To keep drivers and passengers of vehicles safe, especially in rural areas with limited access to information and communications technology (ICT), the Department of Transportation (DOT) and the commercial automotive industry are keenly interested in machine vision based vehicle to infrastructure (V2I) and connected automated vehicle (CAV) technology to perform functions such as navigation assistance in areas where global positioning systems 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, the contractor has developed Reading Barcode Signs to Support V2I Safety (RB3S) system in Phase I, with several demonstrated capabilities including robust barcode road sign locating and recognition algorithm based on machine learning; an integrated system with real-time recognition capability; dynamic road condition retrieval; and testing on one-lane suburb roads.

In Phase II, the contractor will refine and enhance the RB3S system for practical use in highway environments. Some of the proposed Phase II efforts include detailed requirement analysis in real highway environments; system ruggedization and miniaturization; improvement of the barcode recognition method under challenging image conditions with longer distance, and robust tests in real, multi-lane highway conditions in both suburb and urban environments.

• 6913G619C100047

• Small Business Innovation Research

• FY 2002-2022 / Safety / Safety Data and Analysis

• Cooperative Automated Vehicles

• Volpe Center SBIR FY2019 Phase II Awards