five

HARVIS Non Stabilized Assistant flight simulation parameters

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://zenodo.org/record/5940204
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset regroups data from the test of the HARVIS Non Stabilised Approach assistant. The experiment consisted in testing the assistant in realistic conditions in single pilot operations on an A320 research simulator. The validation session with a participant was composed of 6 scenarios. 3 scenarios were played with the assistant support and 3 without it.  Pilots were seated in the left seat of the cockpit and were told to land on runway 25 of Paris Orly Airport. The Aircraft was positioned approximately at 7NM before runway threshold.  Initial conditions (A/C speed, position, flaps configuration, landing gear state, wind…) varied from one test to another impacting the difficulty of the approach.  Pilots were briefed about the meteorological situation on the approach before each test.  When ready, the test begun, and pilots had to manually control the A/C in Visual Meteorological Conditions with the objective to stabilize the A/C for landing.  The assistant provided alerting in case of diverging parameters and assisted the pilot in the go around decision-making at the stabilization gate (500ft above airport elevation). The participants were told to stabilize the A/C before stabilization point.  At stabilization point, participants had to follow assistant’s order unless they thought the order inappropriate. 1 file is provided for each test: analysis_flight_parameters_P00X_SX_(No)Harvis.csv Regroups the flight parameters recorded during each test. At each timestamp, each parameter have been analysed to see if there are within limits defined for the assistant. Each file is identified by a participant number "P00X", a scenario number "SX". If the participant was assisted by the assistant, the file is tagged with "Harvis", if not, the file is with "NoHarvis"
创建时间:
2022-02-02
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作