Suchergebnisse

Am Anfang des 21. Jahrhunderts sind in vielen Ländern starke Veränderungen in Warenflüssen und im Mobilitätsverhalten von Personen spürbar. Auf der einen Seite entwickelt sich eine globalisierte Welt, in der Arbeitsteilung und die Erschließung neuer Märkte den Warentransport massiv ansteigen lassen. Auf der anderen Seite verändert sich das Mobilitätsverhalten der Menschen: mehr Freizeitverkehr in den Industrieländern, mehr Nachfrage nach motorisiertem Verkehr in Entwicklungs- und Schwellenländern. Es wird erwartet, dass diese Entwicklung zu einem Anstieg der verkehrsbezogenen negativen Externalitäten führen wird, wie z.B. Stauerscheinungen, lokale Luftverschmutzung und Klimawandel. Aus diesem Grund sehen sich alle Nationen großen Herausvorderungen im Bereich der Verkehrs- und Infrastrukturplanung gegenüber. Es wird nötig sein – neben technischen und regulativen Interventionen – weitere politische Maßnahmen zu entwickeln, welche auf Verhaltensänderungen der Bürger abzielen. Vor diesem Hintergrund beschäftigt sich diese Arbeit mit möglichen Verbesserungen einer angewandten Nutzen-Kosten-Analyse (NKA), die sich durch die Berücksichtigung von heterogenen Nutzerpräferenzen und Nutzerattributen im Verhaltensmodell einer agentenbasierten Verkehrssimulation ergeben können. Die Arbeit beschäftigt sich mit der Bewertung positiver und negativer Wirkungen auf die Gesellschaft, die sich aufgrund von politischen Maßnahmen ergeben könnten. Dafür werden mehrere hypothetische Maßnahmen in verschiedenen realen Szenarien eingeführt und Änderungen im Mobilitätsverhalten, Änderungen in Abgasemissionen und Änderungen im individuellen Wohlfahrtsniveau werden berechnet. Insgesamt werden drei Arbeitspakete bearbeitet: 1. Analyse von Maßnahmen, welche die gesamtgesellschaftliche Wohlfahrt steigern, in Bezug auf Akzeptanzproblemene. 2. Entwicklung eines Modells zur Vorhersage von aggregierten und räumlich disaggregierten Änderungen fahrzeugspezifischer Warm- und Kaltstartemissionen. 3. Internalisierung von fahrzeugspezifischen, zeitabhängigen Emissionskosten mit Hilfe einer optimalen Luftschadstoffmaut. Das erste Arbeitspaket geht davon aus, dass in der Praxis einzelne Kennzahlen (wie z.B. das Nutzen-Kosten-Verhältnis) einen starken Einfluss auf die Bewertung von Verkehrsmaßnahmen haben; diese Zahl vernachlässigt allerdings Verteilungseffekte, die auf räumlich differenzierter oder personenspezifischer Ebene implizit entstehen. Um diesem Effekt entgegenzuwirken, werden empirisch bestimmte, heterogene Kostenpräferenzen der Nutzer in das Verhaltensmodell der Verkehrssimulation eingeführt. Zunächst verbessert dies die Genauigkeit und die Vorhersagekraft des Modells. Außerdem zeigt sich, dass die sich ergebenden individuellen Nutzenveränderungen ein robuster Indikator für die Identifizierung von Gewinnern und Verlierern einer Maßnahme darstellt. In der ökonomischen Analyse werden dann zwei Aggregations- und Monetarisierungsmöglichkeiten durchgeführt und verglichen: der Ansatz über Zeitäquivalente und der Ansatz über Einkommensäquivalente. Für den Ansatz über Einkommensäquivalente deuten die Ergebnisse darauf hin, dass sowohl Maut als auch nicht-monetäre Maßnahmen, die eine Verkürzung der Reisezeiten zum Ziel haben, eine regressive Wirkung auf die Wohlfahrtsverteilung in der Gesellschaft haben können. Eine progressive (Einkommens)steuer zur Finanzierung der Maßnahme könnte aus diesem Grund u.U. nicht umverteilend wirken, da sie lediglich die individuellen Zahlungsbereitschaften zur Verbesserung des Services reflektiert. Zusammenfassend kann gesagt werden, dass der Vergleich der beiden Ansätze es ermöglicht, Gründe für öffentlichen Widerstand zu identifizieren, der sich gegen Projekte wendet, die aus Sicht des üblichen NKA-Ansatzes ökonomisch sinnvoll erscheinen. Das zweite Arbeitspaket zeigt die technische Möglichkeit, heterogene Nutzerattribute – hier Fahrzeugattribute – in eine agentenbasierte Verkehrssimulation einzubeziehen. Ein neuartiges Emissionsberechnungstool (EMT) wird entwickelt, das detaillierte Luftschadstoff- und Klimawandelexternalitäten berücksichtigt. Hochdifferenzierte Warm- und Kaltstartemissionen, die von Fahrzeugtyp, Verkehrszustand und Aktivitätendauer abhängen, werden im Rahmen mehrerer hypothetischer Erhöhungen der distanzabhängigen Autonutzerkosten berechnet. Es