A Framework on New Travel Demand Model Based on Potential Travelers and Surrounding Land Uses for Rapid Transit

Z. Abal Abas


One of the public transports is rapid transit, which provides the highest performance mode of urban transportation. Currently, existing rapid transit travel demand analysis from the service provider is based on ticketing data that contain information such as time travel, origin and destination; which is using trip based method. This method has its limitation such as the demand is for trip making rather than for activities as well as having spatial, temporal and demographic aggregation errors. It also failed to predict the travel demand when there is future development or growth in the surrounding area. Therefore, new method for modeling travel demand is needed. This paper proposes a framework of new model and analytics for travel demands of rapid transits based on big data of potential travelers and surrounding land uses. Land uses and transportation are interdependent. With this proposed concept, the accurate travel demand for rapid transit in the future will be met. Therefore, the rapid transit service will have excellence operation, which includes optimum frequency, punctuality and reliable service.

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M. Betty, The new science of cities. MIT Press, Cambridge, 2013.

Z. A. Abas, L. Ee-Theng, A. F. N. A. Rahman, Z. Z. Abidin, and A. S. Shibghatullah, “Enhanced scheduling traffic light model using Discrete Event Simulation for improved signal timing analysis,” ARPN J. Eng. Appl. Sci., vol. 10, no. 18, pp. 8135–8140, 2015.

J. Holmgren, “An analysis of the determinants of local public transport demand focusing the effects of income changes,” Eur. Transp. Res. Rev., vol. 5, no. 2, pp. 101–107, 2013.

V. R. Vuchic, “Urban Public Transportation Systems,” Transp. Eng. Plan., vol. I, p. 26, 1981.

M. Saberi, H. S. Mahmassani, D. Brockmann, and A. Hosseini, “A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origindestination demand networks,” Transportation (Amst)., pp. 1–20, 2016.

M. . Gonzalez, H. C.A, and B. A.L, “Understanding individual human mobility pattern,” Nature, vol. 453, 2008.

C. M. Schneider, V. Belik, C. T., S. Z., and M. C. Gonza´lez, “Unravelling daily human mobility motifs,” J. R. Soc. Interface, vol. 10, 2013.

IBM, “Big data and analytics in travel and transportation,” 2013.

“London ’ s Rapid Transit Initiative,” 2014.

L. Zhang and D. Levinson, “Agent-Based Approach to Travel Demand Modeling: Exploratory Analysis,” Transp. Res. Rec., vol. 1898, no. 1, pp. 28–36, 2004.

N. Huynh, V. L. Cao, R. Wickramasuriya, M. Berryman, P. Perez, and J. Barthelemy, “An Agent Based Model for the Simulation of Road Traffic and Transport Demand in A Sydney Metropolitan Area,” Eighth Int. Work. Agents Traffic Transp. , no. 2005, pp. 1–7, 2014.

M. C. Beutel, S. Addicks, B. S. Zaunbrecher, S. Himmel, K. H. Krempels, and M. Ziefle, “Agentbased transportation demand management: Demand effects of reserved parking space and priority lanes in comparison and combination,” SMARTGREENS 2015 - 4th Int. Conf. Smart Cities Green ICT Syst. Proc., pp. 317–323, 2015.

N. F. Mansor, Z. Abal Abas, A. F. N. Abdul Rahman, A. S. Shibghatullah, and S. Safiah, “An analysis of the parameter modifications in varieties of harmony search algorithm,” Int. Rev. Comput. Softw., vol. 9, no. 10, pp. 1736–1749, 2014.

A. Morimoto, Transportation and Land Use Planning. 2014.

S. Salleh and Z. Abal Abas, Simulation for Applied Graph Theory Using Visual C++. Boca Raton: CRC Press Taylor & Francis Group, 2016.

Z. Abal Abas, S. Salleh, and Z. Manan, “Extended Advancing Front Technique for the Initial Triangular Mesh Construction on a Single Coil for Radiative Heat Transfer,” Arab. J. Sci. Eng., vol. 38, no. 9, pp. 2245–2262, 2013.

S. F. Abdullah, A. F. N. A. Rahman, and Z. A. Abas, “CLASSIFICATION OF GENDER BY USING FINGERPRINT RIDGE DENSITY IN NORTHERN PART OF MALAYSIA,” ARPN J. Eng. Appl. Sci., vol. 10, no. 22, pp. 10722–10726, 2015.

N. F. Mansor, Z. A. Abas, A. F. N. A. Rahman, A. S. Shibghatullah, and S. Sidek, “AN OPTIMIZATION SOLUTION USING A HARMONY SEARCH ALGORITHM,” in International Symposium on Research in Innovation and Sustainability 2014, 2014, vol. 2014, no. October, pp. 1745–1749.

Z. A. Abas, S. Salleh, A. F. N. A. Rahman, H. Basiron, A. S. Hassan Basari, and N. Hassim,

“Improvement of Element Creation Procedure for Generating Initial Triangular Unstructured Mesh for Radiative Heat Transfer Modelling,” Int. Rev. Model. Simulations, vol. 6, no. 5, pp. 1649–1656, 2013.

M. I. Jasmi, A. F. N. A. Rahman, Z. A. Abas, and

. S. Shibghatullah, “Optimized Coating Design of Energy Saving Glass Using Binary Harmony Search for Better Transmission Signal,” Int. J. Comput. Sci. Inf. Secur., vol. 14, no. 8, pp. 436–443, 2016.

N. Hashim, Z. ZainalAbidin, A. Shibghatullah, Z. AbalAbas, and N. Yusof, “A New Model of Crypt Edge Detection Using PSO and Bi-cubic Interpolation for Iris Recognition,” in Advanced Computer and Communication Engineering Technology: Proceedings of ICOCOE 2015, A. H. Sulaiman, A. M. Othman, I. M. F. Othman, A. Y. Rahim, and C. N. Pee, Eds. Cham: Springer International Publishing, 2016, pp. 659–669.

Z. Abas, Z. Shaffiei, A. F. N. A. Rahman, and A. S. Shibghatullah, “Using Harmony Search for Optimising University Shuttle Bus Driver Scheduling for Better Operational Management,” in ITMAR 2014, 2014, vol. 1, pp. 614–621.

M. R. Ramli, Z. Abal Abas, F. Arif, and M. I. Desa, “An Analysis Review Approaches Used In Health Human Resources Planning,” Int. J. Comput. Sci. Inf. Secur., vol. 14, no. 8, pp. 908–935, 2016.

Z. A. Abas et al., “A supply model for nurse workforce projection in Malaysia,” Health Care Manag. Sci., 2017.


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