Modelling Effects of Land Use Changes on Traffic Based on Proposed Traffic Simulator

Document Type : Original Article

Authors

Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Lavizan, Tehran, Iran

Abstract

In this paper, a traffic simulator is designed in order to investigate the travel demand based on GIS data and analysis. In order to evaluate the proposed simulator, four different scenarios are provided for the arrangement of land use services. In first scenario, all service land use are located in the middle of the region; in second scenario, land use services located on the periphery of the region; in the third scenario, land use is defined regularly in the entire area; and finally, in the last scenario, unchanged statuses are evaluated. The comparison parameters are Vehicle Miles of Travel (VMT) and Vehicle Hours of Travel (VHT), which are measured for these four scenarios. The analysis of the results shows that the regular distribution of land use service (scenario 3), with VHT, mean of 33.01 minutes is the best scenario, while scenario 2 with a VHT average of 35.12 minutes has the worst performance.

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References

[1]     Behzadi S, Alesheikh AA. Introducing a novel model of belief–desire–intention agent for urban land use planning. Eng Appl Artif Intell 2013;26:2028–44. doi:10.1016/j.engappai.2013.06.015.
[2]     Qi H, Wang W, Lu J. Study on the Relationship between Urban Land-Use and Traffic Generation with Remote Sensing and PLSR. ICCTP 2011, Reston, VA: American Society of Civil Engineers; 2011, p. 302–14. doi:10.1061/41186(421)32.
[3]     D. S. Transportation for a Livable City. San Francisco CA; 2002, Retrieved July 2, 2013 n.d.
[4]     Mousavi Z, Behzadi S. Geo-Portal Implementation with a Combined Approach of AHP and SWOT. Int J Nat Sci Res 2019;7:22–31.
[5]     Guo Z, Agrawal AW, Dill J. Are Land Use Planning and Congestion Pricing Mutually Supportive? J Am Plan Assoc 2011;77:232–50. doi:10.1080/01944363.2011.592129.
[6]     Mitchell RB, Rapkin C. Urban traffic: A function of land use. Columbia University Press; 1954.
[7]     Behzadi S, Alesheikh AA. Cellular Automata vs. Object-Automata in Traffic Simulation. Int J Remote Sens Appl 2014;4:61. doi:10.14355/ijrsa.2014.0401.07.
[8]     Litman T, Steele R. Land use impacts on transport. Victoria Transport Policy Institute Canada; 2017.
[9]     Soltani A, Saghapoor T, Izadi H, Pakshir A. Trip generation and its relationship with land use diversity: Case studies of four urban districts in Shiraz metropolitan area 2012.
[10]   Mousavi Z, Behzadi S. Introducing an Appropriate Geoportal Structure for Managing Wildlife Location Data. Int J Nat Sci Res 2019;7:32–48.
[11]   Morimoto A. Transportation and land use in Doi, K. (ed.) Traffic and safety sciences: Interdisciplinary Wisdom of IATSS. 2015.
[12]   Shubho MTH, Neema MN. Impact of land use change on prodigious traffic growth towards impeding livability of a city. Environ Ecol Manag 2014;2014:1–15.
[13]   Arnott R, Inci E, Rowse J. Downtown Parking and Traffic Congestion: A Diagrammatic Exposition 2012.
[14]   Council AT. National guidelines for transport system management in Australia. Backgr Mater 2006;5.
[15]   Giuliano G. Land use impacts of transportation investments. Geogr Urban Transp 2004;3:237–73.
[16]   Gehrke SR, Clifton KJ. An activity-related land use mix construct and its connection to pedestrian travel. Environ Plan B Urban Anal City Sci 2019;46:9–26.
[17]   Zhang T, Sun L, Yao L, Rong J. Impact Analysis of Land Use on Traffic Congestion Using Real-Time Traffic and POI. J Adv Transp 2017;2017:1–8. doi:10.1155/2017/7164790.
[18]   Wingo L. An economic model of the utilization of urban land for residential purposes. Pap Reg Sci Assoc 1961;7:191–205. doi:10.1007/BF01969080.
[19]   Alonso W. Location and land use. toward a general theory of land rent. Locat L Use Towar a Gen Theory L Rent 1964.
[20]   Izraeli O, McCarthy TR. Variations in travel distance, travel time and model choice among smsas. J Transp Econ Policy 1985:139–60.
[21]   Handy S. How land use patterns affect travel patterns: A bibliography. 1992.
[22]   Gordon P, Kumar A, Richardson HW. Congestion, Changing Metropolitan Structure, and City Size in the United States. Int Reg Sci Rev 1989;12:45–56. doi:10.1177/016001768901200103.
[23]   Ewing R, Pendall R, Chen D. Measuring Sprawl and Its Transportation Impacts. Transp Res Rec J Transp Res Board 2003;1831:175–83. doi:10.3141/1831-20.
