D, USDOT
10:30AM – 10:40AM Break
10:40AM – 11:30AM Industry and Applications
10:40AM – 10:57AM Next-Generation Location Services
Dr. Jane Macfarlane, Chief Scientist and Head of Research, HERE
10:57AM – 11:13AM Use of Big Data for Transportation Systems Analysis – Southern California Experience with RIITS Data
Dr. Xudong Jia, Professor and Chair, Department of Civil Engineering, California Polytechnic University, Pomona.
11:13AM – 11:30AM Advanced Modeling techniques to evaluate benefits of Connected Vehicle Technology
Balaji Yelchuru, Senior Associate at Booz Allen Hamilton
11:30AM – 12:00PM Discussion, Research Needs and Directions (all speakers)
Innovations in Statistical Methods for Transportation Researchers and Practitioners (Session 397)
Monday, January 11, 2016 3:45PM - 5:30PM Convention Center, 150B
Lectern Session
Panagiotis Anastasopoulos, University at Buffalo, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Reliability-Based Design Procedure for Top-Down Fatigue Cracking (16-2037)
Yared Dinegdae, KTH Royal Institute of Technology
Bjorn Birgisson, Royal Institute of Technology
Analysis of Rear-Ending Events on Congested Freeways Using Video-Recorded Shockwaves (16-4572)
Indrajit Chatterjee, University of Minnesota, Twin Cities
Quantifying Safety Effects of Rural Roadway Features Using Mixed Distribution Generalized Linear Models (16-6503)
Mohammad Razaur Shaon, University of Wisconsin, Milwaukee
Xiao Qin, University of Wisconsin, Milwaukee
Ordered Fractional Split Approach for Aggregate Injury Severity Modeling (16-6952)
Shamsunnahar Yasmin, McGill University
Naveen Eluru, University of Central Florida (UCF)
Jaeyoung Lee, University of Central Florida (UCF)
Mohamed Abdel-Aty, University of Central Florida (UCF)
Monday, January 11, 2016 3:45PM - 5:30PM Convention Center, 150B
Lectern Session
Panagiotis Anastasopoulos, University at Buffalo, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Reliability-Based Design Procedure for Top-Down Fatigue Cracking (16-2037)
Yared Dinegdae, KTH Royal Institute of Technology
Bjorn Birgisson, Royal Institute of Technology
Analysis of Rear-Ending Events on Congested Freeways Using Video-Recorded Shockwaves (16-4572)
Indrajit Chatterjee, University of Minnesota, Twin Cities
Quantifying Safety Effects of Rural Roadway Features Using Mixed Distribution Generalized Linear Models (16-6503)
Mohammad Razaur Shaon, University of Wisconsin, Milwaukee
Xiao Qin, University of Wisconsin, Milwaukee
Ordered Fractional Split Approach for Aggregate Injury Severity Modeling (16-6952)
Shamsunnahar Yasmin, McGill University
Naveen Eluru, University of Central Florida (UCF)
Jaeyoung Lee, University of Central Florida (UCF)
Mohamed Abdel-Aty, University of Central Florida (UCF)
Statistical Methods in Transportation (Session 638)
Tuesday, January 12, 2016 2:00PM - 3:00PM Convention Center, Hall E
Poster Session
Yiyi Wang, Montana State University, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Non-Gaussian Interrupted Time Series Regression Analysis for Evaluating the Effect of Smart Motorways on Road Traffic Accidents (16-0157)
Mohammed Quddus, Loughborough University
Investigating Fractal Characteristics in Crash Trends for Potential Traffic Safety Prediction (16-0494)
Kirolos Haleem, West Virginia Department of Transportation
Priyanka Alluri, Florida International University (FIU)
Albert Gan, Florida International University (FIU)
Flexible Modeling Approach Using Dirichlet Process Mixtures: Application to Municipality-Level Railway Grade Crossing Crash Data (16-1565)
Shahram Heydari, University of Waterloo
Liping Fu, University of Waterloo
Dominique Lord, Texas A&M Transportation Institute
Bani Mallick, Texas A&M Transportation Institute
Determining Contributory Factors Affecting Rear-end Crashes Using Hurdle Count Models
Mehdi Hosseinpour (16-1629)
Ahmad Shukri Yahaya, Universiti Sains Malaysia
Mohammad Reza Ahadi, Transportation Research Institute
