Evaluating the Impact of an Integrated Urban Design of Transport Infrastructure and Public Space on Human Behavior and Environmental Quality: A Case Study in Beijing

  • Liu YangEmail author
  • Koen H. van Dam
  • Bani Anvari
  • Audrey de Nazelle
Part of the Springer Proceedings in Complexity book series (SPCOM)


Urban transport infrastructure can result in the physical, psychological and environmental separation of neighborhoods, public spaces and pedestrian networks, leading to negative impacts on citizens’ daily commutes, social activities and the quality of the ecosystem. An integrated design of transport infrastructure and public space is beneficial for mediating these negative impacts. In this paper, we propose an integrated methodology, which combines urban design, computational scenario evaluation and decision-making processes, based on a conceptual model of human and ecological needs-driven planning. To evaluate the impacts of the road network and public space design on individual outdoor activities, travel behavior and air pollution, an agent-based model is demonstrated. This model is then applied to a case study in Beijing, leading to hourly traffic volume maps and car-related air pollution heat maps of a baseline road network-public space design.


Urban transport infrastructure Human behavior Public space Agent-based modeling Policy-making support Environmental evaluation Air pollution simulation 


  1. Alberti, M., & Marzluff, J. M. (2004). Ecological resilience in urban ecosystems: Linking urban patterns to human and ecological functions. Urban Ecosystem, 7(3), 241–265. Scholar
  2. Axelrod, R. M. (1976). Structure of decision: The cognitive maps of political elites. Princeton: Princeton University Press.Google Scholar
  3. Axelrod, R. M. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton: Princeton University Press.CrossRefGoogle Scholar
  4. Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., et al. (2012). Smart cities of the future. [Article]. European Physical Journal-Special Topics, 214(1), 481–518. Scholar
  5. Bustos-Turu, G. (2018). Integrated modelling framework for the analysis of demand side management strategies in urban energy systems, PhD Thesis, Imperial College London, October 2018Google Scholar
  6. Carmona, M. (2003). Public places, urban spaces: The dimensions of urban design. Oxford: Architectural Press.Google Scholar
  7. China-Latest-Free. (2017). Geofabrik GmbH. Accessed 28 Feb 2018.
  8. de Nazelle, A., Nieuwenhuijsen, M. J., Antó, J. M., Brauer, M., Briggs, D., Braun-Fahrlander, C., et al. (2011). Improving health through policies that promote active travel: A review of evidence to support integrated health impact assessment. Environment International, 37(4), 766–777.CrossRefGoogle Scholar
  9. de Nazelle, A., Rodríguez, D. A., & Crawford-Brown, D. (2009). The built environment and health: Impacts of pedestrian-friendly designs on air pollution exposure. Science of the Total Environment, 407(8), 2525–2535.ADSCrossRefGoogle Scholar
  10. Department of Population and Employment Statistics National Bureau of Statistics. (2010). Tabulation on the 2010 population census of the People’s Republic of China. Beijing, China: China Statistics Press and Beijing Info Press.Google Scholar
  11. Department of Social and Science and Technology Statistics National Bureau of Statistics. (2008). 2008 time use survey in China. Beijing, China: China Statistics Press.Google Scholar
  12. Forrester, J. W. (1969). Urban dynamics. Cambridge, MA: MIT Press.Google Scholar
  13. Gan, W. (2014). Responsive urban simulation: An approach towards real time evaluation of urban design projects (Master’s thesis). Politecnico Di Milano, Milano, Italy.Google Scholar
  14. Geddes, S. P. (1915). Cities in evolution: An introduction to the town planning movement and to the study of civics. London: Williams & Norgate London.Google Scholar
  15. Horni, A., Nagel, K., & Axhausen, K. W. (2016). The multi-agent transport simulation MATSim. London: Ubiquity Press.CrossRefGoogle Scholar
  16. Jackson, T., Jager, W., & Stagl, S. (2004). Beyond insatiability: Needs theory, consumption and sustainability. ESRC Sustainable Technologies Programme Working Paper Series, 2.Google Scholar
  17. Long, Y., & Liu, X. (2013). Automated identification and characterization of parcels (AICP) with OpenStreetMap and points of interest (Working paper # 16). Beijing City Lab.Google Scholar
  18. Mallmann, C. (1980). Society, needs and rights: a systemic approach. In K. Lederer & J. V. Galtung (Eds.), Human needs: A contribution to the current debate (pp. 37–54). Cambridge, MA: Oelgeschlager, Gunn and Hain.Google Scholar
  19. Ravazzoli, E., & Torricelli, G. P. (2017). Urban mobility and public space. A challenge for the sustainable liveable city of the future. The Journal of Public Space, 2(2), 37–50.CrossRefGoogle Scholar
  20. Skiena, S. S. (1998). The algorithm design manual. London: Springer Science & Business Media.zbMATHGoogle Scholar
  21. UN-Habitat. (2015). Global public space toolkit: From global principles to local policies and practice. Nairobi: United Nations Human Settlements Programme.Google Scholar
  22. van Dam, K. H., Bustos-Turu, G., & Shah, N. (2017). A methodology for simulating synthetic populations for the analysis of socio-technical infrastructures. In W. Jager et al. (Eds.), Advances in social simulation 2015 (Vol. 528). Cham: Springer.Google Scholar
  23. van Dam, K. H., Koering, D., Bustos-Turu, G., & Jones, H. (2014). Agent-based simulation as an urban design tool: Iterative evaluation of a smart city masterplan. In The Fifth Annual Digital Economy All Hands Conference.Google Scholar
  24. Varnelis, K. (2008). The infrastructural city: Networked ecologies in Los Angeles. Barcelona: Actar.Google Scholar
  25. Yang, L., Zhang, L., Stettler, M. E. J., Sukitpaneenit, M., Xiao, D., & van Dam, K. H. (2019). Supporting an integrated transportation infrastructure and public space design: A coupling simulation methodology for evaluating traffic pollution and microclimate. Sustainable Cities and Society. Scholar
  26. Zellner, M. L. (2008). Embracing complexity and uncertainty: The potential of agent-based modeling for environmental planning and policy. Planning Theory & Practice, 9(4), 437–457. Scholar
  27. Zhao, P., Chapman, R., Randal, E., & Howden-Chapman, P. (2013). Understanding resilient urban futures: A systemic modelling approach. Sustainability, 5(7), 3202–3223. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Liu Yang
    • 1
    Email author
  • Koen H. van Dam
    • 2
  • Bani Anvari
    • 3
  • Audrey de Nazelle
    • 4
  1. 1.Center of Architecture Research and Design, University of Chinese Academy of SciencesBeijingChina
  2. 2.Department of Chemical EngineeringImperial College LondonLondonUK
  3. 3.Centre for Transport Studies, University College LondonLondonUK
  4. 4.Centre for Environmental Policy, Imperial College LondonLondonUK

Personalised recommendations