@article{ref1,
title="Informed decision-making by integrating historical on-road driving performance data in high-resolution maps for connected and automated vehicles",
journal="Journal of intelligent transportation systems: technology, planning, and operations",
year="2020",
author="Liu, Jun and Khattak, Asad",
volume="24",
number="1",
pages="11-23",
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 &quot;warn&quot; 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.<p /> <p>Language: en</p>",
language="en",
issn="1547-2450",
doi="10.1080/15472450.2019.1699076",
url="http://dx.doi.org/10.1080/15472450.2019.1699076"
}