About the research
The weights and configurations of large vehicles traveling the primary interstate system are known with relative certainty due to the information collected at numerous weigh stations. It is uncommon, however, that farm-to-market vehicles and other implements of husbandry (IoH) travel the interstate system; thus, an accurate assessment of the characteristics of these vehicles is left unknown. Since these vehicles commonly travel rural roads, and often at weights exceeding the legal limit especially during harvest, an accurate understanding of low-volume road usage is necessary to properly plan for the near-term repair and replacement of structures and roadways; even more, the information collected will help improve the long-term performance and asset management activities.
A recently completed pooled-fund project, which the Iowa Department of Transportation (DOT) was the lead state on, looked to assess the impact of implements of husbandry on bridges. Those efforts produced valuable information especially as it relates to lateral load distribution. Even so, the project was largely completed using a database of virtual vehicles developed through information provided by equipment manufacturers and rule-of-thumb. Although it is believed the database generally represented current vehicles, the accuracy cannot be verified without direct measurement of all vehicles. Furthermore, one piece of missing information is the frequency with which those vehicles cross low-volume road bridges.
The objective of this project was to develop a portable weigh-in-motion system using a rural road bridge to estimate the characteristics of vehicles traveling these roads. A unique instrumentation setup was utilized with strain gages placed on the bottom face of the deck as well as on the top and bottom flanges of the girders, which allowed for the application of algorithms for vehicle classification determination. Further classification of the IoH vehicles is made possible by actual determination of specific vehicle type based on strain response and the corresponding number and spacing of axles. This vehicle information provides actual loading and corresponding bridge response and, thus, maintenance decisions and actual structural demands can be properly selected based on existing traffic types and frequencies. The system developed for this project can be deployed on rural bridges for realistic traffic classifications.