Realization of Two Types of Compact City - Street Activeness and Tramway -

The purpose of this research is to verify the effectiveness of the combination of the introduction of a tramway with introducing a public facility for urban residents and implementing a policy to promote activeness around it, on urban sprawl. By using an agent-based model (ABM), which was built for simulating urban structure changes through autonomous behavior of urban residents, this research clarified that, depend on the urban initial state, the combination of these policies can lead the two different types of compact city: the polycentric-form and the monocentric-form.

[1]  Eric J. Miller,et al.  Urban Form, Energy and the Environment: A Review of Issues, Evidence and Policy , 1996 .

[2]  Brent Yarnal,et al.  Uncertainty awareness in urban sprawl simulations: Lessons from a small US metropolitan region , 2009 .

[3]  J. Jacobs,et al.  The Economy of Cities , 1969 .

[4]  G. Nigel Gilbert,et al.  Agent-Based Models , 2007 .

[5]  Hideyuki Nagai,et al.  Bustle Changes the City - Facility for Stopping Off and Modeling Urban Dynamics - , 2017 .

[6]  Yu-hsin Tsai.  Quantifying Urban Form: Compactness versus 'Sprawl' , 2005 .

[7]  Steven F. Railsback,et al.  Agent-Based and Individual-Based Modeling: A Practical Introduction , 2011 .

[8]  Elisabete A. Silva,et al.  Land use–transport interaction modeling: A review of the literature and future research directions , 2015 .

[9]  Randy Gimblett,et al.  The simulation and visualization of complex human–environment interactions , 2001 .

[10]  Arnold K. Bregt,et al.  Multi-actor-based land use modelling: spatial planning using agents , 2001 .

[11]  Tadahiro Taniguchi,et al.  Multi-agent Simulation about Urban Dynamics Based on a Hypothetical Relationship between Individuals' Travel Behavior and Residential Choice Behavior , 2011 .

[12]  Zvi Eckstein,et al.  Cities and Growth: Theory and Evidence from France and Japan , 1994 .

[13]  Michael Batty,et al.  Cities and complexity - understanding cities with cellular automata, agent-based models, and fractals , 2007 .

[14]  Hans de Bruijn,et al.  Decision-making for light rail , 2009 .

[15]  J. Brueckner.  Urban Sprawl: Lessons from Urban Economics , 2001 .

[16]  Daniel Schunk,et al.  Spatial Dynamic Modeling and Urban Land Use Transformation , 2003 .

[17]  Dai Nakagawa,et al.  Measuring walkability and its effect on light rail usage: a comparative study of the USA and Japan , 2014 .

[18]  I. Benenson.  MULTI-AGENT SIMULATIONS OF RESIDENTIAL DYNAMICS IN THE CITY , 1998 .

[19]  R. Lucas.  On the Mechanics of Economic Development , 1988 .

[20]  Declan Redmond,et al.  An examination of residential preferences for less sustainable housing , 2009 .

[21]  Michael P. Johnson.  Environmental Impacts of Urban Sprawl: A Survey of the Literature and Proposed Research Agenda , 2001 .

[22]  Fulong Wu,et al.  Calibration of stochastic cellular automata: the application to rural-urban land conversions , 2002, Int. J. Geogr. Inf. Sci..

[23]  Pavlos S. Kanaroglou,et al.  Smart growth strategies, transportation and urban sprawl: simulated futures for Hamilton, Ontario , 2008 .

[24]  R. Ewing.  Is Los Angeles-Style Sprawl Desirable? , 1997 .

[25]  C. Woodcock,et al.  Compact, Dispersed, Fragmented, Extensive? A Comparison of Urban Growth in Twenty-five Global Cities using Remotely Sensed Data, Pattern Metrics and Census Information , 2008 .

[26]  Darren M. Scott,et al.  Impacts of commuting efficiency on congestion and emissions: case of the Hamilton CMA, Canada , 1997 .