Razie Asoodeh, Imam Khomeini International University
Hojr Momeni, Kansas State University
Development of Permanent Deformation Models for Granular Materials and Soils (16-2318)
Tania Avila-Esquivel, University of Costa Rica
Cristhy Araya-Porras, University of Costa Rica
José Aguiar-Moya, University of Costa Rica
Luis Loria-Salazar, University of Costa Rica
Use of Clustering Model and Adjusted Boxplot Model for Identification of Secondary Incidents (16-2882)
Hyoshin Park, University of Maryland
Ali Haghani, University of Maryland
Comparison of Confidence and Prediction Intervals for Different Mixed-Poisson Regression Models (16-4936)
John Ash, University of Washington
Yajie Zou
Dominique Lord, Texas A&M Transportation Institute
Yinhai Wang, University of Washington
Heterogeneity in Hybrid-Involved Crash Severities: Exploratory Analysis Using Hierarchical Mixed Logit Model with Hierarchical Hybrid Vehicle Attributes (16-5162)
Shuaiqi Huang, Pennsylvania State University
Puttipan Seraneeprakarn, Pennsylvania State University
Venkataraman Shankar, Pennsylvania State University
Modified Rank-Ordered Logit Model to Analyze Injury Severity of Occupants in Multivehicle Crashes (16-5382)
Shelley Bogue, Old Dominion University
Rajesh Paleti, Old Dominion University
Spatiotemporal Crash Rate Monitoring for Improving Highway Safety (16-5699)
Rupert Giroux, Florida Department of Transportation
Omer Vanli, Florida State University
Eren Ozguven, Florida A&M University - Florida State University
Unsupervised Cluster Method for Pavement Grouping Based on Multidimensional Performance Data (16-6643)
Shi Qiu, Beijing University of Technology
Shaofan Wang, Beijing University of Technology
Danny Xiao, University of Wisconsin, Platteville
Jinxi Zhang, Beijing University of Technology
Long Li
Development of a Comprehensive Fuzzy Cluster-Based HSID Technique (16-6957)
Ranja Bandyopadhyaya, National Institute of Technology, Patna
Sudeshna Mitra, Indian Institute of Technology
Correlated Random Parameter Marginalized Two-Part Model: An Application to Refined-Scale Longitudinal Crash Rate Data (16-3707)
Xiaoxiang Ma, Colorado State University
Suren Chen, Colorado State University
Feng Chen, School of Transportation Engineering Tongji University
Tuesday, January 12, 2016 2:00PM - 3:00PM Convention Center, Hall E
Poster Session
Yiyi Wang, Montana State University, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Non-Gaussian Interrupted Time Series Regression Analysis for Evaluating the Effect of Smart Motorways on Road Traffic Accidents (16-0157)
Mohammed Quddus, Loughborough University
Investigating Fractal Characteristics in Crash Trends for Potential Traffic Safety Prediction (16-0494)
Kirolos Haleem, West Virginia Department of Transportation
Priyanka Alluri, Florida International University (FIU)
Albert Gan, Florida International University (FIU)
Flexible Modeling Approach Using Dirichlet Process Mixtures: Application to Municipality-Level Railway Grade Crossing Crash Data (16-1565)
Shahram Heydari, University of Waterloo
Liping Fu, University of Waterloo
Dominique Lord, Texas A&M Transportation Institute
Bani Mallick, Texas A&M Transportation Institute
Determining Contributory Factors Affecting Rear-end Crashes Using Hurdle Count Models
Mehdi Hosseinpour (16-1629)
Ahmad Shukri Yahaya, Universiti Sains Malaysia
Mohammad Reza Ahadi, Transportation Research Institute
Razie Asoodeh, Imam Khomeini International University
Hojr Momeni, Kansas State University
Development of Permanent Deformation Models for Granular Materials and Soils (16-2318)
Tania Avila-Esquivel, University of Costa Rica
Cristhy Araya-Porras, University of Costa Rica
José Aguiar-Moya, University of Costa Rica
Luis Loria-Salazar, University of Costa Rica
Use of Clustering Model and Adjusted Boxplot Model for Identification of Secondary Incidents (16-2882)
Hyoshin Park, University of Maryland
Ali Haghani, University of Maryland
Comparison of Confidence and Prediction Intervals for Different Mixed-Poisson Regression Models (16-4936)
