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2021-02-28
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Copyright (c) 2021 Rounaq Basu, Roberto Ponce-Lopez, Joseph Ferreira
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How to Cite
A framework to generate virtual cities as sandboxes for land use-transport interaction models
Rounaq Basu
Massachusetts Institute of Technology
Roberto Ponce-Lopez
Joseph Ferreira
DOI: https://doi.org/10.5198/jtlu.2021.1791
Keywords: Land use-transport interaction (LUTI) models, Virtual cities, Model generalizability, Model replicability, Model transferability
Abstract
One of the major critiques of land use-transport interaction (LUTI) models over the ages has been their over-dependence on individualized software and context. In an effort to address some of these concerns, this study proposes a framework to construct "virtual cities" that can act as sandboxes for testing different features of a LUTI model, as well as provide the capability to compare different LUTI models. We develop an approach to translate any prototypical transportation infrastructure network into a plausible land use zoning plan and synthetic population that are suitable for spatially detailed LUTI microsimulation of the virtual city. Disaggregate units of spatial geometry, like parcels and post codes, are generated using geospatial techniques applied to the transportation network. Households and jobs are randomly sampled from an actual city, and allocated in the virtual city based on matching density gradients. Students are matched with schools and workers are matched with jobs to complete the calibration of a synthetic population for the virtual city. Following the adjustment of behavioral models to complement the reduced scale of the virtual city, we demonstrate the integration between the land use and transportation simulation components in our LUTI model, SimMobility. The benefits of faster convergence times and shorter simulation times are clearly demonstrated through this exercise. We hope that this study, and the open-source releases of the SimMobility software with the virtual city database, can accelerate experimentation with LUTI models and aid the transition from individualized LUTI models to a common shared integrated urban modeling platform.
References
Acheampong, R. A. and E. A. Silva. 2015. Land use–transport interaction modeling: A review of the literature and future research directions. Journal of Transport and Land Use, 8(3):11–38. doi: 10.5198/jtlu.2015.806
Adams, P. C. 1998. Teaching and learning with Sim City 2000. Journal of Geography, 97(2):47–55.
Adnan, M., F. C. Pereira, C. M. L. Azevedo, K. Basak, M. Lovric, S. Raveau, Y. Zhu, J. Ferreira, C. Zegras, and M. Ben-Akiva. 2016. Simmobility: A multi-scale integrated agent-based simulation platform. In 95th Annual Meeting of the Transportation Research Board.
Azevedo, C. L., N. M. Deshmukh, B. Marimuthu, S. Oh, K. Marczuk, H. Soh, K. Basak, T. Toledo, L.-S. Peh, and M. E. Ben-Akiva. 2017. Simmobility short-term: An integrated microscopic mobility simulator. Transportation Research Record, 2622(1):13–23.
Bagchi, A., A. Sprintson, and C. Singh. 2009. Modeling the impact of fire spread on the electrical distribution network of a virtual city. In 41st North American Power Symposium, pp. 1–6. IEEE.
Basu, R., A. Araldo, A. P. Akkinepally, B. H. N. Biran, K. Basak, R. Seshadri, N. Deshmukh, N. Kumar, C. L. Azevedo, and M. Ben-Akiva. 2018a. Automated mobility-on-demand vs. mass transit: A multi-modal activity-driven agent-based simulation approach. Transportation Research Record. doi: 10.1177/0361198118758630.
Basu, R. and J. Ferreira. 2020a. Can increased accessibility from emerging mobility services create a car-lite future? Evidence from Singapore using LUTI microsimulation. Transportation Letters. doi: 10.1080/19427867.2020.1731993.
Basu, R. and J. Ferreira. 2020b. A LUTI microsimulation framework to evaluate the impact of autonomous mobility on the choice of housing-mobility bundles. Environment and Planning B: Urban Analytics and City Science. doi: 10.1177/2399808320925278.
Basu, R. and J. Ferreira. 2020c. Planning car-lite neighborhoods: Examining long-term impacts of accessibility boosts on vehicle ownership. Transportation Research Part D: Transport and Environment. doi: https://doi.org/10.1016/j.trd.2020.102394.
