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Accessibility is a key instrument for assessing active mobility. However, accessibility measures oftensuffer from biases due to spatial aggregation, isochrones with arbitrary cut-offs, and distance-basedcost functions that ignore the route conditions. Previous literature has addressed these issuesindividually, but not holistically. This study applies the MATSim framework to efficiently routebetween billions of origin-destination pairs to calculate fully disaggregate Hansen accessibilities usingcost functions sensitive to network quality. With examples of greenspace and foodstore accessibility,we demonstrate the potential of this method for providing policy-relevant insight into the suitability ofthe built environment for active travel.

Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.

The United Nations have developed Sustainable Development Goals (SDG) to guide countries&rsquo, development in the next decades. In this paper, we first propose a set of measurable indicators that define the degree of achievement of SDG. Secondly, we use a microscopic integrated land use and transportation model to define future scenarios and measure SDG in the future with radical policies. The model is implemented in Munich and Kagawa. The results are not uniform across policies: while the core cities scenario limits urban sprawl and consumption of greenfield land, traffic conditions and GHG emissions worsened. Furthermore, the scenarios also show the relevance of testing policies in different study areas: the core city scenario and the draconic resettlement scenario showed some impact on vehicle-kilometers traveled in Munich, while the impact in the Kagawa region was almost negligible. In general, only strong (and perhaps implausible) relocation policies result in overall significant changes in the SDG indicators.

Problem, research strategy, and findings: Planners today are confronted with unprecedented uncertainty in economic, political, and technological environments, especially at the regional scale. An increasingly common approach to addressing such uncertainty is exploratory scenario analysis. To provide new insights into the methods and utility of such analyses, we conducted a scenario analysis of the Baltimore (MD)–Washington (DC) region by engaging a technical advisory committee and exercising a loosely coupled suite of advanced transportation, land use, and environmental impact models. Our analysis suggests the future is indeed uncertain and may evolve into plausible but quite different alternative scenarios. Key drivers of these scenarios include fuel prices; the rate and form of technological change, especially in the transportation sector; and the restrictiveness of land use controls. Takeaway for practice: By developing exploratory scenario analyses and analyzing them using advanced computational models, planners can gain insights into how best to address uncertain development trends, such as how and to what degree planners can influence the adoption of electric and automated vehicles, how and where to guide development patterns through land use controls, and how best to respond to variation in the cost of energy, which could have dramatic impacts on the future sustainability of cities and regions. Although such scenario analyses cannot in most circumstances provide unambiguous robust or contingent policy prescriptions, they can provide important insights for raising public awareness and provide the foundation for further policy evaluation.

Citizens are increasingly sharing their location and movements through “check-ins” on location based social networks (LBSNs). These services are collecting unprecedented amounts of big data that can be used to study how we travel and interact with our environment. This paper presents the development of a long distance destination choice model for Ontario, Canada, using data from Foursquare to model destination attractiveness. A methodology to collect and process historical check-in counts has been developed, allowing the utility of each destination to be calculated based on the intensity of different activities performed at the destination. Destinations such as national parks and ski areas are very strong attractors of leisure trips, yet do not employ many people and have few residents. Trip counts to such destinations are therefore poorly predicted by models based on population and employment. Traditionally, this has been remedied by extensive manual data collection. The integration of Foursquare data offers an alternative approach to this problem. The Foursquare based destination choice model was evaluated against a traditional model estimated only with population and employment. The results demonstrate that data from LBSNs can be used to improve destination choice models, particularly for leisure travel. ISSN:2220-9964

Background: The appropriate resolution of a zone system is key to the development of any transport model, as well as other spatial analyses. The number and shape of zones directly impacts the effectiveness of any further modeling steps, with the trade-off between computation time and model accuracy being a particularly important consideration. Currently, zone systems are often designed by hand. The gradual rasterization zoning algorithm produces good empirical results by computationally generating raster cells of varying area, but similar population and employment.Methods: We address several limitations of the original algorithm in this paper. Firstly, the allocation of employment to raster cells is weighted by land use instead of by area percentage. Secondly, the algorithm is extended to respect municipal delineations. Raster cells are split along these delineations, with any undesirably small zones created by this process re-merged with neighbors in the same municipality. Aligning the generated cells to municipalities simplifies and improves the disaggregation of socioeconomic data. An iterative algorithm has been developed to automatically determine the threshold that results in the zone system of the desired size. Raster cells are split along these delineations, with any undesirably small zones created by this process re-merged with neighbors in the same municipality.Results and Conclusion: Aligning the generated cells to municipalities simplifies and improves the disaggregation of socioeconomic data. Using this algorithm, a zone system has been generated for the Munich metropolitan region. Only 13 iterations were needed to converge within 5% of target of 5000 delineated zones. The improved algorithm maintains the advantages of the original algorithm and adds several important improvements that are useful when creating a zone system.