[24]   Wachs M. Transportation Policy, Poverty, and Sustainability. Transp Res Rec J Transp Res Board 2010;2163:5–12. doi:10.3141/2163-01.
[25]   Quade PB, Douglas. Douglas. Land Use Impacts of Transportation A Guidebook_Integration of Land Use Planning with Multimodal Transportation Planning. 1998 1998:127–46.
[26]   Tseng F-H, Hsueh J-H, Tseng C-W, Yang Y-T, Chao H-C, Chou L-D. Congestion prediction with big data for real-time highway traffic. IEEE Access 2018;6:57311–23.
[27]   Waddell P. UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning. J Am Plan Assoc 2002;68:297–314. doi:10.1080/01944360208976274.
[28]   Peng Z-R, Zhao L-Y, Yang F. Development of a prototype land use model for statewide transportation planning activities. 2011.
[29]   Acheampong RA, Silva EA. Land use–transport interaction modeling: A review of the literature and future research directions. J Transp Land Use 2015;8:11–38.
[30]   Stults M. Integrating climate change into hazard mitigation planning: Opportunities and examples in practice. Clim Risk Manag 2017;17:21–34. doi:10.1016/j.crm.2017.06.004.
[31]   Kim JH, Hipp JR, Basolo V, Dillon HS. Land Use Change Dynamics in Southern California: Does Geographic Elasticity Matter? J Plan Educ Res 2018;38:39–53. doi:10.1177/0739456X16688252.
[32]   Babiso B, Toma S, Bajigo A. Land use/land cover dynamics and its implication on sustainable land management in Wallecha watershed, southern Ethiopia. Glob J Sci Front Res H Environ Earth Sci 2016;16:49–53.
[33]   Waddell P, Borning A, Noth M, Freier N, Becke M, Ulfarsson G. Microsimulation of urban development and location choices: Design and implementation of UrbanSim. Networks Spat Econ 2003;3:43–67.
[34]   Miller E. The case for microsimulation frameworks for integrated urban models. J Transp Land Use 2018;11:1025–37.
[35]   Pursula M. Simulation of traffic systems-an overview. J Geogr Inf Decis Anal 1999;3:1–8.
[36]   Bieker L, Krajzewicz D, Morra A, Michelacci C, Cartolano F. Traffic Simulation for All: A Real World Traffic Scenario from the City of Bologna, 2015, p. 47–60. doi:10.1007/978-3-319-15024-6_4.
[37]   Lemos LL, Bazzan ALC. Combining adaptation at supply and demand levels in microscopic traffic simulation: a multiagent learning approach. Transp Res Procedia 2019;37:465–72. doi:10.1016/j.trpro.2018.12.217.
[38]   Sokolowski JA, Banks CM. Principles of modeling and simulation: a multidisciplinary approach. John Wiley & Sons; 2011.
[39]   Hunter M, Biswas A, Chilukuri B, Guin A, Fujimoto R, Guensler R, et al. Energy-Aware Dynamic Data-Driven Distributed Traffic Simulation for Energy and Emissions Reduction. Handb. Dyn. Data Driven Appl. Syst., Cham: Springer International Publishing; 2018, p. 467–87. doi:10.1007/978-3-319-95504-9_20.
[40]   Li D, Cova TJ, Dennison PE. Setting Wildfire Evacuation Triggers by Coupling Fire and Traffic Simulation Models: A Spatiotemporal GIS Approach. Fire Technol 2019;55:617–42. doi:10.1007/s10694-018-0771-6.
[41]   Amarasinghe UGLS, Rajapakse RACP. Swarm intelligence for urban traffic simulation: Results from an Agent-based modeling and simulation study of the Sri Lankan context. International Research Conference on Smart Computing and Systems Engineering-SCSE 2018.
[42]   The population of Tehran is derived from the website: http://worldpopulationreview.com/world-cities/tehran-population/ n.d.
[43]   Mohammadiha A, Malakooti H, Esfahanian V. Development of reduction scenarios for criteria air pollutants emission in Tehran Traffic Sector, Iran. Sci Total Environ 2018;622–623:17–28. doi:10.1016/j.scitotenv.2017.11.312.
[44]   Moradi A, Soori H, Kavousi A, Eshghabadi F, Jamshidi E, Zeini S. Spatial analysis to identify high risk areas for traffic crashes resulting in death of pedestrians in Tehran. Med J Islam Repub Iran 2016;30:450.
[45]   Heger M, Sarraf M. Air Pollution in Tehran. World Bank; 2018. doi:10.1596/29909.
[46]   Kantor Y, Rietveld P, van Ommeren J. Towards a general theory of mixed zones: The role of congestion. J Urban Econ 2014;83:50–8. doi:10.1016/j.jue.2014.08.003.
[47]   Lyu X, Han Q, Vries B de. Validation of a simulation system exploring land-use impacts on travel behavior. Transp Res Procedia 2019;37:51–8. doi:10.1016/j.trpro.2018.12.165.
[48]   Reisi M, Aye L, Rajabifard A, Ngo T. Land-use planning: Implications for transport sustainability. Land Use Policy 2016;50:252–61. doi:10.1016/j.landusepol.2015.09.018.

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History

  • Receive Date: 07 November 2019
  • Revise Date: 09 January 2020
  • Accept Date: 20 January 2020

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