JTLU Volume 8, No. 3 (2015)

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Table of Contents:
  • Viewpoint: Toward a new generation of land use transport interaction models, pp. 1-10
  • Land use–transport interaction modeling: A review of the literature and future research directions, pp. 11-38
  • Forecasting inaccuracies: a result of unexpected events, optimism bias, technical problems, or strategic misrepresentation?, pp. 39-55
  • Assessing and integrating uncertainty into land-use forecasting, pp. 57-70
  • Integrating activity-based travel-demand models with land-use and other long-term lifestyle decisions, pp. 71-93
  • Toward spatial justice: The spatial equity effects of a toll road in Cape Town, South Africa, pp. 95-114
  • Urban form and life-cycle energy consumption: Case studies at the city scale, pp. 115-128
  • Evaluating air pollution exposures across cycling infrastructure types: Implications for facility design, pp. 131-149
  • Bi-level cellular agent-based model: Simulation of potential impacts of high-speed rail on land cover change in the Lisbon Metropolitan Area, Portugal, pp. 151-180
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    • Item
      Viewpoint: Toward a new generation of land use transport interaction models
      (Journal of Transport and Land Use, 2015) van Wee, Bert
      Land use transport interaction (LUTI) models are often developed to model the interaction between the land use and transport systems for relatively large-scale spatial developments, like new residential or office areas, new main roads, or railway lines. In this paper I argue that we need a next generation of LUTI models that model trends such as peak car; decline in population, shops, services, etc.; impact of information and communications technology (ICT) on activity patterns and travel; and cycling policies. The current generation of LUTI models cannot adequately answer the policy questions raised by these trends. However, a major problem is that the future of these trends is uncertain, and we lack empirical research into the dynamics between these trends and their wider impact on land use and transport systems. Nevertheless, LUTI models can, by utilizing what-if calculations, help explore future trends and their implications. Other challenges for LUTI models include the calculation of a wider set of accessibility indicators, the inclusion of interactions between key actors in the transport and land-use system—serious gaming may prove a useful way to explore these interactions—and the development of dynamic visualizations.
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      Land use–transport interaction modeling: A review of the literature and future research directions
      (Journal of Transport and Land Use, 2015) Acheampong, Ransford A.; Silva, Elisabete A.
      The aim of this review paper is to provide comprehensive and up-to-date material for both researchers and practitioners interested in land-use-transport interaction (LUTI) modeling. The paper brings together some 60 years of published research on the subject. The review discusses the dominant theoretical and conceptual propositions underpinning research in the field and the existing operational LUTI modeling frameworks as well as the modeling methodologies that have been applied over the years. On the basis of these, the paper discusses the challenges, on-going progress and future research directions around the following thematic areas: 1) the challenges imposed by disaggregation—data availability, computation time, stochastic variation and output uncertainty; 2) the challenges of and progress in integrating activity-based travel demand models into LUTI models; 3) the quest for a satisfactory measure of accessibility; and 4) progress and challenges toward integrating the environment into LUTI models.
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      Forecasting inaccuracies: a result of unexpected events, optimism bias, technical problems, or strategic misrepresentation?
      (Journal of Transport and Land Use, 2015) Naess, Petter; Andersen, Jeppe Astrup; Nicolaisen, Morten Skou; Strand, Arvid
      Based on the results from a questionnaire survey and qualitative interviews among different actors involved in traffic forecasting, this paper discusses what evidence can be found in support of competing explanations of forecasting errors. There are indications that technical problems and manipulation, and to a lesser extent optimism bias, may be part of the explanation of observed systematic biases in forecasting. In addition, unexpected events can render the forecasts erroneous, and many respondents and interviewees consider it to be simply not possible to make precise predictions about the future. The results give rise to some critical reflections about the reliability of project evaluations based on traffic forecasts susceptible to several systematic as well as random sources of error.
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      Assessing and integrating uncertainty into land-use forecasting
      (Journal of Transport and Land Use, 2015) Ševčíková, Hana; Simonson, Mark; Jensen, Michael
      Uncertainty in land use and transportation modeling has received increasing attention in the past few years. However, methods for quantifying uncertainty in such models are usually developed in an academic environment and in most cases do not reach users of official forecasts, such as planners and policymakers. In this paper, we describe the practical application of a methodology called Bayesian melding and its integration into the land-use forecast published by the Puget Sound Regional Council, a metropolitan planning organization. The method allows practitioners to assess uncertainty about forecasted quantities, such as households, population, and jobs, for each geographic unit. Users are provided with probability intervals around forecasts, which add value to model validation, scenario comparison, and external review and comment procedures. Practical issues such as how many runs to use or assessing uncertainty for aggregated regions are also discussed.
    • Item
      Integrating activity-based travel-demand models with land-use and other long-term lifestyle decisions
      (Journal of Transport and Land Use, 2015) Katoshevski-Cavari, Rachel; Glickman, Inbal; Ishaq, Robert; Shiftan, Yoram
      This paper extends and integrates the general activity-based model framework to present the complex relationship between long-term individual decisions, such as residential location, and daily activity and travel-behavior decisions. More specifically, it demonstrates the use of an activity-based accessibility (ABA) measure as an important variable in residential zone choice, thus serving as the link between short-term activity and travel decisions and long-term residential choice decisions. We develop a partial activity-based model accounting for the interrelationship of the main activity type, travel destination and mode choice. The log-sum at the top of the hierarchy of this model is the ABA measure capturing the overall utility of all travel alternatives. The results show that this measure is a highly significant variable in the residential-choice model, clearly indicating the great influence of activity accessibility, short-term opportunities, and travel decisions on residential area choice. All other log-sums were also significant, showing the interrelationships of all choices. Specifically, the destination-choice log-sum in the main activity-choice model demonstrates that as accessibility increases, people are more likely to participate in out-of-home activities.
