Abstract
Improvements in the safety performance and efficiency of the roadway transportation system are sought and realized through the deployment of Automated Driver Assistance Systems and higher-level vehicle automation systems. The consistent function of these systems depends largely on the ability of the vehicle sensors to accurately detect the roadway environment. This environment includes pavement markings and roadside delineation, the primary local offline source of information on roadway alignment. The Reading the Road Ahead workshops at the Transportation Research Board’s Automated Vehicles Symposium (AVS, 2016 through 2020) and Automated Road Transportation Symposium (ARTS, 2021) were convened to provide a platform for understanding the interactions of machine vision systems with traffic control devices, featuring expert presentations in the fields of machine vision, human factors, traffic engineering, and transportation safety performance.
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References
Pike, A.D.: LiDAR detection and sensor fusion opportunities for pavement markings. In: Proceedings of the Automated Vehicles Symposium, Orlando, Florida (2019)
Kuznicki, S., Katz, B.: Designing for consistency: matching applications to scenarios in the use of traffic control devices/pavement markings. In: Proceedings of the 5th International Symposium on Highway Geometric Design, Vancouver, BC, Canada (2015)
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Kuznicki, S.O. (2023). Six Years of Reading the Road Ahead: Supporting Roadway Automation with Traffic Control Devices. In: Meyer, G., Beiker, S. (eds) Road Vehicle Automation 9. ARTSymposium 2021. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-031-11112-9_11
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DOI: https://doi.org/10.1007/978-3-031-11112-9_11
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