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.

路面状况（包括路面温度，冻结和解冻深度以及随之而来的机械性能）是路面性能和使用寿命的关键。例如，弱化是覆盖美国一半地区的季节性冻土地区行人道损坏的主要原因，这给纳税人带来了巨大的财务成本。近年来，由于采用了“弹簧负载限制”（SLR）策略改进了操作方式，减少了损坏。但是，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。此类方法/工具可通过少量数据，劳动密集型观察和/或主观经验手动获得和/或实施。该论文报告了从密歇根交通部最近的一个项目中学到的东西，该项目用于开发基于Web的路面状况预测和SLR决策支持工具：名为MDOTSLR的基于Web的应用程序。MDOTSLR能够以很少的延迟访问更多数据，并自动进行数据采集，处理和决策。在本文中，将首先介绍支持该工具功能的数据创新和新模型。随后是该应用程序的主要功能（或服务），包括软件工程详细信息。与没有网络交付的传统工具相比，该基于网络的工具可自动获取和处理天气数据，GIS数据，道路天气信息系统数据，实时实地测量，从而实现更准确，更方便的SLR预测。该工具可以轻松地扩展或修改为其他道路机构，以立即节省道路维护成本，并减少对当地交通和经济的干扰。