SBIR-STTR Award

There is a need and opportunity for an easily deployable, flexible, high-resolution system that can increase the speed, safety, and ease of evaluating grade crossings wherever they are found. Advancements in the capabilities of unmanned aerial systems (UAS or “drones”), combined with more flexible flight rules from the Federal Aviation Administration have been enabling more widespread testing and deployment of UAS for a variety of applications, including civil infrastructure inspection. This project is proposing evaluation and demonstration of a cost-effective UAS-based photogrammetry-enabled inspection system that would create detailed digital surface models useful for enabling automated grade crossing assessments. By comparing 3D data generation capabilities to governmental and industry design guidelines and recommendations, the project is designed to yield the needed proof-of-concept prototype UAS-based system. The system will include demonstrations of applying new and existing geospatial software tools to test and evaluate automated assessment capabilities. Included will be demonstrations of the ability of UAS-based photogrammetry to determine grade crossing profile’s slope and rate of change, determining visual sight lines, and detecting railway infrastructure on an automated basis. A final technical report will summarize the system and include a work plan for Phase II that will lead to a pre-production prototype ready for commercialization.

Drone–based assessment of rail grade crossings offers a great potential for rapid assessment of hang-up condition, visual sight line analysis, and crossing infrastructure. Through the Phase I SBIR, a proof-of-concept system was demonstrated at highway-rail crossings near Chelsea, MI with partner review. The collected imagery was processed through 3D photogrammetric software to produce high resolution digital elevation models (DEMs). It was demonstrated how the DEMs could be used for analysis of humped crossings and visual sight lines through a customized ArcGIS Pro workflow. Automated sign identification was demonstrated through use of an online machine learning tool. The Phase II SBIR project seeks to fully automate the Railroad Grade Crossing Viewshed and Automated Profile Assessment Tools as documented in the Phase I final report. With an emphasis on rapid drone data collection and the use of high accuracy GPS, MTRI Inc. seeks to provide commercially-available, timely, and accurate inspection of rail grade crossing and surrounding areas. The addition of a secure website will enable a user-friendly method for customers to request crossings to be inspected, send data to be analyzed by MTRI Inc., and receive all final products and reports based on the results of the automated tools.