Grant: Idea to Innovation
University of Waterloo
$123,250.00
Automated winter road surface condition monitoring system
EF 2012-13
Résumé
Monitoring of winter road surface conditions during and after a snow storm is essential for most transportation agencies in Canada who are responsible for winter road maintenance. Information on road surface conditions can be used to assess the need for maintenance service, compare the effectiveness of different treatment methods, and evaluate the quality of the maintenance services delivered by contractors across different maintenance yards. Real-time information on road surface conditions is also invaluable to the road users who can use the information to improve their travel and driving decisions such as where, when and in what mode to travel. Currently, monitoring of winter road surface conditions is mostly done through personal observations and manual recording, which is limited in repeatability, details and timeliness. While recent developments in sensor technologies such as continuous friction measurement equipment (CFME), web-based surveillance video, and spectroscopic snow and ice cover sensors have afforded new opportunities for quick and objective assessment of road surface conditions, they are costly for implementation and limited in spatial coverage and completeness. The proposed project is to further advance our new winter road condition monitoring solution featuring innovative applications of machine vision, artificial intelligence, and data fusion techniques on a platform of cloud-based wireless and Internet technologies. The prototype solution includes a fully automated data collection unit consisting of a GPS, a camera, an IR thermometer, and interfaces to other sensors such as plowing/salting status. The data are processed onboard and then transmit to a central server where data from a large number of participating vehicles is processed to generate road surface condition information that is of high spatial, temporal and lateral coverage. The availability of such complete information has the potential to profoundly change the winter maintenance practice and will benefit all Canadians with improved mobility, road safety, and environmental protection.
Programme
Idea to Innovation
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
435008-2012
Name nom
Fu, Liping
Department département
Civil & Environmental Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2012
Award amount
123250
Program id
I2IPJ
Program name en
Idea to Innovation
Program name fr
De l'idée à l'innovation
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
700
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Transportation systems and services
Area of application fr
Services et systèmes de transport
Research subject code
1003
Research subject group en
Civil engineering
Research subject group fr
Génie civil
Research subject en
Transportation engineering
Research subject fr
Génie du transport
Partie
1
Nb partie
1
Application title
Automated winter road surface condition monitoring system
Keyword
NSERC
Application summary
Monitoring of winter road surface conditions during and after a snow storm is essential for most transportation agencies in Canada who are responsible for winter road maintenance. Information on road surface conditions can be used to assess the need for maintenance service, compare the effectiveness of different treatment methods, and evaluate the quality of the maintenance services delivered by contractors across different maintenance yards. Real-time information on road surface conditions is also invaluable to the road users who can use the information to improve their travel and driving decisions such as where, when and in what mode to travel. Currently, monitoring of winter road surface conditions is mostly done through personal observations and manual recording, which is limited in repeatability, details and timeliness. While recent developments in sensor technologies such as continuous friction measurement equipment (CFME), web-based surveillance video, and spectroscopic snow and ice cover sensors have afforded new opportunities for quick and objective assessment of road surface conditions, they are costly for implementation and limited in spatial coverage and completeness. The proposed project is to further advance our new winter road condition monitoring solution featuring innovative applications of machine vision, artificial intelligence, and data fusion techniques on a platform of cloud-based wireless and Internet technologies. The prototype solution includes a fully automated data collection unit consisting of a GPS, a camera, an IR thermometer, and interfaces to other sensors such as plowing/salting status. The data are processed onboard and then transmit to a central server where data from a large number of participating vehicles is processed to generate road surface condition information that is of high spatial, temporal and lateral coverage. The availability of such complete information has the potential to profoundly change the winter maintenance practice and will benefit all Canadians with improved mobility, road safety, and environmental protection.