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Road Condition Imaging: Model Development
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.ORCID iD: 0000-0001-9372-3416
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

It is important to classify road conditions to plan winter road maintenance, carry out proper actions and issue warnings to road users. Existing sensor systems only cover parts of the road surface and manual observations can vary depending on those who classify the observations. One challenge is to classify road conditions with automatic monitoring systems. This paper presents a model based on data from winter 2013-2014, retrieved from two installations in Sweden and Norway. To address that challenge an innovative and cost effective road condition imaging system, capable of classifying individual pixels of an image as dry, wet, icy or snowy, is evaluated. The system uses a near infra-red image detector and optical wavelength filters. By combining data from images taken from different wavelength filters it is possible to determine the road status by using multiclass classifiers. One classifier for each road condition was developed, which implies that a pixel can be classified to two or more road conditions at the same time. This multiclass problem is solved by developing a Bayesian Network that uses road weather information system data for the calculation of the probabilities for different road conditions.

Place, publisher, year, edition, pages
2015.
Keywords [en]
Road condition, Near Infra Red, classification, remote sensing, Bayesian Networks
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-24250Local ID: STCOAI: oai:DiVA.org:miun-24250DiVA, id: diva2:784398
Conference
Transportation Research Board 2015 Annual Meeting
Note

Paper number: 15-0885

Presented at the conference in Washington.

Available from: 2015-01-29 Created: 2015-01-29 Last updated: 2016-12-23Bibliographically approved
In thesis
1. Surface Status Classification, Utilizing Image Sensor Technology and Computer Models
Open this publication in new window or tab >>Surface Status Classification, Utilizing Image Sensor Technology and Computer Models
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

There is a great need to develop systems that can continuously provide correct information about road surface status depending on the prevailing weather conditions. This will minimize accidents and optimize transportation. In this thesis different methods for the determination of the road surface status have been studied and analyzed, and suggestions of new technology are proposed. Information about the road surface status is obtained traditionally from various sensors mounted directly in the road surface. This information must then be analyzed to create automated warning systems for road users and road maintenance personnel. The purpose of this thesis is to investigate how existing technologies can be used to obtain a more accurate description of the current road conditions. Another purpose is also to investigate how existing technologies can be used to obtain a more accurate description of the current road conditions. Furthermore, the aim is to develop non-contact technologies able to determine and classify road conditions over a larger area, since there is no system available today that can identify differences in road surface status in the wheel tracks and between the wheel tracks.

Literature studies have been carried out to find the latest state of the art research and technology, and the research work is mainly based on empirical studies. A large part of the research has involved planning and setting up laboratory experiments to test and verify hypotheses that have emerged from the literature studies. Initially a few traditional road-mounted sensors were analyzed regarding their ability to determine the road conditions and the impact on their measured values when the sensors were exposed to contamination agents such as glycol and oil. Furthermore, non-contact methods for determining the status of the road surface have been studied. Images from cameras working in the visible range, together data from the Swedish Transportation Administration road weather stations, have been used to develop computerized road status classification models that can distinguish between a dry, wet, icy and snowy surface. Field observations have also been performed to get the ground truth for developing these models. In order to improve the ability to accurately distinguish between different surface statuses, measurement systems involving sensors working in the Near-Infrared (NIR) range have been utilized. In this thesis a new imaging method for determining road conditions with NIR camera technology is developed and described. This method was tested in a field study performed during the winter 2013-2014 with successful results.

The results show that some traditional sensors could be used even with future user-friendly de-icing chemicals. The findings from using visual camera systems and meteorological parameters to determine the road status showed that they provide previously unknown information about road conditions. It was discovered that certain road conditions such as black ice is not always detectable using this technology. Therefore, research was performed that utilized the NIR region where it proved to be possible to detect and distinguish different road conditions, such as black ice. NIR camera technology was introduced in the research since the aim of the thesis was to find a method that provides information on the status of the road over a larger area. The results show that if several images taken in different spectral bands are analyzed with the support of advanced computer models, it is possible to distinguish between a dry, wet, icy and snowy surface. This resulted in the development of a NIR camera system that can distinguish between different surface statuses. Finally, two of these prototype systems for road condition classification were evaluated. These systems were installed at E14 on both sides of the border between Sweden and Norway. The results of these field tests show that this new road status classification, based on NIR imaging spectral analysis, provides new information about the status of the road surface, compared to what can be obtained from existing measurement systems, particularly for detecting differences in and between the wheel tracks.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2015. p. 104
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 219
Keywords
road condition, NIR, infrared, remote sensing, signal processing, classifiers
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-24828 (URN)STC (Local ID)978-91-88025-13-5 (ISBN)STC (Archive number)STC (OAI)
Public defence
2015-05-05, Q221, Akademigatan 1, Östersund, 10:15 (English)
Opponent
Supervisors
Available from: 2015-04-15 Created: 2015-04-14 Last updated: 2016-12-23Bibliographically approved

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Jonsson, PatrikThörnberg, BennyDobslaw, Felix

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