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Machine Vision System to Support Vehicle to Infrastructure (V21) Safety Applications

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: 6913G619C100047
Agency Tracking Number: 180FH1009II
Amount: $748,402.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 18-FH1
Solicitation Number: N/A
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-09-03
Award End Date (Contract End Date): 2021-09-05
Small Business Information
15400 Calhoun Dr Ste 190
Rockville, MD 20855-2814
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Huiping Li
 (240) 406-7614
Business Contact
 Mark James
Phone: (301) 294-5221
Research Institution

To keep drivers and passengers of vehicles safe, especially in rural areas with limited access to Information and Communications Technology (ICT), the DOT and the commercial automotive industry are keenly interested in machine vision based V2I and CAV technology to perform functions such as navigating assistance in areas where GPS or detailed maps are unavailable, caution and warning systems capable of recognizing unsafe conditions, and timely notification of changing road conditions. To address this interest, IAI has developed RB3S system in Phase I, with several demonstrated capabilities including: 1) Robust barcode road sign locating and recognition algorithm based on machine learning; 2) Integrated system with real-time recognition capability; 3) Dynamic road condition retrieval; and 4) testing on one-lane suburb roads.
In Phase II, IAI will refine and enhance the RB3S system for practical use in highway environments. Some of the proposed Phase II efforts include: 1) Detailed requirement analysis in real highway environments; 2) System ruggedization and miniaturization; 3) Improvement of the barcode recognition method under challenging image conditions with longer distance, and 4) Robust test in real multi-lane highway conditions in both suburb and urban environments.

* Information listed above is at the time of submission. *

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