A genetic-fuzzy system modeling of trip distribution

Thesis (Doctoral)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2010Includes bibliographical references (leaves: 89-96)Text in English; Abstract: Turkish and Englishix, 141 leavesTrip distribution modelling is one of the most active parts of travel demand analysis. In recent years, use of soft computing techniques has introduced effective modelling approaches to the trip distribution problem. Fuzzy Rule-Based System (FRBS) and Genetic Fuzzy Rule-Based System (GFRBS: fuzzy system improved by a knowledge base learning process with genetic algorithms) modelling of trip distribution are two of these new approaches. However, much of the potential of these techniques has not been demonstrated so far. The present study explores the potential capabilities of these approaches in an urban trip distribution problem with some new features. For this purpose, a simple FRBS and a novel GFRBS were designed to model Istanbul intra-city passenger flows. Subsequently, their accuracy, applicability, and generalizability characteristics were evaluated against the well-known gravity and neural networks based trip distribution models. The overall results show that: i) traditional doubly constrained gravity models are still simple and efficient; ii) neural networks may not show expected performance when they are forced to satisfy production-attraction constraints; iii) simply-designed FRBSs, learning from observations and expertise, are both interpretable and efficient in forecasting trip interchanges even if the data is large and noisy; and iv) use of genetic algorithms in fuzzy rule base learning considerably increases modelling performance, although it brings additional computation costs

Recommendations to Harmonize Travel Behaviour Analysis

Among several other efforts to identify data needs and to harmonize travel surveys in Europe, this report aims to define recommendations to collect and report travel data with the identification of main data needs and gaps, and with the analysis of alternative sources of information and new data collection techniques. Based on the findings of the previous tasks and a stakeholder workshop in OPTIMISM project, and after a brief review of past studies in the same direction, this report starts from a list of variables which are needed for policy making but are unavailable/insufficient in the context of existing data collection methodologies especially with respect to NTS. The report then, explores alternative sources of information, potential use of modern data collection techniques (mainly ICT applications such as GPS and smart phone technologies) and options to merge them with NTS data. Finally, it discusses recommendations for a Europe-wide travel survey considering the current data needs for policy making in transportation. The research has been conducted under the OPTIMISM project which was received funding from the European Union's Seventh Framework Programme (FP7/2007-2013), grant agreement n° 284892. The report has been produced as the OPTIMISM project deliverable 2.3: Recommendations to Harmonize Travel Behaviour Analysis.JRC.J.1-Economics of Climate Change, Energy and Transpor

Quantifying the Effects of Sustainable Urban Mobility Plans

This technical note uses the expert scoring information available in current scientific literature in order to explore the impacts and effects that different urban measures may have in planning for sustainability on a European wide level.JRC.J.1-Economics of Climate Change, Energy and Transpor

The impact of measuring internal travel distances on selfpotentials and accessibility

Internal travel distances are fundamental in accessibility measurement, as they affect the weight of the intra-regional interactions, especially when using a gravity formulation. The contribution of the internal accessibility of each zone to its overall accessibility is known as self-potential. Several studies demonstrate its importance in accessibility analyses, especially in the most urbanized regions. It is precisely in urban regions where internal travel distances are more difficult to estimate due to congestion, which in turn may be influenced by factors such as urban density, urban morphology, network infrastructure, etc. Accessibility analyses usually use coarse estimates of internal distances, generally based on the regions' area and in some cases considering its level of urbanization. In this study we explore different forms of estimating internal travel distances in accessibility analysis and reflect on their advantages and drawbacks. One of the main difficulties that arise when measuring internal travel distances is the lack of data. However, the growing potential of ICTs in providing new sources of data can be used to improve representativeness of data. In this study we used speed profiles data from TeleAtlas/TomTom to calculate internal travel distances for European NUTS-3 regions and we compare this measure with three other metrics traditionally used in the literature. Following this exercise, we discuss the conditions under which it is advantageous to use more complex measures of internal travel distance. Finally, we test the sensitivity of potential accessibility indicators to the combined effect of different internal distance metrics and distance decay factors

The impact of measuring internal travel distances on self-potentials and accessibility

Internal travel distances are fundamental in accessibility measurement, as they affect the weight of the intra-regional interactions, especially when using a gravity formulation. The contribution of the internal accessibility of each zone to its overall accessibility is known as self-potential. Several studies demonstrate its importance in accessibility analyses, especially in the most urbanized regions. It is precisely in urban regions where internal travel distances (measured as travel length, time or cost) are more difficult to estimate due to congestion, which in turn may be influenced by factors such as urban density, urban morphology, network infrastructure, etc. Accessibility analyses usually use coarse estimates of internal distances, generally based on the regions' area and in some cases considering its level of urbanization. In this study we explore different forms of estimating internal travel distances in accessibility analysis and reflect on their advantages and drawbacks. One of the main difficulties that arise when measuring internal travel distances is the lack of data. However, the growing potential of ICTs (Information and communication technologies) in providing new sources of data can be used to improve representativeness of data. In this study we used speed profiles data from TeleAtlas/TomTom to calculate internal travel distances for European NUTS-3 regions and we compare this measure with three other metrics traditionally used in the literature. Following this exercise, we discuss the conditions under which it is advantageous to use more complex measures of internal travel distance. Finally we test the sensitivity of potential accessibility indicators to the combined effect of different internal distance metrics and distance decay factors.JRC.J.1-Economics of Climate Change, Energy and Transpor

