Web application service in bus arrival time prediction

• Autorzy: Stjepainovic Aleksandar , Kostadinovic Miroslav , Kuzmi Goran , Stojcic Mirko , Stjepanovic Sladjana

Identyfikatory

DOI

10.15199/48.2020.04.07

Warianty tytułu

PL

Zastosowanie aplikacji sieciowej do prognozowania czasu przyjazdu autobusu w komunikacji miejskiej

• Języki publikacji: EN

Abstrakty

EN

Bus arrival time prediction represents very important part of the service that informs passengers of intelligent transport systems in public bus transportation. Different methods are used for the prediction. In this paper, two methods for predicting arrival time of bus are analysed. Proposed method is the freely available Google’s web service “DistanceMatrixAPI” . Comparative view of obtained results using the Kalman filter and Web service is presented. For the experimental research we proposed model of Distribution Modular Information and Communication System. Research results shows that the implementation of Kalman filter method is much more accurate that the use of “DistanceMatrix API” method.

PL

W artykule zaprezentowano inteligentny system informujący pasażerów transportu publicznego o przewidywanym pczasie przyjazdu pojazdu. Analizowano dwie metody. NBajlepsze parametry miał system wykorzystujący filtr Kalmana.

Słowa kluczowe

EN

Google API; web service; BATP; Kalman filter

PL

Google API; system prognozowania przyjazdu autobusu; filtr Kalmana

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 4
• Strony: 39--42
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Stjepainovic Aleksandar

• Faculty of Traffic and Transportation, ul. Vojvode Misica 52, 74000 Doboj, Bosnia and Herzegovina

autor

Kostadinovic Miroslav

• Faculty of Traffic and Transportation, ul. Vojvode Misica 52, 74000 Doboj, Bosnia and Herzegovina

autor

Kuzmi Goran

• Faculty of Traffic and Transportation, ul. Vojvode Misica 52, 74000 Doboj, Bosnia and Herzegovina

autor

Stojcic Mirko

• Faculty of Traffic and Transportation, ul. Vojvode Misica 52, 74000 Doboj, Bosnia and Herzegovina

autor

Stjepanovic Sladjana

• Faculty of Technical Science Novi Sad, Serbia

Bibliografia

• [1] M. Zaki, I. Ashour, M. Zorkany, B. Hesham, Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman filter Techniques, International Journal of Modern Engineering Research, (IJMER), Vol. 3, Issue 4, Jul-Avg. 2013. ISSN:2249
• [2] Shriram Kulkarni , Revati Deshmukh , Basavraj Devpuje , Nilam Kapare, Kumar Murari, Real Time Bus Arrival Prediction System Using GPS, Universalreview.org , Volume VIII, Issue II, FEBRUARY/2019.
• [3] Xuefeng Liu, Jingjing Fan, Jianhua Mao, and Fenxiao Ye, A Low-Power Self-service Bus Arrival Reminding Algorithm on Smart Phone, The International Arab Journal of Information Technology, Vol. 16, No. 2, March 2019.
• [4] Dr. Ranjana Dinkar Raut, Vineet Kumar Goyal, Public transport Bus Arrival Time Prediction with Seasonal and Special Emphasis on Weather Compensation changes using RNN, International Journal of advanced Research in Computer and Communication Engineering, Vol. 1, Issue 6, Avgust 2012, ISSN:2278-1021.
• [5] Mehmet Altinkaya, Metin Zontal, Urban Bus Arrival Time Prediction: A Rewiev of Computational Models, International Journal of Recent Technology and Engineering (IJRTE), ISSN: 2277-3878, Vol. 2, Issue 4, September 2013.
• [6] Amer Shalaby, Ali Farhan, Prediction Model of Bus Arrival and Departure Times Using AVL and APC data, Journal of Public Transportation, 2004.
• [7] S.I.J . Chien, Y. Ding, and C. Wei, Dynamic Bus Arrival Time Prediction with Artificial Neural Networks, Journal of Transportation Engineering, 2002.
• [8] A. Deebika Shree ; J. Anusuya ; S. Malathy, Real Time Bus Tracking and Location Updation System, 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 2019.
• [9] Anudeep P., Krishna Prakash N.,Intelligent Passenger Information System Using IoT for Smart Cities, Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 851. Springer, 2019.
• [10] Kumar, B.A., Prasath, G.H. & Vanajakshi, Dynamic Bus Scheduling Based on Real-Time Demand and Travel Time, L.I nt J Civ Eng 17: 1481. https://doi.org/10.1007/s40999-019- 00445-y
• [11] Jang won Seo, Dae gyu Hwang, Kyung hee Lee, Ki seongKim, Inho Jeon Changqiang Jung, Youngak Kim, "An Intelligent Bus Status Informing Scheme Exploiting Smartphone Application“, International Journal of Smart Home, Vol. 7, No.3, May 2013.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).