zeigt sich, dass die Preiselastizitäten der Emissionen höher sind als die der Verkehrsnachfrage. Dies bedeutet, dass das Modell in der Lage ist die positiven Effekte von Stauauflösung auf das Emissionsniveau zu beschreiben. Eine räumlich hoch aufgelöste Analyse zeigt allerdings, dass die Emissionen pro Fahrzeugkilometer auf Hauptverkehrsstraßen und tangentialen Autobahnen ansteigen. Dies verringert die Effizienz des Systems in Bezug auf die Emissionen pro Fahrzeugkilometer. Auf urbanen Straßen sinken diese spezifischen Emissionen hingegen. Dies erhöht die Effizienz des Systems diesbezüglich. Obwohl letzterer Effekt ersteren dominiert zeigt dies, dass das EMT den Effekt einer emissionsoptimalen Geschwindigkeit um 60 km/h widerspiegelt, welcher auch in Realität auftritt. Das letzte Arbeitspaket zielt darauf ab die Entscheidungsfindung innerhalb einer NKA zu verbessern indem eine optimale Luftschadstoff-Maut berechnet wird. Dazu wird die Ausgabe des EMT verwendet, welches im zweiten Arbeitspaket entwickelt wurde. Es wird ein neuartiger Ansatz vorge- stellt, mit dem eine fahrzeugspezifische, zeitabhängige Luftschadstoff-Maut berechnet werden kann. Ein Vergleich dieser Internalisierungsstrategie zu den Wirkungen einer regulativen Maßnahme – eine Reduktion der Höchstgeschwindigkeit in der Innenstadt auf 30 km/h – zeigt, dass letztere Maßnahme deutlich weniger zur Reduzierung der Gesamtemissionen beiträgt. Die regulative Maßnahme führt sogar zu höheren Ineffizienzen als der Bezugsfall: dies impliziert generalisierte Preise oberhalb des ökonomischen Optimums für Stadtbewohner und generalisierte Preise unterhalb des ökonomischen Optimums für Pendler und Güterverkehr. Die Resultate zeigen auch, dass die Luftschadstoff-Maut auch Zeitverluste reduziert und somit implizit eine Staubepreisung darstellt. Auch wenn eine optimale Maut tendenziell eher ein theoretisches Konstrukt ist, kann gezeigt werden, dass der verwendete Ansatz dafür geeignet ist, Verkehrsmaßnahmen zu bewerten, die auf eine Reduktion von Luftschadstoffemissionen in Metropolregionen abzielen. Zusammenfassend kann gesagt werden, dass diese Arbeit mehrere strukturelle Probleme im Bereich der aktuellen quantitativen Bewertung von Verkehrsmaßnahmen herausarbeitet. Anhand verschiedener Fallbeispiele wird gezeigt, wie durch Fortschritte in agentenbasierten Verkehrssimulationen wertvolle zusätzliche Informationen sowohl für Entscheidungsträger als auch für öffentliche Beteiligungsverfahren bereitgestellt werden können. Die Einführung heterogener Nutzerpräferenzen und Nutzerattribute beschreibt zwar vermutlich reales Verhalten präziser; abschließend kommt die Arbeit allerdings zu dem Schluss, dass die Frage wie Gewinne und Verluste verschiedener Individuen gegeneinander aufgewogen werden normativ festgelegt werden muss, möglichst im Rahmen gesellschaftspolitischer Diskussionen. ; At the beginning of the 21st century, many countries are experiencing major changes in commodity flows and in people's mobility. On the one hand, a globalized world is evolving where division of labor and new markets lead to a strong increase in freight transport. On the other hand, people's mobility patterns are shifting: more leisure related travel in the industrialized countries, more demand for motorized transport in the developing countries. This is expected to lead to an increase of transport-related negative externalities such as congestion, local pollution, and climate change. For this reason, all nations face major challenges in the field of transport infrastructure and policy planning: Political interventions need to be developed which—in addition to technological and regulatory measures—aim for behavioral changes of people. Against this background, the thesis concerns possible improvements in applied Benefit-Cost Analysis (BCA) that can be obtained when introducing heterogeneous user preferences and user attributes into the behavioral model of an agent-based transport simulation. The thesis focuses on the valuation of positive and negative effects for society that might be caused by policy interventions. Several hypothetic policies are introduced in different real-world scenarios, and changes in mobility patterns, changes in exhaust emissions, and changes in well-being are calculated for every individual of the population. In total, three work packages are treated: 1. Analysis of public acceptance problems of transport policies that increase overall welfare for society. 