United States Department of Transportation
i
Automated Vehicle and Pavement Marking Evaluation in Connecticut
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2024-05-06
[PDF-5.64 MB]
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Edition:Final Report May 21, 2021 – June 30, 2024
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Abstract:The condition, visibility, and contrast of longitudinal pavement markings are critical to roadway safety and have been used for decades by infrastructure owner operators (IOOs) as a frame of reference to communicate to drivers how to navigate roadways. Over the last decade, vehicle manufacturers have also begun incorporating new intelligent, advanced driver assistance systems (ADAS) and sensors in their vehicles to further improve vehicle safety, performance and interactions between the driver and other roadway users. Is it wise to rely on the existing roadway markings to guide the new cars of today as well as the cars of the future? What are the minimum longitudinal marking requirements for driver assistance technologies to be successful in improving roadway performance and safety? This study explored the effect of longitudinal pavement marking quality using a variety of pavement marking performance levels on the detectability of pavement markings by machine vision systems. To evaluate the effect that various pavement marking characteristics have on machine vision detection, this study collected roadway lane marking characteristics and ADAS lane marking detection information on selected public roadways in Connecticut under various lighting conditions. All data using retroreflectometer and vehicles equipped with ADAS features and camera assembly were collected in three phases: pre-construction, during construction, and post-construction of lane marking improvements to evaluate the differences in ADAS machine vision lane marking detection in different lane marking width, color, contrast, and retroreflectivity. A data visualization tool was developed to visualize the lane marking characteristics. Outcomes from this study will be used to help the CTDOT and other IOOs determine the type, width, materials, and maintenance intervals of lane marking improvements to meet the demands of automated vehicles in the future.
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