Automated Extraction of Grade Crossing Features from LIDAR Data - Phase 2

The summary for the Automated Extraction of Grade Crossing Features from LIDAR Data - Phase 2 Federal Grant is detailed below. It contains information such as the Catalog of Federal Domestic Assistance (CFDA) number, who is eligible for the grant, how much grant money will be awarded, important deadlines, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed in the Grant Announcement Contact section. If these sections are incomplete, please visit the website of the government agency that is offering this grant.


	Federal Grant Title:	Automated Extraction of Grade Crossing Features from LIDAR Data - Phase 2
	CFDA Number:	20.313
	CFDA Description:	Railroad Research and Development
	Federal Agency Name:	DOT Federal Railroad Administration
	Category of Funding Activity:	Science and Technology
	Category Explanation:	Information not provided
	Opportunity Category:	Discretionary
	Funding Opportunity Number:	FR-RRD-11-001
	Document Type:	Grants Notice
	Funding Instrument Type:	Grant
	Posted Date:	Jan 12, 2011
	Creation Date:	Jan 12, 2011
	Original Closing Date for Applications:	Feb 11, 2011 No Explanation
	Current Closing Date for Applications:	Feb 11, 2011 No Explanation
	Archive Date:	Mar 13, 2011
	Expected Number of Awards:	1
	Estimated Total Program Funding:	Information not provided
	Federal Grant Award Ceiling:	$100,000
	Federal Grant Award Floor:	$0
	Cost Sharing or Matching Requirement:	No

Applicants Eligible for this Grant: Others (see text field entitled "Additional Information on Eligibility" for clarification)
Additional Information on Eligibility: Only the University of Michigan is eligible to apply for this grant.
Grant Description: This is a continuation of grant DTFR53-09-G-00046 with the University of Michigan and will fund phase 2 of the work. Using LIDAR data the Grantee will develop algorithms to automatically detect and record grade crossing parameters and traffic control devices in the vicinity of railroad right-of-way
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