Real-time computing of pavement conditions in cold regions: A large-scale application with road weather information system
Real-time computing of pavement conditions in cold regions: A large-scale application with road weather information system
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DOI：
10.1016/j.coldregions.2021.103228
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发表时间：
2021-04
影响因子：
4.1
通讯作者：
Zhen Liu;J. Bland;Ting Bao;M. Billmire;Aynaz Biniyaz
中科院分区：
文献类型：
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作者：
Zhen Liu;J. Bland;Ting Bao;M. Billmire;Aynaz Biniyaz
路面条件包括路面温度、冻融深度以及随之而来的力学性能是路面性能和寿命的关键。例如，在覆盖美国一半面积的季节性冰冻地区，融化弱化是路面损坏的主要原因，这给纳税人带来了巨大的经济成本。近年来，由于弹簧负载限制（SLR）政策的改进，损害已经减轻。然而，从信息技术的角度来看，流行的SLR日期预测方法/工具仍然是原始的。这样的方法/工具是利用少量数据、劳动密集型观察和/或主观经验手动获得和/或实现的。本文报道了密歇根州交通部最近支持的一个项目，该项目旨在开发基于网络的路面状况预测和SLR决策支持工具：一个名为MDOTSLR的基于网络的应用程序。MDOTSLR能够以很小的延迟访问更多的数据，并自动化数据采集、处理和决策。本文将首先介绍支持该工具功能的数据创新和新模型。随后将是应用程序的主要功能（或服务），包括软件工程细节。与传统的无网络传输的工具相比，该工具能够真实的实时地自动获取和处理气象数据、GIS数据、道路气象信息系统数据和野外测量数据，从而使SLR预报更加准确和方便。该工具可以很容易地扩展或修改为其他道路机构，以立即节省道路维修的资金，并减少对当地交通和经济的干扰。
Pavement conditions including pavement temperatures, freezing and thawing depths, and the consequent mechanical performance are the key to the performance and longevity of the pavement. For example, thaw-weakening is a major cause of pavement damage in seasonally-frozen areas covering half of the U.S., leading to huge financial costs for taxpayers. In recent years, the damage has been lessened due to improved practices with Spring Load Restriction (SLR) policies. However, prevalent SLR date prediction methods/tools are still primitive from the perspective of information technology. Such methods/tools are obtained and/or implemented manually with small amounts of data, labor-intensive observations, and/or subjective experience. The paper reports what has been learned from a recent project supported by the Michigan Department of Transporation for the development of a web-based pavement condition prediction and SLR decision support tool: a web-based app called MDOTSLR. MDOTSLR enables access to much more data with little latency and automates data acquisition, processing, and decision making. In this paper, the data innovations and new models that support the functions of the tool will be first introduced. Followed will be the major functions (or services) of the app including software engineering details. Compared with traditional tools without web delivery, this web-based tool automates the acquisition and processing of weather data, GIS data, road weather information system data, and field measurements in real time and thus enables more accurate and convenient SLR predictions. The tool can be easily extended or modified for other road agencies for immediate financial savings in road maintenance and less disturbance to local transportation and economy.