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Tytuł artykułu

Evaluating a Proposed Urban Transportation System Using Advance Transport and Land-Use Modelling Framework

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The effect of traffic congestion, emission, and road accident on cities that depend solely on motor vehicles make them unsustainable. Increased mobility from rapid urbanization has placed great demand on the transport system of such cities. To meet the increasing demand, modelling travel demand based on the transport network has become a necessity for sustainable urban development. In this study, an advanced transport and land-use modelling framework was developed to evaluate a transport system of a proposed new city. Furthermore, transport (road) network connectivity indices were used to measure the level of connectivity of the transport network. The findings show that the proposed transport system may not support the sustainable urban development of the new city due to the low level of network connectivity. The result further revealed that about 52% of the residents will depend on auto modes of transportation making the new city car-dependent rather than transit-dependent. Specifically, all corridor road links showed a high level of traffic congestion problem. The alternative of building more rails or a bus rapid transit (BRT) system connecting the main and a new city is worth considering when proposing an urban transport system. The advanced transport and land-use modelling framework developed in this study to evaluate the performance of the transportation system could serve as a decision-support system (DSS) towards sustainable planning and development of both old and new cities.
Twórcy
autor
  • National Engineering Research Center for Water Transport Safety, P.R. China
  • Engineering Research Center for Transportation Safety, Ministry of Education of P.R. China
  • Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, 430063, Hubei, P.R. China
  • Mechanical Engineering Department, Dr. Hilla Limann Technical University, P. O Box, 553 Wa, Ghana
autor
  • National Engineering Research Center for Water Transport Safety, P.R. China
  • Engineering Research Center for Transportation Safety, Ministry of Education of P.R. China
  • Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, 430063, Hubei, P.R. China
autor
  • National Engineering Research Center for Water Transport Safety, P.R. China
  • Engineering Research Center for Transportation Safety, Ministry of Education of P.R. China
  • Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, 430063, Hubei, P.R. China
Bibliografia
  • 1. Sahitya K.S., Prasad C.S.R.K. Modelling structural interdependent parameters of an urban road network using GIS. Spat. Inf. Res. 2020; 28, 327–334. DOI: 10.1007/s41324–019–00295–9.
  • 2. Mahmoudi R., Shetab-Boushehri S., Hejazi S.R, Emrouznejad A. Determining the relative importance of sustainability evaluation criteria of urban transportation network. Sustainable Cities and Society. 2019. DOI: 10.1016/j.scs.2019.1014932019.
  • 3. Kumar R., Parida P., Madhu E., Kumar A.V.A.B. Does Connectivity Index of Transport Network have Impact on Delay for Driver? Transportation Research Procedia, 2017; 25 (2017): 4988–5002. DOI: 10.1016/j.trpro.2017.05.377.
  • 4. Kumar P., Jain S.S., Kulkarni S.Y., Parida, M. Multi Modal Transportation System. 2010. Available on-line at https://www.nbmcw.com/tech-articles/.
  • 5. Serdar M.Z., Koç, M., Al-Ghamd S.G. Urban Transportation Networks Resilience: Indicators, Disturbances, and Assessment Methods. Sustainable Cities and Society. 2022; 76(2022): 103452. DOI: 10.1016/j.scs.2021.103452
  • 6. Sreelekha M.G., Krishnamurthy K., Anjaneyulu M.V.L.R. Interaction between Road Network Connectivity and Spatial Pattern. Procedia Technology. 2016; 24 (2016): 131–139. DOI: 10.1016/j.protcy.2016.05.019.
  • 7. Labi S., Faiz S., Saeed T.U., Alabi B.N.T., Woldemariam W. Connectivity, Accessibility, and Mobility Relationships in the Context of Low-Volume Road Networks. Transportation Research Record. 2019; 1–11. DOI: 10.1177/0361198119854091.
  • 8. Daniel C.B., Saravanan S., Mathew S. GIS Based Road Connectivity Evaluation Using Graph Theory. T. V. Mathew et al. (eds.), Transportation Research, Lecture Notes in Civil Engineering. 2020; 45. DOI:10.1007/978–981–32–9042–6_17.
  • 9. Ort ́Uzar J.D., Willumsen L.G. Modelling Transport. Fourth Edition., John Wiley & Sons, Ltd. England. 2001.
  • 10. Caliper Corporation. Travel Demand Modeling with TransCAD Version 7.0 User Guide. Caliper Corporation, United State of America. 2015, 13.
  • 11. Hollander Y. Multiple Objectives in Travel Demand Modeling. Transportation Research Record Journal of the Transportation Research Board. 2010; 2175(1): 120–129.
  • 12. Zhong M., Shan R., Du, D., Lu C. A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa, Florida. Transportation Planning and Technology. 2015; 38(5): 1–17.
  • 13. Zhong M., Wang W., Hunt J.D., Pan P. H, Chen T., Li J., Yang W., Zhang K. Solutions to cultural, organizational, and technical challenges in developing PECAS models for the cities of Shanghai, Wuhan, and Guangzhou. Journal of Transport and Land Use. 2018: 1193–1229.
  • 14. Hunt J.D., Abraham J.E. Design and Application of the PECAS Land-use Modelling System. the 8th International Conference on Computers in Urban Planning and Urban Management (CUPUM), Sendai, Japan. 2003; 7.
  • 15. Hunt J.D., Abraham J.E. PECAS Theoretical Formulation. 2009. Available online at http://www.hbaspecto.com/pecas/downloads/.
  • 16. Liu Y. Modelling Urban Development with Geographical Information Systems and Cellular Automata. Taylor & Francis Group, New York, USA. 2009; 71.
  • 17. Wegmann F., Everett J. Minimum Travel Demand Model Calibration and Validation Guidelines for State of Tennessee. prepared for Florida Department of Transportation Systems Planning Office, 2012. Available online at http://web.utk.edu/~tnmug08/2013b.
  • 18. Federal Highway Administration (FHWA). Travel model validation and reasonableness checking manual-second edition, 2010. Available online at https:rosap.ntl.vts.gov/view/55924.
  • 19. Sansò B., Luc Milot L. Performability of a Congested Urban Transportation Network When Accident Information is Transportation Science. 1999; 33(1): 68–79. DOI: 10.1287/trsc.33.1.68.
  • 20. Lokku P.S., Prasad C.S.R.K., Krishna K.B. A Local Level Transit-Oriented Development Typology: Using Two-Step Clustering Technique. T. V. Mathew et al. (eds.), Transportation Research, Lecture Notes in Civil Engineering. 2020; 45. https://doi.org/10.1007/978–981–32–9042–6_4.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-29118947-8246-4eff-bc1b-4a539799a5ea
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