    • Item
      Toward spatial justice: The spatial equity effects of a toll road in Cape Town, South Africa
      (Journal of Transport and Land Use, 2015) van Dijk, Justin Tycho; Krygsman, Stephan; de Jong, Tom
      The present study sets out to provide an ex ante insight into the equity effects of a toll charge on the traffic diversions and geographical accessibility of work locations in the Cape Town metropolitan region, South Africa. Based on a static traffic assignment model and aggregate accessibility measures, computed in a GIS environment, the effects of a toll were estimated for different income categories for both a reference scenario and two toll scenarios. The findings indicate that particularly low-income commuters will divert to alternative routes. However, the results also indicate that the introduction of a toll will only have a limited impact on geographical accessibility. Nevertheless, because particularly low-income commuters are likely to divert to alternative routes, a toll should maybe not be levied on the road toward spatial justice without revenue redistribution or additional investment in the public transport system.
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      Urban form and life-cycle energy consumption: Case studies at the city scale
      (Journal of Transport and Land Use, 2015) Nichols, Brice G.; Kockelman, Kara M.
      By combining daily (operations) and embodied energy demands, this work estimates life-cycle energy demands for residents and workers in different city settings. Using life-cycle analyses (LCAs) of different neighborhood types in Austin, Texas, this analysis fabricates five different city types, reflecting actual accessibility and resident and employment density profiles. Five residential and three commercial neighborhood types are distributed across 16-kilometer (10-mile) radius regions, with demographics held constant, for comparability. As expected, per-capita daily energy demands decrease with increased resident and employment density. Interestingly, embodied energy savings via increases in density are substantial. Though embodied energy makes up only 10-20 percent of total life-cycle energy, per-capita savings via density suggest it should be included in planning analyses. Overall, average life-cycle per-capita energy use ranges from 140 gigajoule (GJ)/year/capita in the least dense Orlando-style setting to around 90 GJ/ year/capita in the maximum-density scenario, corresponding to a 35 percent reduction in per-capita energy demand. Energy reductions for Phoenix, Austin, and Seattle settings (relative to an Orlando-based de- sign) are 18, 22, and 24 percent per-capita, respectively. Results provide a rare view of how total annual energy demands in both residential and commercial sectors are affected by density.
    • Item
      Evaluating air pollution exposures across cycling infrastructure types: Implications for facility design
      (Journal of Transport and Land Use, 2015) Farrell, William J.; Weichenthal, Scott; Goldberg, Mark; Hatzopoulou, Marianne
      Expanding urban cycling networks requires consideration of a number of important factors. Yet there exists no set of best practices and surprisingly little research detailing which sorts of cycling infrastructure may be better or worse in terms of exposure to harmful pollutants. A large air-quality data collection campaign was conducted in summer 2012 whereby cyclists equipped with ultrafine particle (UFP) and black carbon (BC) monitors covered over 550 kilometers of streets, including 325 kilometers of designated cycling facilities on the Island of Montreal. The clearest result from this exercise is that pollution levels on trails, often far from vehicular streets, are markedly lower than cycling facilities located on or alongside the street. For in-street and separated facilities, both UFP and BC were more closely associated with the hierarchy of the street than the type of cycling facility. Between in-street and separated facilities, the difference in UFP levels was not statistically significant. However, the difference between BC levels on in-street and separated facilities was significant, with separated facilities yielding lower concentrations. Ultimately, more research is needed to understand the potential efficacy of facility and network design as a pollution exposure abatement measure; however, these findings show moderate advantages of separated facilities over in-street facilities and more substantial advantages for off-road facilities over either.
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      Bi-level cellular agent-based model: Simulation of potential impacts of high-speed rail on land cover change in the Lisbon Metropolitan Area, Portugal
      (Journal of Transport and Land Use, 2015) Shen, Yu; Chen, Guineng; Martínez, Luís Miguel; Silva, João de Abreu e
      This paper presents a bi-level cellular agent-based model (ABM) framework, which incorporates a land cover change sub-model at the local level and a socioeconomic activity growth sub-model at the regional level. In the local sub-model, a land cell is set as an agent, of which the land-cover change decisions are mainly influenced by spatial mixed logit models. The regional sub-model is driven by fixed effects panel models, generating estimates of socioeconomic variables, thanks to the accessibility improvement and local land development. The regional outputs are also distributed into the local sub-models as their inputs. By inputting the historical data of the Lisbon Metropolitan Area (LMA) in 1991, a back-casting simulation was executed for validation. It compares the simulated outputs in 2011 with the actual reference data, based on multiple resolution goodness-of-fit (MRG) methods. Three scenarios are then designed to study the potential im- pacts of high-speed rail (HSR) on land-cover change in the LMA according to different proposals of HSR station locations. The scenarios indicate that without HSR the un-built lands in the LMA are likely to be largely developed if the annual GDP growth rate holds at 1.5 percent. With HSR the simulation suggests that land development is accelerated. The opening of an additional HSR station in Setúbal besides Lisbon-Oriente does not act as an obstacle to the urbanization process in the LMA, although it reduces HSR speed and the resulting regional accessibility. However, the contribution of the added station to the land-development process is also limited. Only a few areas are likely to benefit.