Browsing by Subject "Histograms"

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    Enhanced Capabilities of BullReporter and BullConverter
    (Minnesota Department of Transportation, 2017-09) Kwon, Taek M.
    Bull-Converter/Reporter is a software stack for Weigh-In-Motion (WIM) data analysis and reporting tools developed by the University of Minnesota Duluth for the Minnesota Department of Transportation (MnDOT) to resolve problems associated with deployment of multi-vendor WIM systems in a statewide network. These data tools have been used by the MnDOT Office of Transportation System Management (OTSM) since their initial delivery in 2009. The objective of this project was to expand the current conversion capabilities of BullConverter to include more raw data formats from different companies and the current BullReporter functions to include new analysis and reporting capabilities. Data analysis needs change over time, and the members of the OTSM WIM section identified several new functions that would increase efficiency and improve quality of WIM data. This report describes the new reporting and conversion functions implemented in this project.
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    Estimation of Vehicle's Lateral Position via the Lucas-Kanade Optical Flow Method
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-09) Yang, Jiann-Shiou
    The use of rumble strips on roads has proven to be an effective means of providing drivers lane departure warning (LDW). However, rumble strips require an infrastructure and do not exist on a majority of roadways. Furthermore, rumble strips present a difficult issue of where to establish the rumble-strip distance threshold. To develop an effective virtual rumble-strip LDW system where the rumble-strip threshold is allowed to vary according to the risk of the vehicle departing the road, it is essential to know the vehicle’s lateral characteristics; in particular, the vehicle’s lateral position and speed. In this report, we use image processing via an in-vehicle camera to estimate the vehicle’s lateral position and speed. The lateral position is estimated by determining the vehicle’s heading angle via a homography and the Lucas-Kanade optical flow techniques; while the lateral speed is determined via the heading angle and the vehicle’s On Board Diagnostic (OBD)-II forward speed data access. The detail of our approach is presented in this report together with our findings. Our approach will only need the minimal set of information to characterize the vehicle lateral characteristics, and therefore, makes it more feasible in a vehicle application.