Basu, R., A. Jana, and R. Bardhan. 2018b. A health care facility allocation model for expanding cities in developing nations: strategizing urban health policy implementation. Applied Spatial Analysis and Policy, 11(1):21–36. doi: https://doi.org/10.1007/s12061-016-9208-0.
Batty, M. 2007. Model cities. Town Planning Review, 78(2):125–151.
Baum-Snow, N. 2007. Did highways cause suburbanization? The Quarterly Journal of Economics, 122(2):775–805.
Brumbelow, K., J. Torres, S. Guikema, E. Bristow, and L. Kanta. 2007. Virtual cities for water distribution and infrastructure system research. In World environmental and water resources congress 2007: Restoring our natural habitat, pp. 1–7.
Clarke, K. C., S. Hoppen, and L. Gaydos. 1997. A self-modifying cellular automaton model of historical urbanization in the san francisco bay area. Environment and planning B: Planning and design, 24(2):247–261.
Clay, M. J. 2010. Developing an integrated land-use/transportation model for small to medium-sized cities: Case study of Montgomery, Alabama. Transportation planning and technology, 33(8):679–693.
de la Barra, T. 1989. Integrated transport and land use modeling: Decision chains and hierarchies. Derrible, S. and C. Kennedy. 2011. Applications of graph theory and network science to transit network design. Transport reviews, 31(4):495–519.
Dong, X., M. E. Ben-Akiva, J. L. Bowman, and J. L. Walker. 2006. Moving from trip-based to activity-based measures of accessibility. Transportation Research Part A: policy and practice, 40(2):163–180.
Echenique, M. H., A. D. Flowerdew, J. D. Hunt, T. R. Mayo, I. J. Skidmore, and D. C. Simmonds. 1990. The meplan models of Bilbao, Leeds and Dortmund. Transport reviews, 10(4):309–322.
Feldt, A. G. 1972. Clug; Community land use game. player’s manual with selected readings.
Fortune, S. 1987. A sweepline algorithm for voronoi diagrams. Algorithmica, 2(1-4):153.
Hansen, W. G. 1959. How accessibility shapes land use. Journal of the American Institute of planners, 25(2):73–76.
Hawkins, J. and K. Nurul Habib. 2019. Integrated models of land use and transportation for the autonomous vehicle revolution. Transport reviews, 39(1):66–83.
Hunt, J. D. and J. E. Abraham. 2005. Design and implementation of PECAS: A generalised system for allocating economic production, exchange and consumption quantities. In Integrated land-use and transportation models: Behavioural foundations, pp. 253–273. Emerald Group Publishing Limited.
Iacono, M., D. Levinson, and A. El-Geneidy. 2008. Models of transportation and land use change: A guide to the territory. Journal of Planning Literature, 22(4):323–340.
Johnson, S. 2006. The ghost map: The story of London’s most terrifying epidemic–and how it changed science, cities, and the modern world. Penguin.
Knowles, R. D. 2012. Transit oriented development in Copenhagen, Denmark: From the finger plan to ørestad. Journal of Transport Geography, 22:251–261.
Lee, D. B. 1973. Requiem for large-scale models. Journal of the American Institute of Planners, 39(3):163–178.
Lerman, S. R. 1976. Location, housing, automobile ownership, and mode to work: a joint choice model. Transportation Research Record, 610:6–11.
Lopes, A. S., C. F. G. Loureiro, and B. Van Wee. 2019. LUTI operational models review based on the proposition of an a priori aluti conceptual model. Transport reviews, 39(2):204–225.
Lowry, I. S. 1964. A model of metropolis. Technical report, RAND CORP SANTA MONICA, CALIF.
Martinez, F. 1996. Mussa: Land use model for Santiago City. Transportation Research Record, 1552(1):126–134.
McFadden, D. 1978. Modeling the choice of residential location. Transportation Research Record, (673).
Miller, E. J. 2018. Integrated urban modeling: Past, present, and future. Journal of Transport and Land Use, 11(1):387–399. doi: https://doi.org/10.5198/jtlu.2018.1273.