Background: The appropriate resolution of a zone system is key to the development of any transport model, as well as other spatial analyses. The number and shape of zones directly impacts the effectiveness of any further modeling steps, with the trade-off between computation time and model accuracy being a particularly important consideration. Currently, zone systems are often designed by hand. The gradual rasterization zoning algorithm produces good empirical results by computationally generating raster cells of varying area, but similar population and employment.Methods: We address several limitations of the original algorithm in this paper. Firstly, the allocation of employment to raster cells is weighted by land use instead of by area percentage. Secondly, the algorithm is extended to respect municipal delineations. Raster cells are split along these delineations, with any undesirably small zones created by this process re-merged with neighbors in the same municipality. Aligning the generated cells to municipalities simplifies and improves the disaggregation of socioeconomic data. An iterative algorithm has been developed to automatically determine the threshold that results in the zone system of the desired size. Raster cells are split along these delineations, with any undesirably small zones created by this process re-merged with neighbors in the same municipality.Results and Conclusion: Aligning the generated cells to municipalities simplifies and improves the disaggregation of socioeconomic data. Using this algorithm, a zone system has been generated for the Munich metropolitan region. Only 13 iterations were needed to converge within 5% of target of 5000 delineated zones. The improved algorithm maintains the advantages of the original algorithm and adds several important improvements that are useful when creating a zone system., Open Geospatial Data, Software and Standards, 2

Despite empirical evidence, the common approaches for destination choice modeling do not usually account for an overall travel time budget. In fact, if congestion worsens workers will choose different workplaces instantaneously, a highly unrealistic representation of observed work trip destination choice. The objective of this paper is to incorporate travel time budgets as constraints for non-commute trips in the destination choice model, while the commute time will be given directly by home and workplace locations as defined in a synthetic population. Individual travel time budgets for every trip purpose were calculated using the household as analysis unit. The results indicate that travel time depends on the number of required trips by trip purpose and household sociodemographics. Increasing the number of trips for one purpose reduces the travel time allocated for the other trips, confirming the existence of an overall travel time budget. Household size is the most important sociodemographic variable, followed by the household income. Destination choice modeling with travel time budgets as constraint will add fidelity to trip-based travel demand models.

Finding the appropriate spatial resolution in modeling is a serious challenge at the beginning of every modeling project. The paper presents a methodology to adjust the spatial geography to the resolution of a network. Based on the quadtree algorithm, raster cells are generated that are dynamic in size. Smaller raster cells are used in urban areas and larger raster cells are used in low-density, rural areas. Trip tables of a travel demand model for the State of Georgia are disaggregated to this new zone system of raster cells, and assignment results validate significantly better than when using the original zone system.

Mega-regions are a new geography that may well form the “nation's operative regions when competing in the future global economy. A challenge is to determine how to foster greater efficiencies in these mega-regions by creating a stronger infrastructure and technology backbone in the Nation's surface transportation system,” according to the March 2010 FHWA Strategic Plan. To meet this challenge these regions will need analysis tools to evaluate scenarios and their regional impacts, analysis tools covering areas larger than covered by the typical Metropolitan Planning Organization (MPO) or State Department of Transportation (DOT) models. This paper describes what makes mega-regions different and identifies analytic issues mega-regions may need to address, identifies the Chesapeake Mega-region and provides a framework for analyzing issues within the Chesapeake mega-region. Finally, the framework is tested through a proof of concept scenario which assumes a sudden price rise in gasoline prices and the likely effects on travel. A brief summary of further work and additional scenarios planned is provided.