John Ash, University of Washington
Yajie Zou
Dominique Lord, Texas A&M Transportation Institute
Yinhai Wang, University of Washington
Heterogeneity in Hybrid-Involved Crash Severities: Exploratory Analysis Using Hierarchical Mixed Logit Model with Hierarchical Hybrid Vehicle Attributes (16-5162)
Shuaiqi Huang, Pennsylvania State University
Puttipan Seraneeprakarn, Pennsylvania State University
Venkataraman Shankar, Pennsylvania State University
Modified Rank-Ordered Logit Model to Analyze Injury Severity of Occupants in Multivehicle Crashes (16-5382)
Shelley Bogue, Old Dominion University
Rajesh Paleti, Old Dominion University
Spatiotemporal Crash Rate Monitoring for Improving Highway Safety (16-5699)
Rupert Giroux, Florida Department of Transportation
Omer Vanli, Florida State University
Eren Ozguven, Florida A&M University - Florida State University
Unsupervised Cluster Method for Pavement Grouping Based on Multidimensional Performance Data (16-6643)
Shi Qiu, Beijing University of Technology
Shaofan Wang, Beijing University of Technology
Danny Xiao, University of Wisconsin, Platteville
Jinxi Zhang, Beijing University of Technology
Long Li
Development of a Comprehensive Fuzzy Cluster-Based HSID Technique (16-6957)
Ranja Bandyopadhyaya, National Institute of Technology, Patna
Sudeshna Mitra, Indian Institute of Technology
Correlated Random Parameter Marginalized Two-Part Model: An Application to Refined-Scale Longitudinal Crash Rate Data (16-3707)
Xiaoxiang Ma, Colorado State University
Suren Chen, Colorado State University
Feng Chen, School of Transportation Engineering Tongji University
Committee Meeting Statistical Methodology Committee ABJ80
Tuesday, January 12, 2016 8:00AM - 12:00PM Marriott Marquis, Supreme Court (M4)
Linda Ng Boyle, University of Washington, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Agenda for the Committee Meeting (Click here)
Linda Boyle's Presentation at the Committee meeting (Click here)
Tuesday, January 12, 2016 8:00AM - 12:00PM Marriott Marquis, Supreme Court (M4)
Linda Ng Boyle, University of Washington, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Agenda for the Committee Meeting (Click here)
Linda Boyle's Presentation at the Committee meeting (Click here)
Using Naturalistic Driving Study Data for Road Safety Analysis: Connecting Crashes to Safety-Critical Events (Session 680)
Tuesday, January 12, 2016 3:45PM - 5:30PM Convention Center, 101
Lectern Session
Linda Boyle, University of Washington, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Naturalistic Driving Events: Safety-Critical or Just Supposedly Critical? (P16-0915)
Ronald Knipling, Safety for the Long Haul Inc.
Context-Sensitive Selection of Crash Surrogates for Naturalistic Driving Data (P16-0916)
Feng Guo, Virginia Polytechnic Institute and State University
Risk for Actual or Potential Crash Severity in Rear-end Versus Other Crash Types: The Good, the Bad, and the Ugly Speculation (P16-0917)
Jonas Bärgman, Chalmers University of Technology
Identifying Crashes and Safety-Critical Events with Common Etiology (P16-0918)
Paul Jovanis, Pennsylvania State University
Tuesday, January 12, 2016 3:45PM - 5:30PM Convention Center, 101
Lectern Session
Linda Boyle, University of Washington, presiding
Sponsored By:
Standing Committee on Statistical Methods (ABJ80)
Presentations
Naturalistic Driving Events: Safety-Critical or Just Supposedly Critical? (P16-0915)
Ronald Knipling, Safety for the Long Haul Inc.
Context-Sensitive Selection of Crash Surrogates for Naturalistic Driving Data (P16-0916)
Feng Guo, Virginia Polytechnic Institute and State University
Risk for Actual or Potential Crash Severity in Rear-end Versus Other Crash Types: The Good, the Bad, and the Ugly Speculation (P16-0917)
Jonas Bärgman, Chalmers University of Technology
Identifying Crashes and Safety-Critical Events with Common Etiology (P16-0918)
Paul Jovanis, Pennsylvania State University