Runway Centerline Deviation Estimation from Point Clouds using LiDAR Imagery

7th International Conference on Research in Airport Transportation, ICRAT, Mar 2016

Secure airport operations are an important part of the aviation safety, as about 20 percent of collisions between aircrafts and objects as well as about one third of fatal accidents occur on airfields. The older airports need to be modernized to better cope with increasing traffic and larger aircrafts. Determining proper separation distances or safety areas is part of the revision process. In addition, engineering, environmental and economic impacts have to be considered during such revisions. To support the redesign, statistically significant and representative data is needed, including driving patterns and various derived metrics, such as centerline deviations. Remote sensing technologies offer an effective way to collect large volume of data on aircraft movements at airfields. This study describes the initial results of a LiDAR-based multi-sensor system that is deployed around runways and taxiways to remotely observe aircraft movement. The primary objective is to derive the centerline deviation of moving aircrafts from point clouds. Benefits from these derivations may allow for greater understanding of aircraft movements in the runway environment, and provide data for evaluating the operational safety of various runway design specifications.

Koppanyi, Z., Toth, C. K, Young, S., "Runway Centerline Deviation Estimation from Point Clouds using LiDAR Imagery", ICRAT 2016 Conference, June 20-24, Research Gate 304345484