• TRB 100th Annual Meeting - A Virtual Event

      January 24–28, 2021

    • Online Program

2021

Annual Meeting Event Detail




Poster Session 1314

1314 - Advancements in Road Weather Information

Wednesday, January 27 2:30 PM- 4:00 PM ET
Poster
Sponsored by:
Standing Committee on Road Weather (AKR50)

With the demand for timely, accurate and relevant road weather information increasing across the full range of transportation managers and users, it's important to keep abreast of the many advancements that are being made in this area. This session covers several different projects that explore new developments in road weather data processing, especially geospatial and geostatistical analyses, as well as road weather data uses for improved decision making.



No agenda available

Title Presentation Number
Diving Down the Rabbit Hole: RWIS Data to Develop a SWI
Natalie Villwock-Witte, Western Transportation Institute (WTI)
David Veneziano, Iowa State University
Karalyn Clouser, Western Transportation Institute (WTI)
Laura Fay, Western Transportation Institute (WTI)
Show Abstract
TRBAM-21-00210
Spatial Mapping of Winter Road Surface Conditions via Hybrid Geostatistical Techniques
Mingjian Wu, University of Alberta
Tae J. Kwon, University of Alberta
Liping Fu, University of Waterloo
Show Abstract
TRBAM-21-00464
Safety Effects of Road Weather Information System (RWIS) - A Cost-Benefit Analysis
Davesh Sharma, University of Alberta
Mingjian Wu, University of Alberta
Tae J. Kwon, University of Alberta
Show Abstract
TRBAM-21-01521
Regional Road Surface Temperature Estimation Using RWIS Dataset: A Comparison Between Ordinary Kriging, Empirical Bayesian Kriging and Regression Kriging Methods
Branislav Dimitrijevic, New Jersey Institute of Technology
Sina Darban Khales (sina.darban.khales@njit.edu), New Jersey Institute of Technology
Steven Chien, New Jersey Institute of Technology
Lazar Spasovic, New Jersey Institute of Technology
Show Abstract
TRBAM-21-03794
Winter Road Surface Conditions Classification using Convolutional Neural Network (CNN): Visible - Light and Thermal Images Fusion
Ce Zhang (ce.zhang@mail.mcgill.ca), McGill University
Ehsan Nateghinia, McGill University
Luis Miranda-Moreno, McGill University
Lijun Sun, McGill University
Show Abstract
TRBAM-21-03677

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