A Human-in-the-Loop Evaluation of ACAS Xu

被引:3
|
作者
Rorie, R. Conrad [1 ]
Smith, Casey [1 ]
Sadler, Garrett [2 ]
Monk, Kevin J. [1 ]
Tyson, Terence L. [1 ]
Keeler, Jillian [1 ]
机构
[1] NASA, Ames Res Ctr, Human Syst Div, Moffett Field, CA 94035 USA
[2] San Jose State Univ, Human Syst Div, Moffett Field, CA USA
关键词
unmanned aircraft systems; detect and avoid; collision avoidance;
D O I
10.1109/dasc50938.2020.9256618
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Detect and avoid (DAA) systems provide unmanned aircraft systems (UAS) with an alternative means of compliance with the see-and-avoid requirements associated with operations in the National Airspace System (NAS). Previous studies have examined the efficacy of different DAA alerting and guidance structures and formats. Prior research has also investigated the integration of DAA information with the alerting and guidance generated by the Traffic Alert and Collision Avoidance System (TCAS II). The next-generation replacement for TCAS II - the Airborne Collision Avoidance System X (ACAS X) - includes a variant to be used by UAS (ACAS Xu) that will provide both DAA and Collision Avoidance (CA) guidance. The alerting and guidance issued by ACAS Xu differs from previous DAA and CA systems, a result of new capabilities that were not available to earlier systems. Differences include the removal of warning-level DAA alerting and guidance, as well as the issuance of new types of CA guidance, referred to as Resolution Advisories (RAs). Whereas TCAS II only issues vertical RAs, ACAS Xu adds horizontal and blended (i.e., simultaneous vertical and horizontal) RAs. The current study assessed pilots' ability to respond to and comply with the DAA and RA alerting and guidance generated by ACAS Xu in a human-in-the-loop simulation. Sixteen active UAS pilots participated in the study and were tasked with responding to scripted DAA and RA traffic conflicts. Results showed that pilots were effective at making timely maneuvers against DAA threats. The proportion of losses of DAA well clear against noncooperative intruders was found to be significantly higher than the proportion of losses against cooperative intruders, a result of the limited declaration range of the simulated onboard RADAR. Results also demonstrated that pilots could consistently meet the five second response time requirement for initial RAs. Rapid responses to RAs had the corresponding effect of minimizing the severity of losses of DAA well clear. While pilots complied with initial RAs at a high rate, compliance dropped substantially when the target heading was updated during a horizontal RA. Pilot performance with ACAS Xu will be presented alongside results from prior DAA research.
引用
下载
收藏
页数:10
相关论文
共 50 条
  • [1] An embodiment paradigm in evaluation of human-in-the-loop control
    Froehner, Jakob
    Beckerle, Philipp
    Endo, Satoshi
    Hirche, Sandra
    IFAC PAPERSONLINE, 2019, 51 (34): : 104 - 109
  • [2] A human-in-the-loop haptic interaction with subjective evaluation
    Fang, Ying
    Qiao, Yangjun
    Zeng, Fanrong
    Zhang, Keke
    Zhao, Tiesong
    FRONTIERS IN VIRTUAL REALITY, 2022, 3
  • [3] An Introduction to ACAS Xu and the Challenges Ahead
    Manfredi, Guido
    Jestin, Yannick
    2016 IEEE/AIAA 35TH DIGITAL AVIONICS SYSTEMS CONFERENCE (DASC), 2016,
  • [4] Human-in-the-Loop SLAM
    Nashed, Samer B.
    Biswas, Joydeep
    THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2018, : 1503 - 1510
  • [5] Design and Evaluation of a Human-in-the-Loop Connected Cruise Control
    Chen, Zheng
    Park, Byungkyu Brian
    Hu, Jia
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (08) : 8104 - 8115
  • [6] Fitts' Evaluation of a Developed Human-in-the-Loop Assistive Device
    Antunes, Rui Azevedo
    Palma, Luis Brito
    2020 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS (MEMEA), 2020,
  • [7] Human-in-the-Loop Mixup
    Collins, Katherine M.
    Bhatt, Umang
    Liu, Weiyang
    Piratla, Vihari
    Sucholutsky, Ilia
    Love, Bradley
    Weller, Adrian
    UNCERTAINTY IN ARTIFICIAL INTELLIGENCE, 2023, 216 : 454 - 464
  • [8] Human-in-the-loop speech-design system and its evaluation
    Kondo, Daichi
    Morise, Masanori
    2019 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2019, : 608 - 612
  • [9] Human-in-the-Loop Insulin Dosing
    Bequette, B. Wayne
    JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, 2021, 15 (03): : 699 - 704
  • [10] Human-in-the-Loop Data Collection and Evaluation for Improving Mathematical Conversations
    Datta, Debajyoti
    Phillips, Maria
    Bywater, James P.
    Lilly, Sarah
    Chiu, Jennifer
    Watson, Ginger S.
    Brown, Donald E.
    ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS AND DOCTORAL CONSORTIUM, PT II, 2022, 13356 : 551 - 554