Modelling Future Mobility - Scenario Simulation at Macro Level

The aim of the report is to simulate policy scenarios for passenger transport using Europe-wide transport models, estimate their potential impacts and demonstrate how do they differ from each other and from the reference scenario for 2030. In more detail, the main objectives of the deliverable can be given as follows: - to model future multi-modal mobility scenarios for passengers formulated within the previous tasks of the project, - to simulate impacts of identified trends and selected strategies on demand, supply and technology at macro level, - to analyse impacts of selected policies and identified trends on mobility patterns such as in travel demand and modal split, - to estimate potential impacts of selected policy measures on environmental indicators via transport emissions and vehicle fleet sizes, - to compare impacts of different scenario options in quantitative terms and provide useful insights for exploring best policy scenarios and strategies for sustainable passenger transport. The research has been conducted under the OPTIMISM project which was received funding from the European Union's Seventh Framework Programme (FP7/2007-2013), grant agreement n° 284892. The report has been produced as the OPTIMISM project deliverable 3.4: Modelling Future Mobility - Scenario Simulation at Macro Level.JRC.J.1-Economics of Climate Change, Energy and Transpor

European landscape changes between 2010 and 2050 under the EU Reference Scenario: EU Reference Scenario 2013 LUISA platform – Updated Configuration 2014

The ‘Land-Use-based Integrated Sustainability Assessment’ modelling platform (LUISA) is primarily used for the ex-ante evaluation of EC policies that have a direct or indirect territorial impact. It is based on the concept of ‘land function’ for cross-sector integration and for the representation of complex system dynamics. Beyond a traditional land use model, LUISA adopts a new approach towards activity-based modelling based upon the endogenous dynamic allocation of population, services and activities. LUISA has been applied to address the competition for land arising from the energy, transport and climate dimensions of EU policies and configured according to the EU Energy Reference scenario 2013 (updated configuration 2014) to produce high-resolution land use/cover projections up to 2050 and a related series of thematic indicators. This report describes the stocks and the main land cover/use flows (LCF) taking place in Europe in the period 2010-2050 and the processes that cause those flows, thus providing insight on how the European landscape might change if the future happens according to a reference scenario consistent with settings (economic and demographic in particular) and policies in place in 2013 (hence including in particular the 2020 renewable energy targets). Main findings: • The extent of the land for housing and leisure (urban) and industrial/commercial and services (ICS) increases, while the area of agriculture, forest and natural land decreases; • Urban and industrial land are expected to represent the highest share of net formation as % of the initial year (2010); • Energy crops appear in the model as of 2020 and are expected to reach 135,479 km2 across Europe in 2050; • Energy crops become the second most important land transformation in Europe (17%); approximately 90 % of the land consumed for energy purposes comes from land for food and feed, followed by forest and natural land; • While a large proportion of land dedicated to food and feed crops is expected to be converted into dedicated energy crops, the net land losses are very small as a results of the conversion from forest land into food and feed production; • New forest and natural land compensate in some way for quantity of losses or consumption by other uses; however the high value of the turnover indicator, reveal that those land-uses are unstable and vulnerable to the fast changes driven by economic development and climate changes, thus compromising the biodiversity and habitat conservation status; • The conversion between farming types represent 35% over the total land changes between 2010 and 2050; The results show the loss of natural and agricultural land because of ever-ongoing urbanisation and industrialization processes. The loss of natural and agricultural land for food production is even larger because of the advent of energy crops production incited by shifts in the European Energy supply system.JRC.H.8-Sustainability Assessmen

European cities: territorial analysis of characteristics and trends - An application of the LUISA Modelling Platform (EU Reference Scenario 2013 - Updated Configuration 2014)

