Curbside Parking Occupancy Detection - Dashcam-Based Solutions

被引:1
|
作者
Li, Jiayu [1 ]
Zhang, Hanming [1 ]
Hu, Juhua [1 ]
Cheng, Wei [1 ]
机构
[1] Univ Washington, Tacoma Sch Engn & Technol, Seattle, WA 98195 USA
关键词
D O I
10.1109/MDM61037.2024.00046
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Accurate assessment of curbside parking occupancy is essential for policymakers to optimize public resource allocation. It is also beneficial for driver/autonomous vehicles' parking planning. Despite its importance, there is still no comprehensive solution of curbside parked vehicle detection for different road and traffic scenarios. We therefore propose two computer vision based solutions for efficiently quantify parked vehicles in simple and complex scenarios, respectively, from the street videos taken by off-the -shelf dash cameras. The proposed Al pipelines encompass multiple tasks, including vehicle detection and tracking, road surface detection, and lane line detection. The interplay between detected vehicles, road surface, and lane lines enhances the robustness of feature engineering. Through evaluations, our solutions demonstrate their capability to handle diverse road and traffic scenarios, including busy main roads, quiet side roads, and residential areas.
引用
收藏
页码:219 / 226
页数:8
相关论文
共 50 条
  • [41] A Visual Sensor Network for Parking Lot Occupancy Detection in Smart Cities
    Baroffio, Luca
    Bondi, Luca
    Cesana, Matteo
    Redondi, Alessandro Enrico
    Tagliasacchi, Marco
    2015 IEEE 2ND WORLD FORUM ON INTERNET OF THINGS (WF-IOT), 2015, : 745 - 750
  • [42] An rPark-branded Proposed Smart Occupancy Detection System for Parking
    Rahman, Atiqur
    Ufiteyezu, Emmanuel
    JURNAL KEJURUTERAAN, 2023, 35 (05): : 1017 - 1024
  • [43] Deep Convolutional Neural Network for Parking Space Occupancy Detection Based on Non-local Operation
    Shen Xuanjing
    Shen Zhe
    Huang Yongping
    Wang Yu
    JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2020, 42 (09) : 2269 - 2276
  • [44] Deep learning-based parking occupancy detection framework using ResNet and VGG-16
    Thakur, Narina
    Bhattacharjee, Eshanika
    Jain, Rachna
    Acharya, Biswaranjan
    Hu, Yu-Chen
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (1) : 1941 - 1964
  • [45] Deep learning-based parking occupancy detection framework using ResNet and VGG-16
    Narina Thakur
    Eshanika Bhattacharjee
    Rachna Jain
    Biswaranjan Acharya
    Yu-Chen Hu
    Multimedia Tools and Applications, 2024, 83 : 1941 - 1964
  • [46] An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength
    Lou, Liangliang
    Zhang, Jinyi
    Xiong, Yong
    Jin, Yanliang
    SENSORS, 2019, 19 (10):
  • [47] Deep learning-based vehicle occupancy detection in an open parking lot using thermal camera
    Paidi, Vijay
    Fleyeh, Hasan
    Nyberg, Roger G.
    IET INTELLIGENT TRANSPORT SYSTEMS, 2020, 14 (10) : 1295 - 1302
  • [48] Real-Time Parking Occupancy Detection for Gas Stations Based on Haar-AdaBoosting and CNN
    Xiang, Xuezhi
    Lv, Ning
    Zhai, Mingliang
    El Saddik, Abdulmotaleb
    IEEE SENSORS JOURNAL, 2017, 17 (19) : 6360 - 6367
  • [49] Deep Convolutional Neural Network for Parking Space Occupancy Detection Based on Non-local Operation
    Shen X.
    Shen Z.
    Huang Y.
    Wang Y.
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2020, 42 (09): : 2269 - 2276
  • [50] A machine learning approach to infer on-street parking occupancy based on parking meter transactions
    Sonntag, Jonas
    Schmidt-Thieme, Lars
    2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2020,