Automated winter road surface condition monitoring system

对加拿大大多数负责冬季道路维护的运输机构来说，在暴风雪期间和之后监测冬季路面状况是必不可少的。有关路面状况的资料可用来评估维修服务的需要、比较不同处理方法的成效，以及评估承建商在不同维修场地提供的维修服务的质素。关于路面状况的实时信息对于道路使用者来说也是非常宝贵的，他们可以使用这些信息来改进他们的旅行和驾驶决策，如在哪里、何时和以什么方式旅行。目前，对冬季路面状况的监测大多是通过个人观察和人工记录完成的，在重复性、细节和及时性方面存在局限性。虽然传感器技术的最新发展，如连续摩擦测量设备(CFME)、基于网络的监控视频和光谱冰雪覆盖传感器，为快速和客观地评估路面状况提供了新的机会，但它们的实施成本高昂，空间覆盖和完整性有限。拟议的项目旨在进一步推进我们新的冬季路况监测解决方案，在基于云的无线和互联网技术平台上创新应用机器视觉、人工智能和数据融合技术。原型解决方案包括一个全自动数据收集单元，由GPS、摄像头、红外温度计以及与其他传感器的接口组成，例如耕作/盐渍状态。数据在车上处理，然后传输到中央服务器，在那里处理来自大量参与车辆的数据，以生成具有高空间、时间和横向覆盖的路面状况信息。这些完整信息的提供有可能深刻改变冬季维护做法，并将改善机动性、道路安全和环境保护，使所有加拿大人受益。

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.