FUTURE RESEARCH DIRECTIONS

The analysis presented in this report can be extended in several ways. Prediction

accuracy can be improved in several ways including:

  • • The model presented in this report is based on data from all routes and hence can be used to model degradation in all routes. If enough data becomes available, a separate model for each route can yield a higher accuracy and robustness. Also, if the data is available, the influence of wheels on track degradation can be analysed and modelled.
  • • The model presented in this report only focuses on Curves. A separate model to predict degradation for other track components (e.g. straight, H-crossing, crossover) can help prioritise the maintenance across the entire network.
  • • Similar procedure can be used to analyse the deterioration data and model the rate of deterioration/defection of different assets of tram system (e.g. overheads).

REFERENCES

Ahmad, R., & Kamaruddin, S. (2012). An overview of time-based and condition- based maintenance in industrial application. Computers & Industrial Engineering, 63(1), 135-149. doi:10.1016/j.cie.2012.02.002

Alfelor, R., Carr, G., & Fateh, M. (2001). Track degradation assessment using gage restraint measurements. Transportation Research Record: Journal of the Transportation Research Board, 1742, 68-77. doi:10.3141/1742-09

Andrade, A. R., & Teixeira, P. F. (2011). Uncertainty in rail-track geometry degradation: Lisbon-Oporto line case study. Journal of Transportation Engineering, 137(3), 193-200. doi:10.1061/(ASCE)TE.1943-5436.0000206

Andrade, A. R., & Teixeira, P. F. (2013). Unplanned-maintenance needs related to rail track geometry.Proceedings of the ICE - Transport.

Budai, G., Huisman, D., & Dekker, R. (2005). Scheduling preventive railway maintenance activities. The Journal of the Operational Research Society, 57(9), 1035-1044. doi:10.1057/palgrave.jors.2602085

Caetano, L., & Teixeira, P. F. (2013). Availability approach to optimizing railway track renewal operations. Journal of Transportation Engineering, 139(9), 941-948. doi:10.1061/(ASCE)TE.1943-5436.0000575

El-sibaie, M., & Zhang, Y. J. (2004). Objective track quality indices. Transportation Research Record: Journal of the Transportation Research Board, 1863, 81-87. doi:10.3141/1863-11

Gazder, U. & Ratrout, N. T. (2015). A new logit-artificial neural network ensemble for mode choice modeling: a case study for border transport. Journal of Advanced Transportation. DOI: 10.1002/atr.1306

Guler, H., Jovanovic, S., & Evren, G. (2011). Modelling railway track geometry deterioration.Proceedings of the ICE - Transport.

Hensher, D. A. (2000). Transport economics: A personal view. Journal of Advanced Transportation, 34(1), 65-106. doi:10.1002/atr.5670340105

Jovanovic, S. (2004). Railway track quality assessment and related decision making. IEEE International Conference on Systems, Man and Cybernetics. doi:10.1109/ ICSMC.2004.1400992

Larsson, D. (2004). A study of the track degradation process related to changes in railway traffic. (PhD thesis). Lulea University of Technology.

Liu, R., Xu, P., & Wang, F. (2010). Research on a short-range prediction model for track irregularity over small track lengths. Journal of Transportation Engineering, 136(12), 1085-1091. doi:10.1061/(ASCE)TE.1943-5436.0000192

Mazloumi, E., Moridpour, S., Currie, G., & Rose, G. (2012). Exploring the Value of Traffic Flow Data in Bus Travel Time Prediction. Journal of Transportation Engineering, 138(4), 436-446.

Mazloumi, E., Rose, G., Currie, G., & Moridpour, S. (2011). Prediction Intervals to Account for Uncertainties in Neural Network Predictions: Methodology and Application in Bus Travel Time Prediction. Engineering Applications of Artificial Intelligence, 24(3), 534-542.

Moridpour, S., & Hesami, R. (2015). Degradation and performance specification of Melbourne tram tracks. The 3rd International Conference on Transportation Information and Safety (ICTIS).

Peng, F., & Ouyang, Y. (2012). Track maintenance production team scheduling in railroad networks. Transportation Research Part B: Methodological, 46(10), 1474-1488. doi:10.1016/j.trb.2012.07.004

Peng, F., & Ouyang, Y. (2013). Optimal clustering of railroad track maintenance jobs. Computer-Aided Civil and Infrastructure Engineering, 29(4), 235-247. doi:10.1111/mice.12036

Quiroga, L., & Schnieder, E. (2013). Railway systems. In H. Czichos (Ed.), Handbook of Technical Diagnostics. Springer Berlin Heidelberg. doi:10.1007/978-3- 642-25850-3_26

Sadeghi, J. (2010). Development of railway track geometry indexes based on statistical distribution of geometry data. Journal of Transportation Engineering, 136(8), 693-700. doi:10.1061/(ASCE)0733-947X(2010)136:8(693)

Sadeghi, J., & Askarinejad, H. (2010). Development of improved railway track degradation models. Structure and Infrastructure Engineering, 6(6), 675-688. doi:10.1080/15732470801902436

Shafahi, Y., & Hakhamaneshi, R. (2009). Application of maintenance management model for Iranian railways based on the Markov chain probabilistic dynamic modeling. Scientia Iranica, 16, 87-97.

Tang, S., Boyles, S. D., & Jiang, N. (2015). High-speed rail cost recovery time based on an integer optimization model. Journal of Advanced Transportation, 49(5), 634-647. doi:10.1002/atr.1294

Wu, Z., Flintsch, G., Ferreira, A., & Picado-santos, L. (2012). Framework for multiobjective optimization of physical highway assets investments. Journal of Transportation Engineering, 138(12), 1411-1421. doi:10.1061/(ASCE)TE.1943- 5436.0000458

Yaghini, M., Khoshraftar, M. M., & Seyedabadi, M. (2013). Railway passenger train delay prediction via neural network model. Journal of Advanced Transportation, 47(3), 355-368. doi:10.1002/atr.193

Yarra Trams. (2015). Facts and Figures, Yarra Trams. Retrieved from http://www. yarratrams.com.au/about-us/who-we-are/facts-figures/

Yousefikia, M., Moridpour, S., Setunge, S., & Mazloumi, E. (2014). Modeling degradation of tracks for maintenance planning on a tram line. Journal of Traffic and Logistics Engineering., 2(2), 86-91. doi:10.12720/jtle.2.2.86-91

Zakeri, J. A., & Shahriari, S. (2012). Developing a deterioration probabilistic model for rail wear. International Journal of Traffic and Transportation Engineering, 1, 13-18.

Zhao, J., Chan, A., Stirling, A., & Madelin, K. (2006). Optimizing policies of railway ballast tamping and renewal. Transportation Research Record: Journal of the Transportation Research Board, 1943, 50-56. doi:10.3141/1943-07

 
Source
< Prev   CONTENTS   Source   Next >