2. Development of a model to forecast the aggregated and spatially disaggregated changes of vehicle-specific warm and cold start emissions. 3. Internalization of vehicle-specific, time-dependent emission costs by a first-best air pollution toll. The first work package claims that, in practice, a single figure—such as Benefit-Cost Ratio (BCR)—has a strong impact when deciding about transport policies; however, this figure omits implicit distributional effects that emerge on geo-spatial or inter-personal levels. To correct for this, empirically determined, heterogeneous costs preferences of users are introduced into the behavioral model of the transport simulation. This is found to improve the accuracy and forecast ability of the model. Furthermore, the resulting individual utility differences are found to be robust figures for the identification of winners and losers of the policy. For economic analysis, two aggregation and monetization procedures are performed and compared: the time equivalent and the income equivalent approach. Following the income equivalent approach, the results indicate that road user pricing schemes, but also non-monetary policies that aim at shortening travel times, can have regressive impacts on the welfare distribution of society. A progressive (income) tax to finance the measure might therefore not be re-distributive, but might only reflect the individual willingness-to-pay for improving the corresponding services. Finally, the comparison of the two approaches proves to help identifying possible reasons for public refusal of transport policies that are—according to standard BCA—economically beneficial. The second work package proves the technical feasibility of including heterogeneous user attributes—namely vehicle attributes—into the agent-based transport simulation. A novel Emission Modeling Tool (EMT) is developed to account for detailed air pollution and climate change externalities. Highly differentiated warm and cold start emissions that depend on vehicle types, traffic states, and activity durations are calculated for several hypothetical price changes in car user costs. Aggregated price elasticities of emissions are found to be higher than those of demand. That is, the model is found to capture the positive effects of congestion relief on emission levels. However, a spatially disaggregated analysis shows for high-speed arterials and tangential motorways that average emissions per vehicle kilometer rise. This decreases the efficiency of the system in terms of emissions per vehicle kilometer. In contrast, average emissions per vehicle kilometer drop in urban areas. This increases the efficiency of the system in terms of emissions per vehicle kilometer. Even though the latter effect is dominating the first, the results indicate that the EMT captures the effect of an emission optimal speed around 60 km/h which is also found in reality. The last work package aims at improving decision support in the BCA framework by calculating first-best air pollution tolls. It builds up on the output of the EMT developed in work package two. A novel approach is presented to calculate vehicle-specific, time-dependent air pollution tolls. Comparing this internalization policy to a regulatory measure—a speed limitation to 30 km/h in the inner city—shows that the latter policy is considerably less successful in terms of total emission reduction. It even yields higher inefficiencies than a 'do-nothing' strategy. That means generalized prices beyond the economic optimum for urban travelers and generalized prices below the economic optimum for commuters and freight traffic. Importantly, it is found that the air pollution toll implicitly reduces congestion and therefore works as a congestion pricing scheme. Even though the first-best toll is a rather theoretical concept, the approach proves to help designing transport policies that aim at reducing air pollution in metropolitan areas. In summary, this thesis highlights several structural issues in the context of current quantitative economic policy appraisal. By means of several Case Studies, it shows how advances in multi-agent transport models could provide valuable additional information for decision makers as well as for public participation processes. The introduction of heterogeneous user preferences and user attributes may capture people's behavior more accurately; however, the thesis concludes that the question on how to weigh gains and losses of different individuals against each other remains a normative one, which has to be solved in socio-political discussions.