As part of the planning effort leading up to the development of a statewide Freight Plan, the Oregon Department of Transportation (ODOT) developed a statewide commodity flow forecast. The methodology used to create this Oregon Commodity Flow Forecast (Oregon CFF), aimed to address the limitations of existing forecasts – inconsistent and separate databases for different modes, lack of transparency in data and assumptions, and data gaps – in a consistent methodology based on national and local data sources, and be able to meet the tight timelines. This paper will document the work done by the consulting team and the agency to create a statewide forecast that addressed these limitations. The project team decided to build on the Federal Highway Administration (FHWA) Freight Analysis Framework (FAF2) national commodity flow forecast. The FAF2 commodity flow forecast was chosen because FAF2 is national in scope, highly regarded in terms of capturing interstate and international flows, uses a relatively recent base year (2002), and provided a quick way to complete a forecast in time for the Oregon Freight Plan work. FAF2 provides freight flows in tons or dollar value between 130 FAF2 regions encompassing the US for the year 2002 plus forecasts from 2010 to 2035 in five year increments. The desired final product for the Oregon CFF was a county-county level flow forecast for truck, rail, marine, air, and pipeline modes. In order to transform the coarse FAF2 zone flows (2 zones cover Oregon) into counties within Oregon, the data was disaggregated. Since the FAF2 dataset contains the whole United States, flows with at least one trip ends within Oregon were disaggregated from FAF2 zones to Oregon counties. Each of the freight modes was disaggregated separately. In the case of truck flows, this was done based on county employment and IMPLAN inter-industry coefficients of what commodities are made and used by each industry. For rail flows, the FAF2 flows were compared to the Surface Transportation Board‘s Rail Carload Waybill data set which contains county level detail of origin and destinations. The overall numbers were found to be comparable, so the Waybill data for 2002 was used as the base, and the FAF2 ii growth rates were applied to forecast the future years. The other modes relied on local data to allocate FAF2 flows to specific Oregon facilities (rail stations, airports, marine ports, or pipeline terminals), including US Corps of Engineers Waterborne Commerce data and the Oregon Energy Report. Zones outside of Oregon were aggregated from FAF2 zones to ―Other Domestic‖ and ―Other International‖ categories. Special consideration was made for air mail and fish commodities using the knowledge of industry experts. Using the Rail Waybill data and other sources required a conversion in commodity categories, because FAF2 uses the Standard Classification of Transported Goods (SCTG)TG and other sources used the Standard Transportation Commodity Code classification. Once the data was disaggregated to represent county-county commodity flows, the FAF2 future year forecast numbers were adjusted down to account for the economic downturn that occurred after the forecast was prepared. One of the challenges of working with the FAF2 data is the inability to adjust or quantify the FAF2 underlying economic forecasts, particularly the optimistic economic conditions and low fuel price assumptions. These poses some limitations that must be taken into account. The Oregon CFF 2002 to 2035 forecast provides a basis for understanding the primary freight movements today and in the future under existing conditions. In several instances circumstances are likely to change, and the detail and transparency provided in Oregon CFF can provide a starting point for evaluating such changes.

As public agencies strive to create more accurate travel demand and land-use models, they must also find ways to visualize the model output. The visualization of results is essential in model development to assess how the model is performing. Once a model is out of the development process and into applications, visualizations serve a different purpose. They must communicate the story that the model is telling, deftly showing how the model answers complex policy questions. The range of visualizations required to show these answers includes plots, tables, and maps. This paper will outline a visualization plan developed for the Oregon Department of Transportation Statewide Integrated Model (SWIM).

The project ILUMASS (Integrated Land-Use Modelling and Transportation System Simulation) aims at embedding a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating both changes of land use and the resulting changes in transport demand. The land-use component of ILUMASS will be based on the land-use parts of an existing urban simulation model, but is to be microscopic like the transport parts of ILUMASS. Microsimulation modules will include models of demographic development, household formation, firm lifecycles, residential and non-residential construction, labour mobility on the regional labour market and household mobility on the regional housing market. These modules will be closely linked with the models of daily activity patterns and travel and goods movements modelled in the transport parts of ILUMASS developed by other partners of the project team. The design of the land use model takes into account that the collection of individual micro data (i.e. data which because of their micro location can be associated with individual buildings or small groups of buildings) or the retrieval of individual micro data from administrative registers for planning purposes is neither possible nor, for privacy reasons, desirable. The land use model therefore works with synthetic micro data which can be retrieved from generally accessible public data. ILUMASS is a group project of institutes of the universities of Aachen, Bamberg, Dortmund, Cologne and Wuppertal under the co-ordination of the Transport Research Institute of the German Aerospace Centre (DLR). Study region for tests and first applications of the model is the urban region of Dortmund. The common database will be compiled in co-operation with the City of Dortmund. After its completion the integrated model is to be used for assessing the impacts of potential transport and land use policies for the new land use plan of the city. The paper will focus on the land-use parts of the ILUMASS model. It will present the underlying behavioural theories and how they are made operational in the model design, explain how the synthetic population is generated, show first model results and demonstrate the potential usefulness of the model for the planning process.

