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Citation |
Liu J, Khattak A. J. Intell. Transp. Syst. 2020; 24(1): 11-23. |
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Copyright |
(Copyright © 2020, Informa - Taylor and Francis Group) |
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DOI |
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PMID |
unavailable |
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Abstract |
Connected and automated vehicles (CAVs) are already part of the surface transportation system. In order for a CAV to operate safely, it needs information such as static data (high-resolution navigation maps) and real-time dynamics from various sensors, some of which exchange information with other vehicles or roadside units. High resolution navigation maps can integrate historical on-road driving performance data to help CAVs and drivers operating vehicles with low level automation make informed proactive decisions. This study proposes that navigation maps on CAVs come pre-installed with historical driving data and that they work together with real-time sensors to help CAVs plan maneuvers. Historical driving data offers insights about decisions made by drivers at locations along a route, e.g., where drivers often make sharp turns or where they accelerate and decelerate hard. A pre-installed record of historical driving decisions will support informed decision-making and proactively "warn" CAVs and drivers about potential hazards. This study explores location-based driving volatility as a key to improving safety through CAVs. Location-based volatility is a measure of historical driving performance, defined as the percentage of extreme maneuvers performed on a location in road network. For demonstration, we modeled and visualized real-world high-resolution geo-referenced data. The data comes from a connected vehicle safety pilot program in Ann Arbor, Michigan. We found measured location-based volatility is significantly related to safety outcomes. Therefore, location-based driving volatility can serve as a valuable piece of information to be added to navigation maps in CAVs in order to help them navigate volatile hot-spots. Language: en |
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Keywords |
Connected and automated vehicles; informed decision-making; location-based driving volatility; pre-installed data |