原文传递
Informed decision-making by integrating historical on-road driving performance data in high-resolution maps for connected and automated vehicles
| 题名： | Informed decision-making by integrating historical on-road driving performance data in high-resolution maps for connected and automated vehicles |
| 正文语种： | 英文 |
| 作者： | Jun Liu;Asad Khattak |
| 作者单位： | The University of Alabama;University of Tennessee |
| 关键词： | Connected and automated vehicles; location-based driving volatility; preinstalled data; informed decision-making |
| 摘要： | 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 performanee 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-instalied with historical driving data and that they work together with real-time sensors to help CAVs plan maneuvers. Historical drivi ng data offers in sights about decisi ons made by drivers at locations along a route, e.g., where drivers often make sharp turns or where they accelerate and decelerate hard. A preinstalled 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 performanee, 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. |
| 出版日期： | 2020 |
| 出版年： | 2020 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | Vol24 |
| 期： | No01-06 |
| 页码： | 11-23 |
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