The objective of the project 'Sustainable Mobility in Cities' was to advance an approach for identifying policy packages for sustainable mobility. The study combined qualitative and quantitative methodological components: In the qualitative part of the analysis, market segmentation techniques were used to identify groups and locations positively or negatively affected by transport-related policy instruments. In the quantitative part of the study, a method for developing a synthetic population as the basis for a microsimulation of urban travel demand and traffic was developed. The project was a co-operation between the Department of Geography of the Hebrew University of Jerusalem and the Institute of Spatial Planning. The reports presents the results of the study., Berichte aus dem Institut für Raumplanung ; 56

Walking is a critical mode for sustainability, health, environment, urban vitality, and equity. This work advances pedestrian modeling both theoretically and practically. It collects novel longitudinal data and investigates travel behavior variability. Practically, it develops a more accurate, sensitive, transferable, and efficient pedestrian planning tool for assessing travel outcomes and evaluating policies and scenarios. Der Fußverkehr ist ein wichtiges Verkehrsmittel für Nachhaltigkeit, Gesundheit, Umwelt, städtische Vitalität und Gerechtigkeit. Diese Arbeit bringt die Modellierung für Fußgänger sowohl theoretisch als auch praktisch voran. Sie erhebt neue Längsschnittdaten und untersucht die Variabilität im Verkehrsverhalten. In der Praxis wird ein genaueres, sensitiveres, übertragbares und effizienteres Planungsmodel für Fußgänger entwickelt, mit dem die Ergebnisse der Verkehrsplanung beurteilt und Strategien und Szenarien bewertet werden können.

Contemporary traffic models use agent-based approaches that microscopically represent individuals, including their characteristics and behaviors. This work examines use cases of agent-based models with respect to traffic noise modeling with a focus on scenarios for which an individual representation of actors is necessary. In particular, interactions between land use, traffic and noise as well as equity aspects are investigated. Zeitgenössische Verkehrsmodelle nutzen agentenbasierte Ansätze, mit denen Individuen inklusive ihrer Merkmale und Verhaltensweisen mikroskopisch dargestellt werden. Diese Arbeit untersucht Anwendungsfälle agentenbasierter Modelle im Hinblick auf Verkehrslärmmodellierung mit einem Fokus auf Szenarien, für die eine individuelle Darstellung von Akteuren notwendig ist. Insbesondere werden Wechselwirkungen zwischen Flächennutzung, Verkehr und Lärm sowie Gerechtigkeitsaspekte untersucht.

