Data and Methods to Estimate Connected and Automated Vehicle Penetration Rates
| 项目名称： | Data and Methods to Estimate Connected and Automated Vehicle Penetration Rates |
| 摘要： | Automated driving systems are becoming increasingly prevalent on Virginia roadways. These vehicles rely on radar, lidar, and machine vision to operate, and may detect road markings, barriers, and other vehicles in ways that human drivers do not. Vehicles may also leverage wireless communication to assist in driving, path planning, and communicating with roadside infrastructure. Recent research has investigated the impact of an increasingly connected and automated vehicle fleet on safety and capacity, but these estimates rely on accurate measurements of the volumes or proportions of vehicles on the road equipped with and utilizing these technologies. VDOT does not currently have a way to estimate the volume of connected (CV), automated (AV), or connected and automated (CAV) vehicles operating on Virginia roadways. The purpose of this project is to identify data required for VDOT to accurately estimate the proportion of vehicles equipped with and utilizing vehicle automation technologies that may affect safety and operations. This project will also consider practical ways to collect this data using both available data sources as well as potential additions to the current vehicle registration system. Benefits to VDOT include more accurate data on the rate of CAVs in the vehicle fleet, allowing the development and calibration of empirical models of the effect of CAVs on traffic flow, capacity, safety, and infrastructure planning. |
| 状态： | Active |
| 资金： | $67,699 |
| 资助组织： | Virginia Transportation Research Council |
| 执行机构： | Virginia Transportation Research Council |
| 主要研究人员： | Goodall, Noah J |
| 开始时间： | 20220725 |
| 预计完成日期： | 20230831 |
| 主题领域： | Data and Information Technology；Highways；Operations and Traffic Management；Planning and Forecasting；Safety and Human Factors；Vehicles and Equipment |
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