Urban form and travel behavior: The interplay with residential self-selection and residential dissonance

Author(s):  
Veronique Van Acker
2018 ◽  
Vol 69 ◽  
pp. 98-105 ◽  
Author(s):  
Erick Guerra ◽  
Camilo Caudillo ◽  
Paavo Monkkonen ◽  
Jorge Montejano

Author(s):  
Susan Krumdieck

Oil resources are finite and production decline is a fact for this century. The question is, why there has been so little policy action? This paper proposes that dealing with the complex changes involved in the transition to oil supply contraction requires new kinds of engineering modeling and analysis. There are no miracle technologies that will mitigate the need for major policy, economic, infrastructure and land use changes. Researchers have the responsibility to develop new methods and tools necessary for policy makers and planners to manage this change in direction. Without the right tools, the policy choice is between denying the problem and hoping for miracles. With the right Transition Engineering tools, the policy choices involve changes in land use, incentives, taxes and investments that efficiently reduce vulnerability and risk, increase adaptive capacity and build resilience. For more than a decade, the research and development program at the Advanced Energy and Material Systems Lab (AEMSLab) has focused on Transition Engineering. The first Transition Engineering project assesses vulnerability and risk to essential activities from oil supply contraction in the near and long term. The risk assessment method employs a probabilistic model of future fuel availability and an impact model of travel behavior adaptation to meet the probable fuel constraint. The second project is to assess travel adaptive capacity of current travel behavior and of the current urban forms using a new kind of travel survey, and to develop adaptation models for different urban development scenarios. Another important analysis is the active mode accessibility of the current urban form. The model uses GIS data and an activity model based on the demographic profile. Future urban form development, technology and infrastructure investments and behavior change are modeled using the strategic analysis method.


Author(s):  
Kevin J. Krizek

Communities are increasingly looking to land use planning strategies based on a less auto-dependent urban form to reduce the need for travel, especially drive-alone travel. In recent years, several studies have attempted to test the impact urban form has on travel behavior to determine if such designs are warranted. The results of these studies are mixed because of several shortcomings. Some shortcomings can be attributed to data availability; others are a product of the techniques used to characterize urban form or travel. Still other shortcomings are embedded in the strategies employed, using cross-sectional travel data and correlating travel outcomes with urban form. The line of research is being extended, aimed at isolating the influence of urban form on travel behavior; a new research strategy is presented using longitudinal travel data in concert with detailed measures of travel behavior and urban form. Data sources from the Puget Sound are described and a research strategy is presented that permits a pretest-posttest analysis of households’ travel behavior before and after they changed residential location. Early results show few changes in household travel behavior after a move, suggesting that attitudes toward travel are firmly entrenched and postmove travel provides little insight into how changes in urban form affect travel. Although a pretest-posttest makes valiant strides in shedding new light on the matter, the complex phenomenon being addressed requires myriad approaches. More comprehensive research techniques and even research approaches based on different different traditions are much needed to better understand how urban form and travel interact.


2018 ◽  
Author(s):  
Geoff Boeing

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in two dimensions without any underpasses or overpasses. However, real-world urban street networks exist in three-dimensional space and frequently feature grade separation such as bridges and tunnels: planar simplifications can be useful but they also impact the results of real-world street network analysis. This study measures the nonplanarity of drivable and walkable street networks in the centers of 50 cities worldwide, then examines the variation of nonplanarity across a single city. It develops two new indicators - the Spatial Planarity Ratio and the Edge Length Ratio - to measure planarity and describe infrastructure and urbanization. While some street networks are approximately planar, we empirically quantify how planar models can inconsistently but drastically misrepresent intersection density, street lengths, routing, and connectivity.


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