Spatial Mapping of Winter Road Weather and Surface Conditions

冬季道路天气和表面状况的空间测绘

• 批准号: 558293-2020
• 负责人: Kwon, TaeJung
• 金额: $ 2.16万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705255
• 关键词: Spatial; Mapping; Winter; Road; Weather

Being a northern country, winter conditions are a problem that many Canadians face each year. They make for treacherous driving as the road conditions deteriorate by becoming snow-covered, ice-covered, or impassible due to inundation. To mitigate such effects, cities and road authorities strive to maintain these roads to the best of their abilities based on the information and experience on hand. However, the road network that needs to be monitored and maintained is vastly large, and the costs are high, adding to the difficulties they face when trying to service the roads while also keeping costs down. Acknowledging the gap in existing knowledge and methodologies, this project aims to develop a repeatable yet transferrable method for estimating road surface conditions using one of the most important highway intelligent transportation system facilities - road weather information systems (RWIS). The project utilizes big data and advanced modelling techniques to provide cities and maintenance workers with a tool they need to better assess their roads' conditions and mobilize winter road maintenance services in a timely manner. The beneficiaries of this project will be every Canadian, as roads are important for everyday life in the city. Delays and collisions are environmentally, economically, and societally costly; thus, it is in the best interest of everyone that the roads are serviced in a timely and economical way. Cities and road authorities will benefit from reduced costs while road users will enjoy safe driving experiences during winter. This will not only contribute to improving transportation safety and accessibility but also reducing environmental impacts and winter maintenance operational costs. Therefore, this project will help Canada lead the way in the advancement and development of marketable technologies and skills in the field of winter road maintenance, big data analysis, and advanced artificial intelligence techniques. The outcomes of this project will contribute to building up Canada's innovative academic reputation and industrial excellence while help further diversify and advance its economy.

作为一个北方国家，冬季条件是许多加拿大人每年都面临的问题。他们制造了 因积雪、结冰或无法通行而使路况恶化时的危险驾驶 由于洪水泛滥。为了减轻这种影响，城市和道路管理部门努力将这些道路保持在最好的状态 根据手头的信息和经验了解他们的能力。然而，需要的公路网 监控和维护非常大，成本也很高，增加了他们在尝试时面临的困难 在维护道路的同时也降低了成本。认识到现有知识的差距和 方法，这个项目旨在开发一种可重复但可转移的估计路面的方法 使用条件最重要的公路智能交通系统设施之一--道路天气 信息系统(RVI)。该项目利用大数据和先进的建模技术为城市提供 和维修工人使用他们需要的工具来更好地评估他们的道路状况，并动员冬季道路 维修服务及时到位。这个项目的受益者将是每一个加拿大人，就像道路一样 对城市的日常生活很重要。延误和冲突在环境、经济和社会方面都是 费用昂贵；因此，及时和经济地为道路提供服务符合每个人的最佳利益。 城市和道路当局将受益于成本的降低，而道路使用者将享受安全的驾驶体验 在冬天。这不仅有助于提高交通安全和可达性，而且还 减少环境影响和冬季维护运营成本。因此，这个项目将会有所帮助 加拿大在以下领域的市场技术和技能的进步和发展方面处于领先地位 冬季道路养护、大数据分析和先进的人工智能技术。其结果是 该项目将有助于建立加拿大创新的学术声誉和行业卓越 同时帮助进一步实现经济多元化和发展。