The records for buried infrastructure are often unavailable, incomplete, and inaccurate, which can cause a number of hazards to the public. With buried pipelines, for example, between 1998 and 2017 there were 5,714 significant incidents that occurred in the US that resulted in 306 fatalities, 1260 injuries, and more than $7 billion in property damage. About 40 percent of the incidents were related to poor locating practice. There is an important effort underway to make sure that the subsurface infrastructure—the city’s vital functions of water, electricity, and sewer system, for example—can be accurately mapped. However, mapping and labeling subsurface infrastructure are incredibly difficult because of the subsurface congestion, the limited mobility of sensor platforms, and the absence of data processing algorithms.
Assistant Professor Shuai Li is researching a way to map the cluttered subsurface environment by placing ground penetrating radar (GPR) on autonomous vehicles. As the world moves toward autonomous vehicles, which could represent 10–15 percent of cars on the road by the year 2040, the autonomous vehicles equipped with GPRs can be turned into mobile sensing systems to scan the city subsurface and be able to detect, locate, and characterize buried features. In turn, the unprecedented new data regarding the invariant underground landmarks can also help the localization and navigation of autonomous vehicles in unfavorable circumstances such as during and after hurricanes.
The project is also thought to contribute to improving the public science literacy and improving the technological education of users.