Weather-Sensitive Intelligent Transportation System (ITS) Planning and Management

天气敏感智能交通系统 (ITS) 规划和管理

• 批准号: RGPIN-2017-06448
• 负责人: Kwon, TaeJung
• 金额: $ 1.46万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=656209
• 关键词: Weather; Sensitive; Intelligent; Transportation; System

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'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 – 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.

加拿大的许多地区都受到冬季恶劣天气的不利影响，这可能对驾车者的安全和流动性产生不利影响，从而严重阻碍我国的经济增长和发展。为了减轻冬季天气的负面影响，本研究计划旨在解决与冬季运输有关的几个重要问题和挑战。具体而言，我提出的研究计划包括以下三个研究部分：1）道路和交通状况的估计和预测：该研究部分的重点是开发模型，可以准确地估计和预测道路天气和交通状况信息的一套完整的分析域-空间和时间。在不失一般性的情况下，拟议的研究部分将纳入多种创新数据来源，如遥感卫星图像（例如，IKONOS）、数字高程模型、联网车辆数据以及固定和移动的道路天气状况数据（例如，MARWIS）。2)开发一个综合的冬季风暴严重程度指数：这项研究的组成部分是采取最先进的方法来解决这个问题，它认为小的空间和时间单位作为评估天气严重程度的基石。这项研究的目的是创建一套冬季严重程度指标，能够捕捉多个角度，包括材料使用，道路安全和流动性。3)交通系统优化：该研究部分的主要目标是开发和完善优化各种交通系统的模型和算法，特别关注最重要的公路智能交通系统（ITS）基础设施之一-道路天气信息系统（RWIS）。将本文所述的其他两个研究组成部分作为本研究组成部分的投入，重点将是如何最好地利用邻近地区和省份的利益，在优化系统时考虑其空间划界的影响。拟议的研究计划包括基础和应用研究部分。从长远来看，这项研究将产生大量新的综合知识，以推动冬季运输研究领域的发展，这对促进更可持续的运输系统和环境至关重要。该研究还包括应用研究部分，例如开发冬季维护决策支持系统，该系统将使加拿大和所有加拿大人在恶劣天气事件期间获得更高的安全性、流动性和生产力。