From transport economic literature it is known that pricing (environmental) externalities can improve the efficiency of a transport system. However, in real-world politics, policy setting often follows so-called `backcasting' approaches where predefined goals are set, and policy measures are implemented to reach those goals. This study presents, for a specific case study, an parametric approach to identify the gap between toll levels derived from environmental damage cost internalization and toll levels from the goal to reduce global greenhouse gas emissions in the transport sector until 2020 by 20% (avoidance cost approach). For this purpose, the damage costs internalization is applied to a real-world scenario of Munich metropolitan area. The results indicate that the desired reduction in CO2 emissions is not reached. This parametric internalization approach with damage cost estimates from the literature yields toll levels that are by a factor of 5 too low in order to reach the predefined goal. When aiming at overall emission cost reductions by 20%, the damage cost estimates are even by a factor of 10 too low. Furthermore, it is shown that the major contribution to the overall emission reduction stems from behavioral changes of (reverse) commuters rather than from urban travelers; under some circumstances, the latter even increase their CO2 emission levels. Finally, the study indicates that there might be conicting trends for different types of pollutants, i.e. pricing emissions does not necessarily result in a reduction of all pollutant types.

From the transport economic literature, it is known that optimal pricing of (environmental) externalities improves the urban system. In contrast to theory-based optimal pricing strategies, real-world policy setting often follows so-called "backcasting" approaches where certain targets are set, and policy measures are implemented in order to reach those targets. An example for the latter approach is the EU goal to reduce global greenhouse gas emissions in the transport sector by 20% until 2020 with respect to 1990 levels. This article aims to (i) compare optimal pricing and backcasting approaches for a specific case study in a simulation environment by identifying the contribution of each approach in EU's 2020 emission reduction target, and (ii) to determine the costs required to reach the desired targets. For this purpose, an optimal emission pricing strategy is applied to a real-world scenario of the Munich metropolitan area in Germany. The highly differentiated tolls relate to individual exhaust emissions, i.e. they are calculated using damage cost estimates from the literature and vary over time of day, with traffic situation, and with vehicle type. The results indicate that the desired reduction in CO2 emissions is not reached for optimal pricing approach, and that the initial damage costs estimates need to be multiplied by a factor of 5 in order to reach the target, yielding a price of 350 EUR/ton CO2. When aiming at a decrease of the overall emission costs by 20% (CO2 and local pollutants), the initial cost estimates need to be multiplied by a factor of 10. Furthermore, it is shown that the major contribution to the overall emission reduction stems from behavioral changes of commuters and reverse commuters rather than from urban travelers; under some circumstances, urban travelers even increase their CO2 emission levels. Hence, the study rises awareness that conflicting trends for different types of pollutants and different types of individuals are very likely: an increase in non-methane hydrocarbon levels for urban travelers and freight depicts that pricing emissions does not necessarily result in a reduction of all pollutants or of the emissions levels of all travelers. It is shown how agent-based simulations can be used to provide valuable insights and decision support in such possibly counter-intuitive situations.