Oke, O., Y. M. Aboutaleb, A. P. Akkinepally, C. L. Azevedo, Y. Han, P. C. Zegras, J. Ferreira, and M. Ben-Akiva. 2019. A novel global urban typology framework for sustainable mobility futures. Environmental Research Letters.
Papa, E. and L. Bertolini. 2015. Accessibility and transit-oriented development in European metropolitan areas. Journal of Transport Geography, 47:70–83.
Putman, S. H. 1974. Preliminary results from an integrated transportation and land use models package.
Transportation, 3(3):193–224.
Salvini, P. and E. J. Miller. 2005. Ilute: An operational prototype of a comprehensive microsimulation model of urban systems. Networks and spatial economics, 5(2):217–234.
Semboloni, F., J. Assfalg, S. Armeni, R. Gianassi, and F. Marsoni. 2004. Citydev, an interactive multiagents urban model on the web. Computers, Environment and Urban Systems, 28(1-2):45–64.
Simmonds, D. C. 1999. e design of the delta land-use modelling package. Environment and Planning B: Planning and Design, 26(5):665–684.
Strauch, D., R. Moeckel, M. Wegener, J. Gräfe, H. Mühlhans, G. Rindsfüser, and K.-J. Beckmann. 2005. Linking transport and land use planning: the microscopic dynamic simulation model ilumass. Geodynamics, pp. 295–311.
Sun, J., X. Yu, G. Baciu, and M. Green. 2002. Template-based generation of road networks for virtual city modeling. In Proceedings of the ACM symposium on Virtual reality software and technology, pp. 33–40. ACM.
Thiessen, A. H. 1911. Precipitation averages for large areas. Monthly weather review, 39(7):1082–1089.
Thomson, R. C. and D. E. Richardson. 1995. A graph theory approach to road network generalisation. In Proceeding of the 17th international cartographic conference, pp. 1871–1880.
Van Wee, B. 2015. Toward a new generation of land use transport interaction models. Journal of Transport and Land Use, 8(3), doi: doi.org/10.5198/jtlu.2015.611.
Vanegas, C. A., T. Kelly, B. Weber, J. Halatsch, D. G. Aliaga, and P. Müller. 2012. Procedural generation of parcels in urban modeling. In Computer Graphics Forum, volume 31, pp. 681–690. Wiley Online Library.
Vitins, B. J. and K. W. Axhausen. 2010. Patterns and grammars for transport network generation. In Proceedings of 14th Swiss Transportation Research Conference.
Waddell, P., A. Borning, M. Noth, N. Freier, M. Becke, and G. Ulfarsson. 2003. Microsimulation of urban development and location choices: Design and implementation of urbansim. Networks and Spatial Economics, 3(1):43–67.
Warburton, S. 2009. Second life in higher education: Assessing the potential for and the barriers to deploying virtual worlds in learning and teaching. British journal of educational technology, 40(3):414–426.
Weber, B., P. Müller, P. Wonka, and M. Gross. 2009. Interactive geometric simulation of 4d cities. In Computer Graphics Forum, volume 28, pp. 481–492. Wiley Online Library.
Webster, F. V. and M. Dasgupta. 1991. Land use and transport interactions: Report of the Isgluti study. Technical Report CR295; ISSN: 0266-7045, Transport and Road Research Laboratory.
Wegener, M. and K. Spiekermann. 2018. Multi-level urban models: Integration across space, time and policies. Journal of Transport and Land Use, 11(1). doi: https://doi.org/10.5198/jtlu.2018.1185.
Zhou, E., A. McGlaughlin, and D. Turan. 2015. Generating synthetic road networks from various reduced dimension representations. URL http://snap.stanford.edu/class/cs224w-2015/Generating_Synthetic_Road_Networks_from_Various_Reduced_Deimension_Representations.pdf.
Zhu, Y. and J. Ferreira. 2014. Synthetic population generation at disaggregated spatial scales for land use and transportation microsimulation. Transportation Research Record, 2429(1):168–177.