Cities and towns are at the core of the European economy but they are often also the places where problems related to the quality of life of citizens such as unemployment, segregation and poverty are most evident. To curtail the negative impacts and foster the positive effects of ongoing urban processes in Europe, policies have to be adjusted and harmonised to accommodate future urbanization trends. Such an analysis of the evolution of European cities requires the evaluation of impacts of continent-wide drivers and, at the same time, assessment of the effect of national and local strategies. As a contribution to this analysis of the current and future evolution of European territories (countries, macro-regions, regions or urban areas), the Directorate-General Joint Research Centre (DG JRC) of the European Commission (EC) has developed the Land-Use-based Integrated Sustainability Assessment (LUISA) Modelling Platform. Based on the concept of ‘dynamic land functions’, LUISA has adopted a novel approach towards activity-based modelling and endogenous dynamic allocation of population, services and activities. This report illustrates how European cities could potentially evolve over the time period 2010-2050, according to the reference configuration of the LUISA modelling platform, on the basis of a collection of spatial indicators covering several thematic fields. These spatial indicators aim to improve our understanding of urbanization and urban development processes in Europe; explore territorial dimensions of projected demographic and economic changes, and finally examine some key challenges that urban areas are or may be exposed to. Some of the key findings of this report are given below: - The proportion of the population living in cities, towns and suburbs is higher in the EU than in the rest of the world. According to the LUISA forecasts, the urban proportion will continue to increase up to 2030; subsequently slow down, and reach a relatively steady state by 2050. - In 2010, 65% of the EU population were living in Functional Urban Areas (FUA, the city and its commuting zone). This figure is expected to reach 70% by 2050. The total EU-28 population is expected to grow by 4.6%. Most of this population growth will occur particularly in FUA which will grow by an average 14%. - As of 2010, the amount of artificial areas per inhabitant in the EU-28 was estimated as 498 m2: it becomes 539 m2 in 2050 with an 8% increase. Although there is not a unique spatial pattern, land take tends to start peak at 5 km distance from the city centre. This is due to the fact that land is often less available for development within city centres and that the majority of land take therefore will occur firstly in the suburbs and then in rural areas. - By 2050, potential accessibility – as measure of economic opportunities - will be higher in the urban areas of north-western Europe, while it will not improve in lagging European regions. Urban form has a considerable impact on average travelled distances and thus potentially on the energy dependence of transport. - Green infrastructure is mainly located at the periphery of urban areas. Its share per person is generally low or very low in most of the European cities, with few exceptions. Green infrastructure per capita in FUA shows a general trend towards a decrease across the EU-28 (by approximately 13%) between 2010 and 2050. - Larger cities tend to have higher average flood risk, especially due to the higher sensitivity in terms of potential human and physical losses. The analysis herein presented is part of a wider initiative of DG JRC and DG REGIO aiming to improve the management of knowledge and sharing of information related to territorial policies, such as those concerning urban development. In this framework, the work will be further developed, covering the following main elements: - Development of the European Urban Data Platform, providing a single access point for data and indicators on the status and trends of European urban areas; - Updates of the LUISA configuration, to account for new socio-economic projections; - Support to the development of the EU Urban Agenda and related initiatives; - Provision of evidence-based support for the evaluation of territorial policies in particular to proof the role of cities in the implementation of EU priorities.JRC.H.8-Sustainability Assessmen

European Territorial Trends - Facts and Prospects for Cities and Regions Ed. 2017

This report analyses a set of territorial trends at continental and sub-national scale, looking at patterns and determinants of regional growth, while considering pan-European and national characteristics. Past and prospective demographic and economic trends are analysed to provide a picture of ‘what, where, when and how’ things happen in European cities and regions. Specific emphasis is placed on urban areas since acknowledged sources of both opportunities and challenges. The indicators used in the analysis herein presented are freely and openly accessible in the Territorial Dashboard of the Knowledge Centre for Territorial Policies at: http://urban.jrc.ec.europa.eu/t-board/index.htmlJRC.B.3-Territorial Developmen

The Future of Cities

This report is an initiative of the Joint Research Centre (JRC), the science and knowledge service of the European Commission (EC), and supported by the Commission's Directorate-General for Regional and Urban Policy (DG REGIO). It highlights drivers shaping the urban future, identifying both the key challenges cities will have to address and the strengths they can capitalise on to proactively build their desired futures. The main aim of this report is to raise open questions and steer discussions on what the future of cities can, and should be, both within the science and policymaker communities. While addressing mainly European cities, examples from other world regions are also given since many challenges and solutions have a global relevance. The report is particularly novel in two ways. First, it was developed in an inclusive manner – close collaboration with the EC’s Community of Practice on Cities (CoP-CITIES) provided insights from the broader research community and city networks, including individual municipalities, as well as Commission services and international organisations. It was also extensively reviewed by an Editorial Board. Secondly, the report is supported by an online ‘living’ platform which will host future updates, including additional analyses, discussions, case studies, comments and interactive maps that go beyond the scope of the current version of the report. Steered by the JRC, the platform will offer a permanent virtual space to the research, practice and policymaking community for sharing and accumulating knowledge on the future of cities. This report is produced in the framework of the EC Knowledge Centre for Territorial Policies and is part of a wider series of flagship Science for Policy reports by the JRC, investigating future perspectives concerning Artificial Intelligence, the Future of Road Transport, Resilience, Cybersecurity and Fairness Interactive online platform : https://urban.jrc.ec.europa.eu/thefutureofcitiesJRC.B.3-Territorial Developmen