Reference number : GC-2017-Q1-03269, amendment number : , agreement type : G, recipient legal name : Kwon, Tae-Jung (University of Alberta), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Many regions in Canada are adversely affected by harsh winter weather conditions, which can have a detrimental impact on the safety and mobility of motorists, and thus significantly hinder our nation&rsquo;s economic growth and development. To mitigate the negative impacts of winter weather, this research program is proposed to address several important issues and challenges pertaining to winter transportation. In specific, my proposed research program consists of the following three research components: 1) Estimation and prediction of road and traffic conditions: The focus of this research component is on developing models, which can accurately estimate and predict road weather and traffic condition information over a complete set of analysis domains &ndash; space and time . Without loss of generality, the proposed research component will incorporate multiple innovative data sources such as remotely sensed satellite images (e.g., IKONOS), digital elevation models, connected-vehicles data, and stationary and mobile road weather conditions data (e.g., MARWIS). 2) Development of a comprehensive winter storm severity index: This research component is to take a state-of-the-art approach to the problem, which considers small spatial and temporal units as the building block for evaluating the severity of weather. The objective of this research is to create a set of winter severity indicators that are capable of capturing multiple perspectives, including material use, road safety, and mobility. 3) Transportation system optimization: The main objective of this research component is to develop and refine models and algorithms for optimizing various transportation systems with a specific focus on one of the most important highway intelligent transportation system (ITS) infrastructures - road weather information system (RWIS). Incorporating the two other research components described herein as inputs to this research component, the focus will be on how to best leverage the benefits of neighboring regions and provinces by considering the effects of their spatial demarcations when optimizing the system. The proposed research program entails both fundamental and applied research components. This research, in the long run, will generate a significant body of new and comprehensive knowledge to advance the field of winter transportation research that is essential for promoting more sustainable transportation system and environment. This research also comprises applied research components such as developing a winter maintenance decision support system that will benefit Canada and all Canadians with improved safety, mobility, and productivity during inclement weather events., program purpose french : Many regions in Canada are adversely affected by harsh winter weather conditions, which can have a detrimental impact on the safety and mobility of motorists, and thus significantly hinder our nation&rsquo;s economic growth and development. To mitigate the negative impacts of winter weather, this research program is proposed to address several important issues and challenges pertaining to winter transportation. In specific, my proposed research program consists of the following three research components: 1) Estimation and prediction of road and traffic conditions: The focus of this research component is on developing models, which can accurately estimate and predict road weather and traffic condition information over a complete set of analysis domains &ndash; space and time . Without loss of generality, the proposed research component will incorporate multiple innovative data sources such as remotely sensed satellite images (e.g., IKONOS), digital elevation models, connected-vehicles data, and stationary and mobile road weather conditions data (e.g., MARWIS). 2) Development of a comprehensive winter storm severity index: This research component is to take a state-of-the-art approach to the problem, which considers small spatial and temporal units as the building block for evaluating the severity of weather. The objective of this research is to create a set of winter severity indicators that are capable of capturing multiple perspectives, including material use, road safety, and mobility. 3) Transportation system optimization: The main objective of this research component is to develop and refine models and algorithms for optimizing various transportation systems with a specific focus on one of the most important highway intelligent transportation system (ITS) infrastructures - road weather information system (RWIS). Incorporating the two other research components described herein as inputs to this research component, the focus will be on how to best leverage the benefits of neighboring regions and provinces by considering the effects of their spatial demarcations when optimizing the system. The proposed research program entails both fundamental and applied research components. This research, in the long run, will generate a significant body of new and comprehensive knowledge to advance the field of winter transportation research that is essential for promoting more sustainable transportation system and environment. This research also comprises applied research components such as developing a winter maintenance decision support system that will benefit Canada and all Canadians with improved safety, mobility, and productivity during inclement weather events., agreement title english : Weather-Sensitive Intelligent Transportation System (ITS) Planning and Management, agreement title french : Weather-Sensitive Intelligent Transportation System (ITS) Planning and Management, agreement number : RGPIN, agreement value : 100000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada