Bus Rapid Transit Network Design based on Travel Demand: A Case Study of Karaj, Iran

Document Type : Original Article

Authors

1 Assistant Professor, Department of Civil Engineering, Faculty of Engineering, Payame Noor University, Tehran, Iran

2 Ph.D. Student, Department of Civil Engineering, Faculty of Engineering, Payame Noor University, Tehran, Iran

Abstract

The bus rapid transit (BRT) network is an important public transportation system in some metropolises across the world. Hence, many urban managers and planners seek to develop BRT networks as they are more much flexible than railway transportation networks and can transport huge numbers of passengers. This paper designed a BRT network based on the travel demand using a binary nonlinear mathematical programming model with the aim of maximizing the covered demand and minimizing the construction cost. To calculate the covered travel demand and solve the model, a novel methodology which is exclusive to this study was proposed. To obtain the covered travel demand, the number of covered travels was calculated using the concentric circle method and the center of mass distances of the covered trips in the origins and destinations from the travel start and end stations. Based on the trip demand lines, major production and attraction land-uses, and network shape and integration, five BRT corridors were considered for the city of Karaj, Iran. The network design results suggest that the corridors would cover a total of 244,600 trips (28.7% of the total morning peak-hour trips in 2031). The corridors were estimated to have a total construction cost of 282.5 million USD.

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References

Kepaptsoglou, K., & Karlaftis, M. (2009). Transit route network design problem. Journal of transportation engineering, 135(8), 491-505.
Zhang, L., Lu, J., Yue, X., Zhou, J., Li, Y., & Wan, Q. (2018). An auxiliary optimization method for complex public transit route network based on link prediction. Modern Physics Letters B, 32(05), 1850066.
Xiong, J., Chen, B., Chen, Y., Jiang, Y., & Lu, Y. (2019). Route network design of community shuttle for metro stations through genetic algorithm optimization. IEEE Access, 7, 53812-53822.
Fu, X., & Lam, W. H. (2018). Modelling joint activity-travel pattern scheduling problem in multi-modal transit networks. Transportation, 45(1), 23-49.
Ceder, A., & Wilson, N. H. (1986). Bus network design. Transportation Research Part B: Methodological, 20(4), 331-344.
Ceder, A., & Israeli, Y. (1993). Design and evaluation of transit routes in urban networks. In Proceedings of the 3rd international conference on competition and ownership in surface passenger transport, Ontario, Canada.
Israeli, Y., & Ceder, A. (1995). Transit route design using scheduling and multiobjective programming techniques. In Computer-aided transit scheduling. Springer, Berlin, Heidelberg, 56-75.
Dufourd, H., Gendreau, M., & Laporte, G. (1996). Locating a transit line using tabu search. Location Science, 4(1-2), 1-19.
Pattnaik, S. B., Mohan, S., & Tom, V. M. (1998). Urban bus transit route network design using genetic algorithm. Journal of transportation engineering, 124(4), 368-375.
Bielli, M., Caramia, M., & Carotenuto, P. (2002). Genetic algorithms in bus network optimization. Transportation Research Part C: Emerging Technologies, 10(1), 19-34.
Bruno, G., Gendreau, M., & Laporte, G. (2002). A heuristic for the location of a rapid transit line. Computers & Operations Research, 29(1), 1-12.
Zhao, F., Ubaka, I., & Gan, A. (2005). Transit network optimization: Minimizing transfers and maximizing service coverage with an integrated simulated annealing and tabu search method. Transportation research record, 1923(1), 180-188.
Yang, Z., Yu, B., & Cheng, C. (2007). A parallel ant colony algorithm for bus network optimization. Computer‐Aided Civil and Infrastructure Engineering, 22(1), 44-55.
Zhao, F., & Zeng, X. (2008). Optimization of transit route network, vehicle headways and timetables for large-scale transit networks. European Journal of Operational Research, 186(2), 841-855.
Szeto, W. Y., & Wu, Y. (2011). A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong. European Journal of Operational Research, 209(2), 141-155.
Gutiérrez-Jarpa, G., Obreque, C., Laporte, G., Marianov, V. (2013). Rapid transit network design for optimal cost and origin–destination demand capture. Computers & Operations Research, 40(12), 3000-3009.
Ouyang, Y., Nourbakhsh, S. M., & Cassidy, M. J. (2014). Continuum approximation approach to bus network design under spatially heterogeneous demand. Transportation Research Part B: Methodological, 68, 333-344.
Nikolić, M., & Teodorović, D. (2014). A simultaneous transit network design and frequency setting: Computing with bees. Expert Systems with Applications, 41(16),7200-7209.
Cancela, H., Mauttone, A., & Urquhart, M. E. (2015). Mathematical programming formulations for transit network design. Transportation Research Part B: Methodological, 77,17-37.
Cipriani, E., Fusco, G., Patella, S. M., Petrelli, M., & Quadrifoglio, L. (2019). Transit network design for small-medium size cities. Transportation Planning and Technology, 42(1), 84-97.
Ahmed, L., Mumford, C., & Kheiri, A. (2019). Solving urban transit route design problem using selection hyper-heuristics. European Journal of Operational Research, 274(2), 545-559.
Wang, C., Ye, Z., & Wang, W. (2020). A multi-objective optimization and hybrid heuristic approach for urban bus route network design. IEEE Access, 8, 12154-12167.
Momenitabar, M., & Mattson, J. (2021). A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area. Sustainability, 13(19), 10885.
Mahdavi, A. R., Mamdoohi, A., & Allahviranloo, M. (2021). A fuzzy approach for designing of subway lines, case study: development of the Tehran subway network. Amirkabir Journal of Civil Engineering, 53(9), 13-13.
Durán-Micco, J., van Kooten Niekerk, M., & Vansteenwegen, P. (2022). Designing bus line plans for realistic cases-the Utrecht case study. Expert Systems with Applications, 187, 115918.
Rajabi, R., Yakhchali, S., (2022), Cash Flow Optimization of Portfolio Considering Market Indices Using Genetic Algorithm and Particle Swarm Optimization, Journal of Structural and Construction Engineering, [online], Available at: https://www.jsce.ir/article_144890.html.
Khajeh, A., Kiani, A., Seraji, M., Dashti, H., Optimization of structure using hybrid Harris hawks and genetic algorithm, Journal of Structural and Construction Engineering, [online], Available at: https://www.jsce.ir/article_152908.html
Code 777, (2019). Public Transportation Studies and Feasibility Studies for Rail Systems in Urban and Suburb Areas (Scope of Services), Islamic Republic of Iran Plan and Budget Organization.
Vuchic, V. R. (2007). Urban transit systems and technology. John Wiley & Sons.

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History

  • Receive Date: 27 June 2022
  • Revise Date: 15 August 2022
  • Accept Date: 10 September 2022

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