The German evaluation procedure for the Federal Transport Infrastructure Plan ('Bun-desverkehrswegeplan') is a large-scale and comprehensive modeling, simulation, and eval-uation effort. An important component of the evaluation procedure is a cost-benefit analy-sis, based on the concept of resource consumption. This concept means that new transport infrastructure causes changes in the consumption of time, money, safety, environment, etc. In this paper, we show that — assuming elastic demand for the facility under consideration — the current approach is not in line with basic consumer theory. This stems from incon-sistencies between the behavioral model and the evaluation method: ignoring unobserved attributes of the different transport modes in the evaluation can lead to quite different eco-nomic gains than when these attributes are considered. Current practice in other EU coun-tries avoids this problem typically by applying the so-called rule-of-half, or by directly deriving the logsum term from the underlying logit model. However, a change in the Ger-man assessment procedure towards one of these best-practice approaches for the upcoming Federal Transport Infrastructure Plan in 2015 seems politically not feasible. We therefore propose an easily applicable procedure to include the logic of the rule-of-half into the exist-ing evaluation approach. We show that the resulting calculation yields the same result as the rule-of-half while maintaining the rest of the former evaluation method. Finally, we discuss how another German assessment scheme for urban public transit projects, which is currently under revision, fits into the proposed procedure. ; BMVBS, 960974/2011, Review and further development of the assessment methodology with a focus on the benefits components of the benefit-cost-analysis of the German national transport assessment exercise ; DFG, 92485222, Detaillierte Evaluation verkehrlicher Maßnahmen mit Hilfe von Mikrosimulation

Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into consideration. This leads to the need for transport planning tools that provide additional information for politicians and decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation procedure. ; BMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacities

In democratically organized societies, the implementation of measures with regressive effects on welfare distribution tends to be complicated because of low public acceptance. The microscopic multiagent simulation approach presented in this paper can help to design better solutions in such situations. Income can be included in utility calculations for a better understanding of problems linked to acceptability. This paper shows how the approach can be used in policy evaluation when income is included in user preferences. With the MATSim framework, the implementation is tested in a simple scenario. Furthermore the approach works in a large-scale, real-world example. On the basis of a hypothetical price and speed increase of public transit, effects on the welfare distribution of the population are discussed. This approach, in contrast with applied economic policy analysis, allows choice modeling and economic evaluation to be realized consistently. ; BMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacities

Our chapter starts from the assumption that car user costs are about to increase in the forthcoming decades. This is likely to have impacts on aggregated air pollutant emissions and on the spatial distribution of emissions. The concentration of some air pollutants still exceeds the limiting values prescribed by the European Union, especially in urban areas. Thus, the main focus of this chapter is the question whether a decrease in car travel demand due to higher user costs would result in an overproportional reduction of air pollutant emissions. When it comes to the discussion of cost-related transport policies, large-scale transport models are needed. However, for the analysis of air pollutant emissions, a detailed investigation of the micro level is also necessary. In order to combine both objectives, we use a multi-agent transport model for our simulations. The multi-agent transport simulation MATSim1 is able to simulate large-scale scenarios. It is also particularly suitable for calculating air pollutant emissions on a detailed level as complete daily plans are modeled and the traveler's identity is kept throughout the simulation process. For illustration purposes of the impacts on air pollutant emissions, nitrogen dioxide (NO2) is chosen. Furthermore, the transport sector is the main source of NO2 emissions and NO2 concentration limits are still often exceeded.