Afarand Journals

Geographical Research

eISSN : 2538-4384
pISSN : 1019-7052
Persian
Language
Geographical Research is Published in Persian Fulltext.
Volume 31, Issue 4 (2017)                   GeoRes 2017, 31(4): 60-73 | Back to browse issues page
Article Type:
Original Research |
Subject:

Print XML Persian Abstract PDF HTML

History

Received: 2016/11/9 | Accepted: 2016/12/17 | Published: 2017/03/17
How to cite this article
Sajedinejad A, Hasannayebi E. Implementation of Operational City Bus Systems in Order to Organize Public Transportation. GeoRes 2017; 31 (4) :60-73
URL: http://georesearch.ir/article-1-26-en.html
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rights and permissions
Implementation of Operational City Bus Systems in Order to Organize Public Transportation
Authors Arman Sajedinejad *1, Erfan Hasannayebi2
1- Institute for Information, Science and Technology (IranDoc), Tehran, Iran , sajedinejad@irandoc.ac.ir
2- Department Industrial Engineering ,Tarbiat Modares University, Tehran, Iran
Abstract   (4589 Views)

Due to the substantial share of public transportation in urban travels, it is necessary to improve qualitative and quantitative aspects of public transportation. In quantitative perspective, it is important to improve characteristics such as infrastructure, number of fleets and coverage area. From a qualitative perspective, factors such as convenience, comfort and the quality of equipment have to be considered. In order to encourage citizens to use public transportation, it is necessary to improve the quantitative and qualitative aspects of bus transportation systems simultaneously. In this paper, the strategies of organizing urban bus transportation will be discussed and analyzed focusing on a framework based on Operational City Bus Systems. Also in this paper, the authors intend to elaborate and analyze required information and its role in designing urban transportation systems.

Keywords:
Public Transport, Urban Bus System, Travel Time, Designing Operating Systems.
References
1. - Abdelfattah, A. M., Khan, A. M. (1998), Models for predicting bus delays. Transportation Research Record: Journal of the Transportation Research Board 1623 (1), pp.8-15.
2. - An, S. Yang, H. Wang, J. Cui, N. Cui, J. (2016), Mining urban recurrent congestion evolution patterns from GPS-equipped vehicle mobility data. Information Sciences, Volume 373, pp. 515-526.
3. - Bates, J. Polak, J. Jonesc, P. Cook, A. (2001), The valuation of reliability for personal travel. Transportation Research Part E: Logistics and Transportation Review, 37 (2), pp.191-229.
4. - Bie, Y. Gong, X., Liu, Z. (2015), Time of day intervals partition for bus schedule using GPS data. Transportation Research Part C: Emerging Technologies, Volume 60, pp.443-456.
5. - Chen Mei, Liu, X., Xia, J. (2005), Dynamic prediction method with schedule recovery impact for bus arrival time. Transportation Research Record: Journal of the Transportation Research Board,pp. 208-217.
6. - Chen, M. Liu, X., Xia, J. (2004), A Dynamic Bus‐Arrival Time Prediction Model Based on APC Data. Computer‐Aided Civil and Infrastructure Engineering 19, pp.364-376.
7. - Chen, X. Yu, L., Zhang, Y. (2009), Analyzing urban bus service reliability at the stop, route, and network levels. Transportation Research Part A: Policy and Practice 43, pp.722-734.
8. - Cheung, C. Shalaby, A. S. Persaud, B. N., Hadayeghi, A. (2008), Models for safety analysis of road surface transit. Transportation Research Record: Journal of the Transportation Research Board, 2063 (1), pp.168-175.
9. - Chien, S. I. Ding, Y., Wei, C. (2002), Dynamic bus arrival time prediction with artificial neural networks. Journal of Transportation Engineering 128 (5),pp. 429-438.
10. - Dailey, D. Maclean, S., Cathey, F. (2001), Transit vehicle arrival prediction: Algorithm and large-scale implementation. Transportation Research Record: Journal of the Transportation Research Board, pp.46-51.
11. - Derevitskiy, I., Voloshin, D. Mednikov, L., Karbovskii, V. (2016), Traffic Estimation on Full Graph of Transport Network Using GPS Data of Bus Movements, Procedia Computer Science, Volume 101, pp. 207-216.
12. - El-Geneidy, A. M. Horning, J., Krizek, K. J. (2011), Analyzing transit service reliability using detailed data from automatic vehicular locator systems,45 (1), Journal of Advanced Transportation,pp. 66-79.
13. - Jeong, R., Rilett, R. (2004), Bus arrival time prediction using artificial neural network model. Proceedings of The 7th International IEEE Conference ,pp. 988-993, Intelligent Transportation Systems.
14. - Lin, W. H., Zeng, J. (1999), Experimental study of real-time bus arrival time prediction with GPS data. Transportation Research Record: Journal of the Transportation Research Board, pp,101-109.
15. - Park, T. Lee, S., Moon, Y. J. (2004), Real time estimation of bus arrival time under mobile environment. International Conference on Computational Science and Its Applications, pp. 1088-1096. Springer.
16. - Patnaik, J. Chien, S., Bladikas, A. (2004), Estimation of bus arrival times using APC data, Journal of Public Transportation 7 (1), pp.1–20.
17. - Shalaby, A., Farhan, A. (2004), Prediction model of bus arrival and departure times using AVL and APC data, Journal of Public Transportation 7 (3).
18. - Strathman, J. G., Dueker, K. (1999), Automated bus dispatching, operations control, and service reliability: Baseline analysis. Transportation Research Record, Journal of the Transportation Research Board, 1666 (1), pp.28-36.
19. - Strathman, J. G. Dueker, K. J., Kimpel, T. J. (2000), Service reliability impacts of computer-aided dispatching and automatic vehicle location technology: A Tri-Met case study, Transportation Quarterly, 54 (3), pp.85-102.
20. - Strathman, J. G. Kimpel, T. J., Dueker, K. J. (2002), Evaluation of transit operations: data applications of Tri-Met's automated Bus Dispatching System. Transportation, 29 (3), pp.321-345.
21. - Tétreault, P. R., El-Geneidy, A. M. (2010), Estimating bus run times for new limited-stop service using archived AVL and APC data. Transportation Research Part A: Policy and Practice, 44 (6), pp. 390-402.
22. - Tirachini, A. (2013), Estimation of travel time and the benefits of upgrading the fare payment technology in urban bus services, Transportation Research Part C: Emerging Technologies (30), pp. 239–256.
23. - Weigang, L., Koendjbiharie, W. (2002), Algorithms for estimating bus arrival times using GPS data, in Intelligent Transportation Systems, The IEEE 5th International Conference on Intelligent Transportation Systems Proceedings , IEEE., pp.868 – 873.