Autonomous Flight Trajectory Control System for Drones in Smart City Traffic Management

被引:35
|
作者
Nguyen, Dinh Dung [1 ]
Rohacs, Jozsef [1 ]
Rohacs, Daniel [1 ]
机构
[1] Budapest Univ Technol & Econ, Dept Aeronaut & Naval Architecture, H-1111 Budapest, Hungary
关键词
autonomous drones; UAV; autonomous flight trajectory; inverse motion simulation; smart city integration; TRACKING CONTROL; SECURITY; GUIDANCE; PRIVACY; DESIGN; MODELS;
D O I
10.3390/ijgi10050338
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the integration of UAS in the smart city transportation systems is an actual task that requires radically new, sustainable (safe, secure, with minimum environmental impact and life cycle cost) solutions. The primary objective of this proposed option is the definition of routes as desired and commanded trajectories and their autonomous execution. The airspace structure and fixed routes are given in the global GPS reference system with supporting GIS mapping. The concept application requires a series of further studies and solutions as drone trajectory (or corridor) following by an autonomous trajectory tracking control system, coupled with autonomous conflict detection, resolution, safe drone following, and formation flight options. The second part of the paper introduces such possible models and shows some results of their verification tests. Drones will be connected with the agency, designed trajectories to support them with factual information on trajectories and corridors. While the agency will use trajectory elements to design fixed or desired trajectories, drones may use the conventional GPS, infrared, acoustic, and visual sensors for positioning and advanced navigation. The accuracy can be improved by unique markers integrated into the infrastructure.
引用
收藏
页数:27
相关论文
共 50 条
  • [21] IoT-based traffic prediction and traffic signal control system for smart city
    Neelakandan, S.
    Berlin, M. A.
    Tripathi, Sandesh
    Devi, V. Brindha
    Bhardwaj, Indu
    Arulkumar, N.
    [J]. SOFT COMPUTING, 2021, 25 (18) : 12241 - 12248
  • [22] Infrastructure of RFID-Based Smart City Traffic Control System
    Pawlowicz, Bartosz
    Salach, Mateusz
    Trybus, Bartosz
    [J]. AUTOMATION 2019: PROGRESS IN AUTOMATION, ROBOTICS AND MEASUREMENT TECHNIQUES, 2020, 920 : 186 - 198
  • [23] Smart Traffic Management System
    Miyim, Abubakar M.
    Mohammed, Mansur A.
    [J]. 2019 15TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTER AND COMPUTATION (ICECCO), 2019,
  • [24] SMART CITY INITIATIVE: TRAFFIC AND WASTE MANAGEMENT
    Ankitha, S.
    Nayana, K. B.
    Shravya, S. R.
    Jain, Lovee
    [J]. 2017 2ND IEEE INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ELECTRONICS, INFORMATION & COMMUNICATION TECHNOLOGY (RTEICT), 2017, : 1227 - 1231
  • [25] A Collaborative Safety Flight Control System for Multiple Drones
    Okutake, Tomoki
    Uchida, Noriki
    Yamamoto, Noriyasu
    [J]. 2016 10TH INTERNATIONAL CONFERENCE ON INNOVATIVE MOBILE AND INTERNET SERVICES IN UBIQUITOUS COMPUTING (IMIS), 2016, : 371 - 375
  • [26] Solus: An autonomous aircraft for flight control and trajectory planning research
    Atkins, EM
    Miller, RH
    Van Pelt, T
    Shaw, KD
    Ribbens, WB
    Washbaugh, PD
    Bernstein, DS
    [J]. PROCEEDINGS OF THE 1998 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 1998, : 689 - 693
  • [27] The wild west of drones: a review on autonomous-UAV traffic-management
    Rumba, Rudolfs
    Nikitenko, Agris
    [J]. 2020 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS'20), 2020, : 1317 - 1322
  • [28] Referenced Blockchain Approach for Road Traffic Monitoring in a Smart City using Internet of Drones
    Singh, Maninder Pal
    Singh, Amritpal
    Aujla, Gagangeet Singh
    Bali, Rasmeet Singh
    Jindal, Anish
    [J]. IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), 2022,
  • [29] Autonomous decentralized traffic management system
    Kitahara, F
    Kera, K
    Bekki, K
    [J]. 2000 INTERNATIONAL WORKSHOP ON AUTONOMOUS DECENTRALIZED SYSTEM, PROCEEDINGS, 2000, : 87 - 91
  • [30] A Convolution Neural Network Based VANET Traffic Control System in a Smart City
    Mathiane, Malose
    Tu, Chunling
    Adewale, Pius
    Nawej, Mukatshung
    [J]. INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023, 2024, 825 : 347 - 360