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Intelligent networked sensors for increased traffic safety
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Our society needs to continuously perform transports of people and goods toensure that business is kept going. Every disturbance in the transportation ofpeople or goods affects the commerce and may result in economical losses forcompanies and society. Severe traffic accidents cause personal tragedies forpeople involved as well as huge costs for the society. Therefore the roadauthorities continuously try to improve the traffic safety. Traffic safety may beimproved by reduced speeds, crash safe cars, tires with better road grip andimproved road maintenance. The environmental effects from roadmaintenance when spreading de-icing chemicals need to be considered, i.e.how much chemicals should be used to maximize traffic safety and minimizethe environmental effects. Knowledge about the current and upcoming roadcondition can improve the road maintenance and hence improve traffic safety.This thesis deals with sensors and models that give information about the roadcondition.The performance and reliability of existing surface mounted sensors wereexamined by laboratory experiments. Further research involved field studies tocollect data used to develop surface status models based on road weather dataand camera images. Field studies have also been performed to find best usageof non intrusive IR technology.The research presented here showed that no single sensor give enoughinformation by itself to safely describe the road condition. However, the resultsindicated that among the traditional road surface mounted sensors only theactive freezing point sensor gave reliable freezing point results. Furtherresearch aimed to find a model that could classify the road condition indifferent road classes from existing road weather sensor data and road images.The result was a model that accurately could distinguish between the roadconditions dry, wet, snowy and icy. These road conditions are clearly dissimilarand are therefore used as the definition of the road classes used in this thesis.Finally, results from research regarding remote sensing IR technology showedthat it significantly improves knowledge of the road temperature and statuscompared to data from surface mounted sensors.

Abstract [sv]

Vårt samhälle bygger på att det finns effektiva transporter av människor ochvaror för att säkerställa att samhällets funktioner fungerar och att företagenkan genomföra sina affärer. Störningar i transporterna av människor och varorpåverkar handeln och kan leda till ekonomiska förluster för både företag ochvårt samhälle. Allvarliga trafikolyckor orsakar personliga tragedier för deinblandade samt stora kostnader för samhället. Det är med denna bakgrundsom vägmyndigheterna kontinuerligt arbetar med att förbättratrafiksäkerheten. Trafiksäkerheten kan förbättras genom att minskahastigheterna, se till att bilarna blir krocksäkra, krav på däck med bättreväggrepp och ett bättre vägunderhåll. Miljöeffekterna från vinterväghållningdär avisningsmedel sprids på vägarna måste beaktas, d.v.s. hur mycketkemikalier bör användas för att maximera trafiksäkerheten och minimeramiljöpåverkan. Denna avhandling handlar om sensorer och modeller som gerinformation om väglaget. En kunskap om aktuellt och kommande väglag kanförbättra väghållningen och därmed öka trafiksäkerheten.I avhandlingen har prestanda och tillförlitlighet hos befintliga vägmonteradesensorer granskats i laboratorieexperiment. Data från fältstudier har använtsför att utveckla modeller som kan ge information om vägytans status baseratpå meteorologiska mätdata och kamerabilder. Det har också genomförtsfältstudier för att utforska den fördelaktigaste användningen av beröringsfriinfraröd sensorteknik.Den forskning som presenteras här visar att ingen enskild givare ger tillräckliginformation för att säkert beskriva väglaget. Från de traditionella ytmonteradesensorerna drogs slutsatsen att den aktiva fryspunktsgivaren gav de mesttillförlitliga fryspunktsresultaten. Det vidare arbetet handlade om att hitta enmodell som skulle kunna klassificera vägförhållanden i olika vägklassergenom att utnyttja information från befintliga sensorer och kamerabilder.Detta arbete resulterade i en modell som tillförlitligt kan särskilja väglagentorr, våt, snöig och isig. Dessa väglag är väsentligt olika och har därför valtssom väglagsklasser i denna avhandling. Under en säsong genomfördes ävenfältförsök med beröringsfri infraröd mätteknik där det visade sig att denberöringsfria teknologin förbättrar kunskapen om vägbanans temperatur och vägbanans status.

Place, publisher, year, edition, pages
Östersund: Mid Sweden University , 2011. , 41 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 68
Keyword [en]
Road weather information systems (RWiS), Remote sensing, InfraRed, Computer models
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-14982Local ID: STCISBN: 978-91-86694-52-4 (print)OAI: oai:DiVA.org:miun-14982DiVA: diva2:460376
Supervisors
Available from: 2011-11-30 Created: 2011-11-30 Last updated: 2016-10-19Bibliographically approved
List of papers
1. Road status sensors: A comparison of active and passive sensors
Open this publication in new window or tab >>Road status sensors: A comparison of active and passive sensors
2009 (English)In: TS116: Weather monitoring, 2009Conference paper, Published paper (Refereed)
Abstract [en]

Knowledge of the road status and specifically knowledge of the freezing point of the road surface fluid is crucial in order to perform effective and environmentally safe road maintenance. Road status sensors installed in the road can be passive conductivity sensors or active freezing point sensors. In this paper the output from a passive and an active sensor has been studied when the sensors has been contaminated with common chemicals that can be present on the road surface such as oil, alcohol and glycol. The results indicated that only intelligent active sensors reliably can detect freezing points on the road surface.

