Evaluation of Remote Sensing Technologies for Collecting Roadside Feature Data to Support Highway Safety Manual Implementation

摘要

Roadside feature data are critical inputs to highway safety models as described in the HighwaySafety Manual (HSM). Collecting safety-related roadside feature data is an important step forHSM implementation. Many state DOTs routinely collect data on roadside objects using avariety of sensing methods, and these programs often incur significant cost. At present, it isunknown which of these methods or any combination of these methods is capable of efficientlycollecting safety-related roadside feature data while minimizing cost and safety concern. Theobjective of this research is to identify required roadside feature data for various types ofhighway segments and to characterize the capability of existing sensing methods in contrast torequired roadside feature data through literature review and a nation-wide survey, and large-scalefield trials of selected sensing methods. The results of literature review and surveys are reportedin this paper. The findings of this research suggest that either mobile LiDAR or the combinationof video/photo log method with aerial imagery method is capable of collecting required HSMrelatedroadside information. However, due to the high data reduction effort, the current mobileLiDAR method needs significant improvement in the LiDAR data processing and featureextraction stage.