Non-motorized trips are generally short trips, and in macroscopic models, many of them end up in the same transport analysis zones from which they originate. Since the spatial aggregation nature of these models makes it difficult to model intrazonal trips, the treatment of non-motorized trips in such models is limited. Non-motorized trips can however not be neglected in urban transport analyses considering the high share of walking and cycling in urban areas, and their importance for sustainable mobility. Recognizing the mitigation of the intrazonal problem as key to improving non-motorized trip modeling in macroscopic models, the research seeks to enhance the macroscopic modeling of non-motorized trips by finding a suitable method for calculating intrazonal impedances, and identifying an appropriate level of spatial resolution for analysis zones. To find a suitable method for calculating intrazonal impedances, the study compares both calculated intrazonal impedances and modeled intrazonal trips. The study considers existing methods for calculating intrazonal impedances and a new method that calculates intrazonal impedance by finding the average impedance between node pairs within a zone. The results show that whereas the proposed method provides better estimates of intrazonal impedances, better intrazonal impedance estimates do not guarantee better intrazonal trip estimates. Consequently, non-motorized trips cannot be adequately handled in macroscopic models by improving the calculation of intrazonal impedances. Efforts aimed at improving the calculation of intrazonal impedances should therefore be geared towards reducing the need to deal with intrazonal trips. In identifying an appropriate level of spatial resolution, the study seeks to minimize a cost function with respect to the number of zones and the deviations in traffic assignment results. The objective is to keep the number of zones to the minimum possible while ensuring low deviations in assignment results. Using network length per zone to define spatial resolution, the study applies the gradual rasterization process with the quadtree concept to create 24 different raster cell systems for different levels of spatial resolution. The study identifies 1,000 m network length per raster cell as an appropriate level of spatial resolution for the study area and indicates the possibility of adjusting input variables to define context-specific appropriate levels of spatial resolution. The results show that there is a limit beyond which the benefits derived by further increases in spatial resolution is not worth the costs associated with the extremely high increase in the resultant number of zones. The application of the research findings in the travel demand model of Dachau confirms that mitigating the intrazonal problem improves the modeling of non-motorized trips. The research outcome should facilitate the integration of bicycle and pedestrian travel in the models of planning agencies to enable impact assessment of actions taken to encourage non-motorized travel. This will ensure the successful development and implementation of sustainable mobility concepts. Wege mit nicht-motorisierten Verkehrsmitteln sind im Allgemeinen kurz, wodurch in makroskopischen Modellen viele dieser Wege innerhalb derselben Zone beginnen und enden. Die räumliche Aggregation dieser Modelle erschwert es, intrazonale Wege zu modellieren und daher sind die Möglichkeiten limitiert, nicht-motorisierte Wege abzubilden. Vor dem Hintergrund des hohen Anteils von Fuß und Fahrrad im städtischen Bereich sowie deren Bedeutung für nachhaltige Mobilität dürfen diese Wege jedoch nicht vernachlässigt werden. Davon ausgehend, dass die Verringerung des Problems der Abbildung intrazonaler Wege ein Schlüssel zur Verbesserung der Modellierung nicht-motorisierter Wege in makroskopischen Modellen darstellt, besteht das Ziel dieser Arbeit in der Verbesserung makroskopischer Modellierung nicht-motorisierter Wege durch Bestimmung einer geeigneten Methode zur Berechnung intrazonaler Widerstände sowie der Definition einer geeigneten räumlichen Auflösung der Zonen im Modell. Zur Bestimmung einer geeigneten Methode für die Berechnung intrazonaler Widerstände vergleicht die Studie berechnete Widerstände und modellierten intrazonalen Wegen. Dabei werden bestehende Methoden für die Berechnung intrazonaler Widerstände sowie eine neue Methode betrachtet, bei der die Widerstände durch das Berechnen von Mittelwerten zwischen Knotenpaaren innerhalb einer Zone bestimmt werden. Obwohl die vorgeschlagenen Methoden bessere Abschätzungen der intrazonalen Widerstände liefern, heisst das nicht, dass sie auch die intrazonalen Wege besser abschätzen können. Daraus lässt sich schlussfolgern dass das Problem der nicht-motorisierten Wege in makroskopischen Modellen durch die Verbesserung der Berechnung intrazonaler Widerstände nicht gelöst werden kann. Weitere Bestrebungen zur Verbesserung der Widerstandsberechnungen sollten daher eher darauf abzielen, die Notwendigkeit der Bestimmung intrazonaler Wege zu reduzieren. Zur Bestimmung einer geeigneten räumlichen Auflösung wurde eine Kostenfunktion, in Bezug auf die Anzahl der Zonen sowie die Abweichungen bei den Ergebnissen der Verkehrsumlegung minimiert. Das Ziel ist es, die Anzahl von Zonen minimal zu halten und gleichzeitig niedrige Abweichungen bei der Verkehrsumlegung zu erreichen. In der Studie werden mittels eines Gradual Rasterization Prozesses mit dem Quadtree Konzept 24 verschiedene Rasterzellensysteme für verschiedene Stufen räumlicher Auflösung erstellt. Dabei wird die Länge des Netzwerks pro Zone verwendet, um die räumliche Auflösung festzulegen. Im Ergebnis wurde dabei eine Länge von 1.000 m pro Rasterzelle wurde dabei als ein geeigneter Wert für das Untersuchungsgebiet ermittelt. Die Studie zeigt weiterhin die Möglichkeit, Eingangsvariablen anzupassen um kontextspezifisch geeignete räumliche Auflösungen zu definieren. Die Ergebnisse zeigen, dass es eine Grenze gibt, bei deren Überschreitung der Nutzen einer weiteren Erhöhung der Auflösung nicht größer wird als der Aufwand für die extrem ansteigende Anzahl von Zonen. Die Anwendung der Forschungsergebnisse im Verkehrsnachfragemodell der Stadt Dachau bestätigt, dass eine Verringerung des intrazonalen Problems die Modellierung nicht-motorisierter Wege verbessert. Das Forschungsergebnis erleichtert die Integration von Rad- und Fußverkehr in die Modelle von Planungsbehörden, um die Einflüsse von Maßnahmen zur Förderung des nicht-motorisierten Verkehrs zu bewerten. Dadurch kann die erfolgreiche Entwicklung und Umsetzung nachhaltiger Mobilitätskonzepte gewährleistet werden.