Research Article of Scientific Research and Reviews
Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case
Lingxiang Wei1*, Dong Pan1, Mingjun Liao1,2*
1School of Materials Science and Engineering, Yancheng Institute of Technology, Yan Cheng 224051, China; 2Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing 710064, China
In order to solve the problems of low utilization rate of large parking lots and low efficiency of parking turnover, it is proposed to use A-star algorithm to plan the shortest path for finding a car, and run it in Android system to realize reverse car-searching. By analyzing the current situation of large underground parking lot barriers, A-star algorithm converts the starting point to the destination route into the corresponding parking space to the destination parking space path, calculates the optimal path and provides real-time path car navigation for the vehicle owner. According to the path searched by the A-star algorithm in the Android system, the time spent by the user to blindly search for the vehicle is largely saved, and the parking space utilization rate and the parking turnover rate are effectively improved. Therefore, the research has certain application value in the large parking lots.
Keywords: Transport optimization; A Star Algorithm; Shortest Path; Reverse Car Search
How to cite this article:
Lingxiang Wei, Dong Pan, Mingjun Liao. Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case. Scientific Research and Reviews, 2020; 13:116. DOI:10.28933/srr-2020-04-0105
1. Jian-Hua X , Ping C , Bing-Lian L . Research on
Parking Pricing of Logistics Distribution Vehicle under Urban Traffic Congestion. Journal of Business Economics, 2018,316,16-23
2. Mehdi Nourinejad, Sina Bahrami, Matthew J. Roorda. Designing Parking Facilities for Autonomous Vehicles. Transportation Research Part B Methodological, 2018, 109,110-127.
3. Tan Z, Wang M, Wang Y, et al. Present situation and application of urban underground parking lots. Strategic Study of Chinese Academy of Engineering, 2018, 19(6),100-110.
4. Huang G, Hu Z, Mu M, et al. Multi-View and Multi-Scale Localization for Intelligent Vehicles in Underground Parking Lots. Transportation Research Record, 2019, 2673(11), 791-800.
5. Jin L, Juming M, Junjian F, et al. Visible light indoor parking lot positioning navigation system based on LED lighting. Journal of applied op-tics, 2019, 40(5): 746-750.
6. Song J, Lee J. Positioning Method Using a Vehicular Black-Box Camera and a 2D Barcode in an Indoor Parking Lot. Journal of the korea Institute of Information and Communication Engineering, 2016, 20(1), 142-152.
7. Chenyue H , Zhongwei S . Status Quo and Problems of Underground Space Researches. Journal of Landscape Research, 2017,2,10-14.
8. Lin C, Qiao T. Localization in the Parking Lot by Parked-Vehicle Assistance. IEEE Transactions on Intelligent Transportation Systems, 2016, 17,3629-3634.
9. Masmoudi I, Wali A, Jamoussi A, et al. Trajectory analysis for parking lot vacancy detection system. Iet Intelligent Transport Systems, 2016, 10,461-468.
10. Na C, Lu W, Jia L, et al. Parking Survey Made Efficient in Intelligent Parking Systems. Procedia Engineering, 2016, 137,487-495.
11. Suhr J K , Member, IEEE, et al. Automatic Parking Space Detection and Tracking for Underground and Indoor Environments. IEEE Transactions on Industrial Electronics, 2016, 63(9),5687-5698.
12. Shin J H, Jun H B, Kim J G. Dynamic control of intelligent parking guidance using neural net-work predictive control. Computers & Industrial Engineering, 2018, 120,15-30.
13. Ji J , Khajepour A , Melek W W , et al. Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multi Constraints. IEEE Transactions on Vehicular Technology, 2017, 66,952-964.
14. Yang D, Xu B, Rao K, et al. Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm. Sensors, 2018, 18,332.
15. Zhang Y, Wang F, Fu F, et al. Multi-AGV path planning for indoor factory by using prioritized planning and improved ant algorithm. Journal of Engineering and Technological Sciences, 2018, 50(4),534-547.
16. Yuan L, Li D, Hu S. A map-matching algorithm with low-frequency floating car data based on matching path. EURASIP Journal on Wireless Communications and Networking, 2018,(1),146
17. Xin Z, Chen G. A new method of applying the ETC technology to the underground parking lot in the supermarket. International Journal of Reasoning-based Intelligent Systems, 2016, 8(1-2), 52-58.
18. Tsiropoulou E E, Baras J S, Papavassiliou S, et al. RFID-based smart parking management system. Cyber-Physical Systems, 2017,3(1-4), 22-41.
19. Jung S, Kim Y, Hwang E. Real-time car tracking system based on surveillance videos. EURASIP Journal on Image and Video Processing, 2018, 2018(1),1-13.
20. Shen H, Zhang K, Nejati A. A noncontact positioning measuring system based on distributed wireless networks. Peer-to-Peer Networking and Applications, 2017, 10(3),823-832.
21. Chao L, Ueno M. An extended depth-first search algorithm for optimal triangulation of Bayesian networks. International Journal of Approximate Reasoning, 2017, 80,294-312.
22. Tsiropoulou E E, Baras J S, Papavassiliou S, et al. RFID-based smart parking management system. Cyber-Physical Systems, 2017, 3(1-4), 22-41.
23. Liu X, Liu W, Mei T, et al. Provide: Progressive and multimodal vehicle reidentification for large-scale urban surveillance. IEEE Transactions on Multimedia, 2017, 20(3),645-658.
24. Xu Y, Lu H, Xie Z. Research on multi-robot cooperative location algorithm based on wireless sensor networks. Int. J. Innov. Comp. Inf. Control, 2019, 15(5), 1779-1792.
25. Ma S, Jiang H, Han M, et al. Research on automatic parking systems based on parking scene recognition. IEEE Access, 2017,5,21901 -21917.
26. Mahmood Z, Haneef O, Muhammad N, et al. Towards a fully automated car parking system. IET Intelligent Transport Systems, 2019, 13(2),293-302.
27. Hougardy S, Silvanus J, Vygen J. Dijkstra meets Steiner: a fast exact goal-oriented Steiner tree algorithm. Mathematical Programming Computation, 2016, 9,1-68.
28. Kang W X, Yao-Zhao X U. A Hierarchical Dijkstra Algorithm for Solving Shortest Path from Constrained Nodes. Journal of South China University of Technology, 2017,45,66 -73.
29. Li Y, Zhang H, Zhu H, et al. IBAS: Index Based A-Star. IEEE Access, 2018, 6, 11707-11715.
30. Sundfeld D, Razzolini C, Teodoro G, et al. PA-Star: A disk-assisted parallel A-Star strategy with locality-sensitive hash for multiple sequence alignment. Journal of Parallel and Distributed Computing, 2018, 112,154-165.