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Sight Distance Object Analysis (SODA) V1.0

ABSTRACT: SODSoDAA (Sight Object Distance Analysis) is a user-friendly, automated tool to simulate a driver’s sight distance, developed by Oregon State University with support from the Pacific Northwest Regional University Transportation Center (PacTrans). The input to the program is a point cloud (ASPRS LAS v1.2 format) obtained by any of a variety of methods, such as a terrestrial, mobile, or airborne lidar, or structure from motion photogrammetric software applied to imagery. The developed simulation method enables users to virtually evaluate available sight distances in a 3D context considering a variety of objects, vehicle types, and multi-modal forms of transportation (e.g., bicycle, pedestrian). The SODA tool contains a simple interface which does not require the user to have extensive knowledge of the program and algorithms in order to successfully run it. This document explains the necessary tools to run the program.  Note that the software cannot account for visibility obstructions resulting from these objects.  Also, temporary noise such as passing cars and pedestrians ordinarily should be removed prior to analysis. 

 

Link to the Publication

Link to the program (full version including Matlab Runtime9.1)

Link to the program (small version)

Link to user manual and tutorial

Link to the test data set in international feet

Link to the test data set in meters

 

Developed by:                          Sponsored by:

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Road Marking Extraction (RoME) V1.2

RoME

ABSTRACT: RoME (Road Marking Extractor) is a user-friendly, automated tool to extract and assess lane markings, developed by Oregon State University with support from the Oregon Department of Transportation (ODOT). The inputs to the program are point cloud (ASPRS LAS v1.2 format) and trajectory (asciitrj) data obtained by a mobile lidar unit. The outputs provide retroreflectivity evaluations that can be utilized for informed decision making for maintenance of road markings. The RoME tool contains a simple interface which does not require the user to have extensive knowledge of the program in order to successfully run it. At this time, road markings should be able to be extracted from most mobile lidar systems; however, the radiometric calibration applied for retro-reflectivity evaluation is specific to Oregon DOT’s current mobile lidar system (Leica Pegasus:Two) and will not produce correct results for other systems.  Future releases may address these when radiometric calibrations have been completed and are integrated into the software.

 

Link to the Report and Publications (will be available soon)

Link to the program (full version including Matlab Runtime9.1)

Link to the program (small version)

Link to user manual, tutorial, and parameter sheet

Link to the test data set in international feet

Link to the test data set in meters

 

Developed by:                          Sponsored by:

logo_OSU              logo_ODOT