Abstract
Given the rapid pace of modern technological advancements, the public should expect and demand measurable improvements to highway safety. Yet, it is not so clear how much improvement may be anticipated. Government organizations such as the U.S. Department of Transportation (U.S. DOT) and National Highway Traffic Safety Administration (NHTSA) have already spent decades and millions of dollars researching proper markings, alerting systems, and safety distances to help reduce collisions and other incidents on public roadways. While clearly this effort has had great impact, there are limiting factors that continually constrain the ability of traditional methods to significantly reduce the number of collisions. Such factors include driver behavior aspects such as reaction time, sudden maneuvers, and traffic violations, plus infrastructure aspects such as malfunctioning signals, inadequate signage, and non-standard road design. As increased numbers of connected and automated vehicles (CAV) are introduced into the traffic stream, and advanced safety applications are continually improving, the industry envisions a major decline in incidents across the board. This paper details the limiting factors to why a sizable reduction of incidents is not possible with conventional resources and introduces the framework for adding advanced warnings into connected safety applications in existing vehicles, such as red-light violation warning (RLVW), to achieve measurable results. Further, the paper then applies this same model for use within automated driving systems (ADS). More than just a technological examination, this paper also predicts the expected impact to roadway incidents.
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Acknowledgements
I thank my partner authors for all the time and effort they put into this study. In particular, I express my deepest thanks for the great research done by Varshini. We thank her graduate school, the University of Wisconsin, for training her well, and our colleagues, especially Dr. Alex Noble and Martha Eddy, who made this work possible.
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Baumgardner, G.M., Boyapati, R.K., Kamaraj, A.V. (2022). Effective Advanced Warning for Connected Safety Applications - Supplementing Automated Driving Systems for Improved Vehicle Reaction. In: Akhnoukh, A., et al. Advances in Road Infrastructure and Mobility. IRF 2021. Sustainable Civil Infrastructures. Springer, Cham. https://doi.org/10.1007/978-3-030-79801-7_19
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