Keyword
Road status, road status sensors, freezing point
National Category
Control Engineering
Identifiers
urn:nbn:se:miun:diva-10379 (URN)2-s2.0-84954470884 (Scopus ID)
Conference
ITS World Congress 2009
Available from: 2009-12-02 Created: 2009-11-23 Last updated: 2017-09-14Bibliographically approved
2. Road Condition Discrimination: using Weather Data and Camera Images
Open this publication in new window or tab >>Road Condition Discrimination: using Weather Data and Camera Images
2011 (English)In: 2011 14TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), IEEE conference proceedings, 2011, 1616-1621 p.Conference paper, Published paper (Refereed)
Abstract [en]

An intelligent way of determining the road condition is needed to perform an effective road maintenance that results in high accessibility of the road network and high traffic safety. The hypothesis is that data from existing meteorological sensors and camera images from Road Weather information Systems (RWiS) could be used to improve the road condition classification. Previous research has found that an image analysis alone can estimate the road condition. This paper aims to evaluate if an extensive dataset retrieved from a RWiS site is sufficient to give a more accurate road condition classification than one obtained with an image analysis alone. The study reveals that RWiS data gives additional information for discrimination of the road conditions compared to image analysis only.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011
Series
IEEE International Conference on Intelligent Transportation Systems-ITSC
Keyword
RWIS, Road Condition, Camera images
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14974 (URN)10.1109/ITSC.2011.6082921 (DOI)000298654700265 ()2-s2.0-83755174165 (Scopus ID)STC (Local ID)978-1-4577-2198-4 (ISBN)STC (Archive number)STC (OAI)
Conference
Conference: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Location: Campus George Washington Univ (GWU), Washington, DC Date: OCT 05-07, 2011
Available from: 2011-11-30 Created: 2011-11-29 Last updated: 2016-10-19Bibliographically approved
3. Infrared Thermometry in winter road maintenance
Open this publication in new window or tab >>Infrared Thermometry in winter road maintenance
2012 (English)In: Journal of Atmospheric and Oceanic Technology, ISSN 0739-0572, E-ISSN 1520-0426, Vol. 29, no 6, 846-856 p.Article in journal (Refereed) Published
Abstract [en]

There is significant interest among road authorities in measuring pavement conditions to perform appropriate winter road maintenance. The most common monitoring methods are based on pavement-mounted sensors. This study's hypothesis is that the temperature distribution in a pavement can be measured by means of a nonintrusive method to retrieve the topmost pavement temperature values. By utilizing the latest infrared (IR) technology, it is possible to retrieve additional information concerning both road temperatures and road conditions. The authors discovered that surface temperature readings from IR sensors are more reliable than data retrieved from traditional surface-mounted sensors during wet, snowy, or icyroad conditions. It was also possible to detect changes in the road condition by examining how the temperatures in wheel tracks and in between the wheel tracks differ from a reference dry road condition. The conclusion was that nonintrusive measurement of the road temperature is able to provide an increase in relation to the knowledge about both the road temperature and the road condition. Another conclusion was that the surface temperature should not be considered as being equal to the ground temperatures retrieved from traditional surface-mounted sensors except under conditions of dry, stable roadways. © 2012 American Meteorological Society.

Keyword
Infrared detectors, Measurement techniques, Road accidents, Traffic information systems
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14976 (URN)10.1175/JTECH-D-11-00071.1 (DOI)000305272100007 ()2-s2.0-84864765461 (Scopus ID)STC (Local ID)STC (Archive number)STC (OAI)
Available from: 2011-11-30 Created: 2011-11-29 Last updated: 2017-12-08Bibliographically approved
4. Classification of Road Conditions: From Camera Images and Weather Data
Open this publication in new window or tab >>Classification of Road Conditions: From Camera Images and Weather Data
2011 (English)In: 2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIMSA), IEEE conference proceedings, 2011, 91-96 p.Conference paper, Published paper (Refereed)
Abstract [en]

It is important to correctly determine road condition as it contains essential information for improving traffic safety. Knowledge about the road condition is used by maintenance personnel as a trigger for snow removal and deicing tasks. The presence of severe road conditions is also communicated as warnings and speed reduction recommendations to road users. Previous research shows that road images and data from Road Weather information Systems (RWiS) give enough information to identify road conditions, such as dry, wet, snowy, icy and tracks. The hypothesis of the new model was that it should be possible to develop a model that could classify road conditions from existing RWiS road weather data and road images. This paper proposes a model that gives a correct classification of the road conditions dry, wet, snowy and icy at an accuracy rate of 91% to 100%.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011
Keyword
Road accidents, Traffic information systems, classification algorithms
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14977 (URN)10.1109/CIMSA.2011.6059917 (DOI)000298805900017 ()2-s2.0-82955165719 (Scopus ID)STC (Local ID)978-1-61284-924-9 (ISBN)STC (Archive number)STC (OAI)
Conference
IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA)/IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems (VECIMS) Location: Univ Ottawa, Ottawa, CANADA Date: SEP 19-21, 2011
Available from: 2011-11-30 Created: 2011-11-29 Last updated: 2016-10-19Bibliographically approved

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