Parking Space Detection with Hierarchical Dynamic Occupancy Grids

被引:0
|
作者
Schmid, Matthias R. [1 ]
Ates, S. [2 ]
Dickmann, J. [2 ]
von Hundelshausen, F. [1 ]
Wuensche, H. -J. [1 ]
机构
[1] Univ Bundeswehr Munich, Autonomous Syst Technol TAS, Dept Aerosp Engn, Neubiberg, Germany
[2] Daimler AG, Ulm, Germany
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
an automatic parking system relies on precise estimation of parking space geometry. This paper proposes the use of a hierarchical three-dimensional occupancy grid for the detection of parking spaces. The occupancy grid covers the environment representation of the static world. A hierarchical design allows dynamic selection of the level of detail. Applying a three-dimensional grid provides the additional benefit of supporting a variety of other functions including height estimation using a single environment representation type [7]. The presented approach derives the distance to obstacles and walls and thus is able to represent the free space that forms parking spaces. In a second step, the dimensions of the parking space are calculated. For evaluation, real parking spaces are detected and estimated using short range radar sensors. The calculated dimensions are compared to the ground truth.
引用
收藏
页码:254 / 259
页数:6
相关论文
共 50 条
  • [1] A Review on Automatic Parking Space Occupancy Detection
    Singh, Twinkle
    Khan, Safdar Sardar
    Chadokar, Surendra
    2018 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATION AND TELECOMMUNICATION (ICACAT), 2018,
  • [2] A Bayesian hierarchical detection framework for parking space detection
    Huang, Ching-Chun
    Wang, Sheng-Jyh
    Chang, Yao-Jen
    Chen, Tsuhan
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 2097 - +
  • [3] Parking Space Occupancy Detection Using Deep Learning Methods
    Akinci, Fatih Can
    Karakaya, Murat
    2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
  • [4] An Analysis of Lightweight Convolutional Neural Networks for Parking Space Occupancy Detection
    Ellis, Joshua D.
    Harris, Anthony
    Saquer, Naseem
    Iqbal, Razib
    23RD IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM 2021), 2021, : 261 - 268
  • [5] A Hierarchical Bayesian Generation Framework for Vacant Parking Space Detection
    Huang, Ching-Chun
    Wang, Sheng-Jyh
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2010, 20 (12) : 1770 - 1785
  • [6] Dynamic Occupancy Grids for Object Detection: A Radar-Centric Approach
    Ronecker, Max Peter
    Schratter, Markus
    Kuschnig, Lukas
    Watzenig, Daniel
    2024 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2024), 2024, : 13991 - 13997
  • [7] A Real-Time Parking Space Occupancy Detection Using Deep Learning Model
    Prova, Raktim Raihan
    Shinha, Title
    Pew, Anamika Basak
    Rahman, Rashedur M.
    2022 IEEE INTERNATIONAL IOT, ELECTRONICS AND MECHATRONICS CONFERENCE (IEMTRONICS), 2022, : 51 - 57
  • [8] Video-based parking occupancy detection
    Deruytter, Michael
    Anckaert, Kevin
    VIDEO SURVEILLANCE AND TRANSPORTATION IMAGING APPLICATIONS, 2013, 8663
  • [9] Parking Occupancy Detection using Thermal Camera
    Paidi, Vijay
    Fleyeh, Hasan
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON VEHICLE TECHNOLOGY AND INTELLIGENT TRANSPORT SYSTEMS (VEHITS 2019), 2019, : 483 - 490
  • [10] Parking Space Occupancy at Rail Stations in Klang Valley
    Ho, Phooi Wai
    Ismail, S. M. Sabri
    Rajagopal, Premkumar
    INTERNATIONAL SYMPOSIUM ON CIVIL AND ENVIRONMENTAL ENGINEERING 2016 (ISCEE 2016), 2017, 103