Integrated Sensor Unit for Signalized Intersections

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: 6913G619C100050
Agency Tracking Number: 180FH3005II
Amount: $998,540.93
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 180-FH3
Solicitation Number: N/A
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-09-27
Award End Date (Contract End Date): 2021-09-26
Small Business Information
1845 WEST 205TH STREET, TORRANCE, CA, 90501-1821
DUNS: 153865951
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Armen Gholian
 (310) 320-3088
Business Contact
 Keith Baker
Phone: (310) 320-3088
Research Institution
The DOT seeks an integrated unit capable of identifying and tracking individual vehicles with high accuracy using multiple vehicle detection inputs, including video images, radar-based detection, and vehicle-to-everything radio signal inputs (DSRC, cellular-V2X), with a deep learning-based engine to fuse collected data. To address this DOT need, Physical Optics Corporation (POC) proposes to continue the development of a new Deep Learning-based Vehicle Tracking with Multiple Sensors (DETRAM) system based on a deep learning engine. DETRAM uses multiple deep neural networks to extract intelligence from a diverse set of sensors and fuses information from this variety of signal sources to identify and track individual vehicles under all environmental conditions with a precision currently unmatched by state-of-the-art systems that use a subset of these signal sources. During Phase I, POC demonstrated DETRAM’s feasibility with a proof-of-concept design that included a concept of operations, systems requirement, systems design, data management platform, and prototype demonstration that successfully extracted accurate trajectories by fusing data streams from a camera and a radar. In Phase II, POC will optimize the DETRAM prototype to perform field operational tests in coordination with a state or local highway agency and demonstrate it at Turner-Fairbank Highway Research Center or elsewhere.

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

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