Modelling of winter road surface temperature (RST) — A GIS-based approach

Kwon, Tae J.; Gu, Lian

doi:10.1109/ictis.2017.8047820

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…For this study, the Iowa Environmental Mesonet database, maintained by Iowa State University, is the source of all environmental data used from the various data collection networks. One type of automated system used is the Road Weather Information System (RWIS) which is a collection of advanced meteorological instruments, road surface sensors, and a communication system in which it reports the local weather and road condition (24). Another weather information collection system used is the National Weather Service Cooperative Observer Program (NWS-COOP), which is a network of individuals that collect and record daily weather observations and is often used as a baseline to compare against remote sensing methods.…”

Section: Data Collection and Processingmentioning

confidence: 99%

Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

Wong

Kwon

2021

Transportation Research Record

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Winter driving conditions pose a real hazard to road users with increased chance of collisions during inclement weather events. As such, road authorities strive to service the hazardous roads or collision hot spots by increasing road safety, mobility, and accessibility. One measure of a hot spot would be winter collision statistics. Using the ratio of winter collisions (WC) to all collisions, roads that show a high ratio of WC should be given a high priority for further diagnosis and countermeasure selection. This study presents a unique methodological framework that is built on one of the least explored yet most powerful geostatistical techniques, namely, regression kriging (RK). Unlike other variants of kriging, RK uses auxiliary variables to gain a deeper understanding of contributing factors while also utilizing the spatial autocorrelation structure for predicting WC ratios. The applicability and validity of RK for a large-scale hot spot analysis is evaluated using the northeast quarter of the State of Iowa, spanning five winter seasons from 2013/14 to 2017/18. The findings of the case study assessed via three different statistical measures (mean squared error, root mean square error, and root mean squared standardized error) suggest that RK is very effective for modeling WC ratios, thereby further supporting its robustness and feasibility for a statewide implementation.

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Section: Data Collection and Processingmentioning

confidence: 99%

Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

Wong

Kwon

2021

Transportation Research Record

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“…Hence, a geographic information system (GIS) was used to process and extract the required data in an efficient manner. GIS are computer software packages that integrate user-friendly interfaces for storing, retrieving, analyzing, and visualizing all types of geographically referable data (Kwon and Gu 2017). Not only is GIS capable of dealing with vector and raster data, but it can also effectively process substantial numbers of geospatial datasets.…”

Section: Data Description and Processingmentioning

confidence: 99%

“…North America alone has more than 3,000 RWIS stations currently in operation, and is continuing to expand to improve their existing WRM services and maximize the return on their investments (Kwon and Gu 2017 Therefore, the main objective of this research is to develop a methodological framework to estimate RST using a geographic information system (GIS). Since road weather and surface conditions are generally affected by multiple facets that are very difficult to explain as they exhibit significant randomness, our primary focus will be on developing models related to nocturnal events with different road weather types.…”

Section: Introductionmentioning

confidence: 99%

A geostatistical approach to winter road surface condition estimation using mobile RWIS data

Kwon

Qiu

2019

Can. J. Civ. Eng.

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In winter, it is critical for cold regions to have a full understanding of the spatial variation of road surface conditions such that hot spots (e.g., black ice) can be identified for an effective mobilization of winter road maintenance operations. Acknowledging the limitations in present study, this paper proposes a systematic framework to estimate road surface temperature (RST) via the geographic information system (GIS). The proposed method uses a robust regression kriging method to take account for various geographical factors that may affect the variation of RST. A case study of highway segments in Alberta, Canada is used to demonstrate the feasibility and applicability of the method proposed herein. The findings of this study suggest that the geostatistical modelling framework proposed in this paper can accurately estimate RST with help of various covariates included in the model and further promote the possibility of continuous monitoring and visualization of road surface conditions.

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Snowplow Truck Performance Assessment and Feature Importance Analysis Using Machine-Learning Techniques

Liu

Wei

et al. 2021

J. Transp. Eng., Part A: Systems

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Modelling of winter road surface temperature (RST) — A GIS-based approach

Cited by 4 publications

References 9 publications

Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

A geostatistical approach to winter road surface condition estimation using mobile RWIS data

Snowplow Truck Performance Assessment and Feature Importance Analysis Using Machine-Learning Techniques

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