Exploring the use of LIDAR data from Autonomous Cars for Estimating Traffic Flow Parameters and Vehicle Trajectories
| 项目名称： | Exploring the use of LIDAR data from Autonomous Cars for Estimating Traffic Flow Parameters and Vehicle Trajectories |
| 摘要： | Autonomous vehicles are typically equipped with LIDAR or other similar sensors to detect obstacles in the surrounding environment. LIDAR also provides a means to detect and track other vehicles around the autonomous car. The main goal of this proposed study is to estimate traffic flow parameters along the path of the autonomous car from the point-cloud data generated by the LIDAR. The specific goals of the proposed research are: (1) Collect sample LIDAR data under different traffic conditions on freeways and urban arterials in Hampton Roads; (2) Develop algorithms to detect vehicles around a LIDAR-equipped car and classify them based on vehicle size; (3) Develop algorithms to track other vehicles while within the LIDAR range; and (4) Estimate macroscopic traffic flow parameters based on the detected vehicles along the path of the LIDAR-equipped vehicle. Expected benefits and impacts: (1) New algorithms and methods will be developed to extract traffic flow information from raw LIDAR data; and (2) The developed methods will make it possible to gather massive and detailed data on traffic flow and driving behavior (e.g., car following). This can benefit a variety of applications including microscopic simulation model development and calibration, safety studies, estimation of temporal and spatial traffic flow conditions, etc. |
| 状态： | Completed |
| 资金： | 200000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | Mid-Atlantic Transportation Sustainability Center |
| 项目负责人： | Burden, Lindsay Ivey |
| 执行机构： | Old Dominion University |
| 主要研究人员： | Cetin, Mecit |
| 开始时间： | 20151001 |
| 预计完成日期： | 0 |
| 实际结束时间： | 20170930 |
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