The ongoing urbanization process all around the globe is likely to increase transport-related negative externalities e.g., congestion, air pollution, climate change etc. The situation is severe in rapidly expanding cities where the demand for motorized transport is increasing. This has increased the pressure on the policy makers to devise policies to tackle the problem. Derived from the urbanization process, this thesis considers following objectives. 1. Investigation of the policy measures in a simulation framework a) to abate the transport negative externalities while considering the inter-relationship between different externalities and b) to achieve the politically motivated goals. 2. Development of a computationally efficient model to simulated heterogeneous traffic conditions. With the first objectives, the idea is to investigate the policy measures in the context of industrialized nations; this is addressed in the first part of the thesis. In a simulation environment, marginal social cost pricing allows to correct for the inefficiencies due to exclusion of external costs from behavioral decision making process and to derive real-world policy recommendations. The first part investigates and compares the effect of congestion pricing on emissions levels and the effect of emission pricing on congestion levels while considering heterogeneity in the individual attributes and choice behavior. Derived from the inter-relationship between the two externalities, a joint internalization of vehicular congestion and emissions is proposed. It is applied to a real-world scenario of the Munich metropolitan area in Germany. It is found that the joint internalization moves the car transport system towards the optimum, measured by a strong decrease of congestion and emission costs. In this context, it has been shown for analytical models considering more than one externality, that the correlation between the externalities needs to be taken into account. Typically, in order to avoid overpricing, this is performed by introducing correction factors which capture the correlation effect. However, the correlation structure between, say, emission and congestion externalities changes for every congested facility over time of day. Additionally, the possible efficiency gains highly depend on the implicit price elasticity of demand, which again, depends on the availability of substitutes to car travel. For the Munich case study, it is shown that the iterative calculation of prices based on cost estimates from the literature allows to identify the amplitude of the correlation between the two externalities under consideration. Further, at the disaggregated level, the results show that pricing emissions moves individuals to shorter distance routes, whereas pricing congestion pushes towards longer distance routes. That is, despite the correlation between the two externalities, isolated pricing strategies influence route choice behavior by tendency into opposite directions. 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. The first part also presents an parametric approach to identify the gap between toll levels derived from environmental damage cost internalization and toll levels to achieve the political goal of 20% reduction in GHG emissions of transport sector until 2020 with respect to 1990 levels. For this purpose, the damage costs internalization is applied to the scenario of Munich metropolitan area again and shown that the desired reduction in CO2 emissions is not reached. Further application of the 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 emission costs reductions of 20%, the damage cost estimates are even by a factor of 10 too low. 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. An economic assessment indicates that a toll equivalent to 5 times of the toll from the damage cost internalization approach increases the system welfare 6 times. The second part treats the second objective mainly in the context of the industrializing nations where mixed traffic conditions prevail. In such conditions, it becomes necessary to develop a heterogeneous traffic flow model to include all vehicle classes while keeping the model equally computationally efficient. In this direction, the second part proposes a fast Spatial Queue Model (SQM) to produce realistic flow dynamics by introducing backward traveling holes for mixed traffic conditions. In the proposed approach, the space freed by a leaving vehicle on the downstream end of the link is not available immediately to the following vehicle, rather depends on the speed of backward traveling holes. This results in triangular Fundamental Diagrams (FDs) for traffic flow such that the slope of the left branch is approximately equal to the minimum of the vehicle speed and link speed whereas the slope of the right branch is approximately equal to the speed of the backward traveling holes. With the help of FDs from the simulation of several vehicle classes, it is demonstrated that as the maximum speed of the vehicle class decreases, the density at which the maximum flow is achieved, increases and the maximum flow decreases. In a similar direction, the second part also introduces the seepage link dynamics to the SQM. The seepage is predominately common on the urban streets of most of the industrializing nations. In this model, due to higher maneuverability and smaller size, smaller vehicles (e.g., bicycle, motorbike) move continuously across the gaps between the stationary or almost stationary vehicles and come in front of the queue to leave prior to other queued vehicles. The FDs from simulation of equal modal split of car and bicycle show that the flow characteristics of bicycle is marginally affected by the presence of cars but on the contrary, the flow characteristics of the car is significantly affected by the presence of bicycles. Further, it has been shown that in a traffic stream, seepage is more effective for faster seep mode (e.g., motorbike) than slower seep mode (e.g., bicycle). Finally, in the second part, a comparison of the computational performances from the simulations using various traffic and link dynamics of the queue model is presented. An additional data structure to maintain the backward traveling holes, increases the average simulation time marginally for all three sample sizes (1%, 10%, 100%). However, the look up for seep mode on every link of the network is appeared to be resource intensive with respect to the other link dynamics of the queue model. The rate of increase in the average simulation time using the seepage link dynamics for different sample sizes is significantly higher than the rate of increase in the average simulation time of other link dynamics of the queue model. The third part integrates the two objectives and presents a real-world scenario of Patna, India with a goal of reduction in emissions externality towards sustainable transport. This part exhibits the steps for demand generation and calibration of the scenario. The urban demand is generated using the trip diaries whereas the external demand is generated using hourly trip counts. For the latter, Cadyts is extended to mixed traffic conditions. To include the diverse income effects in the behavioral decision making process of the individual, the individual income is included in the scoring function. The scenario is calibrated to evaluate the Alternative (mode) specific constants (ASCs) for different modes. The calibrated scenario is used for policy testing. Based on the traffic characteristics and composition, a bicycle superhighway is proposed along the existing railway line. An iterative process is proposed to identify the optimum locations of the connectors between bicycle superhighway and existing network. A whatif policy measure is considered in which motorbike is also allowed on the bicycle superhighway. Both policy measures increase the share of the bicycle significantly. To estimate the emissions for the two policy measures, the Emission Modeling Tool (EMT) is extended to mixed traffic conditions. It is shown that if only bicycle is allowed on the bicycle superhighway, significant reduction in emissions are observed in the inner city. However, as soon as the motorbike is also allowed on it, significant increase in the emissions are observed along the bicycle superhighway in the inner city of Patna which emphasizes the need of enforcements to stop motorbikes on the bicycle superhighway. With this, the third part demonstrates that significant reduction in emissions can be obtained in the situations where a pricing measure is difficult to implement. To summarize, this thesis focuses on the evaluation of policy measures in a simulation framework to extract the valuable information for the policy makers to tackle the problem of negative transport externality in the industrialized nations as well as industrializing nations. For the latter, this thesis also extends a computationally efficient traffic flow model to simulate the heterogeneous traffic conditions. Finally, with several case studies, the thesis shows the scope of devising policy recommendations based on the scenario specifications.


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    Title :

    Mitigating negative transport externalities in industrialized and industrializing countries


    Additional title:

    Minderung von negativen externen Effekten des Verkehrs in Industrie- und Entwicklungsländern


    Contributors:

    Publication date :

    2017



    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    380