Identifying overloaded vehicles on a highway is essential for the safety of vehicles on the road as well as for the performance monitoring of highway infrastructure and planning. Traffic enforcement uses various weigh-in-motion (WIM) methods. Since Vehicular Telematics (VT) is favoured in the transport industry, using it for building a new WIM system to infer the payload of a vehicle at any road segment would be beneficial for the transport industry. This paper presents the effort taken to use VT data from onboard diagnostics modules and smartphones to infer the payload of a vehicle. The experiment done to find the correlation between VT data and the payload of a vehicle is discussed. Feature engineering was done; nine different settings were tested to find the best regression model. A multiple nonlinear regression model produced significant a value of 6.322-08 and an -squared value of 0.8736. Results support the notion of using the VT data for nonintrusive measurement of the weight of a vehicle in motion.

中文翻译：

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车载远程信息处理运动称重系统的设计与开发

识别高速公路上的超载车辆对于道路上车辆的安全以及高速公路基础设施的性能监控和规划至关重要。流量执行使用各种动态加权（WIM）方法。由于车载远程信息处理（VT）在交通运输行业受到青睐，因此使用它来构建新的WIM系统以推断任何路段的车辆有效载荷对交通运输行业都是有益的。本文介绍了使用车载诊断模块和智能手机中的VT数据推断车辆有效载荷所付出的努力。讨论了为找到VT数据与车辆有效载荷之间的相关性而进行的实验。特征工程已经完成；测试了九种不同的设置以找到最佳的回归模型。多元非线性回归模型产生了显着的的6.322价值- 08和-的0.8736平方值。结果支持使用VT数据进行运动中车辆重量的非侵入式测量的概念。