7,037 research outputs found

    Human behavior as origin of traffic phases

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    It is shown that the desire for smooth and comfortable driving is directly responsible for the occurrence of complex spatio-temporal structures (``synchronized traffic'') in highway traffic. This desire goes beyond the avoidance of accidents which so far has been the main focus of microscopic modeling and which is mainly responsible for the other two phases observed empirically, free flow and wide moving jams. These features have been incorporated into a microscopic model based on stochastic cellular automata and the results of computer simulations are compared with empirical data. The simple structure of the model allows for very fast implementations of realistic networks. The level of agreement with the empirical findings opens new perspectives for reliable traffic forecasts.Comment: 4 pages, 4 figures, colour figures with reduced resolutio

    Decomposing The Conditional Variance of Cross-Country Output

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    A well established fact in the growth empirics literature is the increasing variation in output per capita across countries. This phenomena however does not adequately describe changes in the distribution of output since it does not account for changes in the covariates which undoubtedly in influence per capita output levels. We propose a robust, nonparametric decomposition of the conditional variation of per capita output and find that OECD countries have experienced diminishing conditional variation while other regions have experienced increasing conditional variation. Our decomposition suggests that most of these changes in the conditional variance of output is due to unobserved factors not accounted for by the traditional growth determinants. In addition to this we show as these factors played very different roles over time and across regions.Generalized Kernel, Nonparametric, Conditional Variation

    The automotive lead Kuznets curve: an analysis of the theory and empirics

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    Este artĂ­culo analiza y critica a Hilton and Levinson (1998), al mostrar que aunque los autores hacen un estudio interesante, los fundamentos teĂłricos en los que se basa su anĂĄlisis son restrictivos. Por ejemplo, el efecto de composiciĂłn que proponen no permite la existencia de economĂ­as de escala contaminantes, y la teorĂ­a del efecto escala no consiente cambios en la tecnologĂ­a. Finalmente, se muestra que el modelo empĂ­rico planteado puede estar arrojando resultados espĂșreos debido a la presencia de raĂ­ces unitarias. Sus resultados tambiĂ©n podrĂ­an ser incorrectos debido a la falta de variables regresoras que la literatura acadĂ©mica ha mostrado explican el nivel de emisiones contaminantes en una economĂ­a. Adicionalmente, los autores no verifican su teorĂ­a con el modelo empĂ­rico presentado. En consecuencia, se proponen algunas sugerencias y futuros temas de investigaciĂłn que podrĂ­an validar sus resultados y los de este tipo de estudios.EconomĂ­a ambiental, curva medio ambiental de Kuznets, contaminaciĂłn,crecimiento econĂłmico, regresiĂłn espĂșrea

    Regime-Shifts & Post-Float Inflation Dynamics In Australia

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    Australia’s inflation rate and inflation uncertainty during the post-float era 1983Q3-2006Q4 have acted as important barometers of Australia’s macroeconomic performance. The conceptualisation and measurement of the nexus between inflation and inflation uncertainty is subject to complex dynamics. We use Markov regime switching heteroscedasticity (MRSH) model to capture long-run stochastic trend and short-run noisy components. This allows us to conclude that in post-float Australia the results deviate significantly from the mainstream Friedman paradigm on inflation and its uncertainty. We also critically review the plausibility of rival paradigm explaining this paradoxical behaviour. The regime shifts detected in the inflation dynamics appear to be linked to the macroeconomic policies pursued to achieve external and internal balance as implied by Keynesian Mundell-Fleming model.

    Convergence in the United States: a tale of migration and urbanization

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    We use non-parametric distribution dynamics techniques to reassess the convergence of per capita personal income (PCPI) across U.S. states and across metropolitan and nonmetropolitan portions of states for the period 1969-2005. The long-run distribution of PCPI is bimodal for both states and metro/nonmetro portions. Further- more, the high income mode of the distribution across metro and nonmetro portions corresponds to the single mode of the long-run distribution across metro portions only. These results (polarization or club-convergence) are reversed when weighting by population. The long run distributions across people are consistent with convergence. Migration and urbanization are the forces behind convergence.Migration, Internal ; Income distribution

    EMPIRICS OF THE METROPOLITAN PRODUCTIVITY PATTERNS IN EUROPE

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    This paper focuses on the main European metropolitan areas and builds empirics on their evolution over the process of economic integration these last twenty years. These metropolitan areas are acknowledged to be the main engines of economic development in Europe, and to concentrate larger and larger shares of population, activities, R&D resources
 Different theoretical frameworks have grounded these cumulative dynamics. Recently, regional and development policies have also based their action on these areas, through the concept of polycentricity for instance. The paper rests thus on a database of the forty main European cities over the period 1975-2000, disaggregated in twenty sectors of activity. First of all, the paper analyses the processes of convergence in terms of productivity or sectoral similarities at work between the different metropolitan areas as well as the evolution of their specialization in terms of value added or employment. An analytical framework is outlined thereafter, based on the rates of growth of productivity and employment, which allows us to define a dynamic view of this convergence process, and to map the dynamic comparative advantages of sectors in our metropolitan areas. In addition to the in-depth analysis of the cities, the results of these different steps show that the metropolitan areas are the main vectors of the process of European integration; a standard model of the metropolitan area seems to emerge as a result of this process.METROPOLITAN AREAS, EUROPEAN INTEGRATION, URBAN GROWTH DYNAMICS, CONVERGENCE, SPECIALIZATION

    Assessment of traffic impact on future cooperative driving systems: challenges and considerations

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    Connect & Drive is a start-up project to develop a cooperative driving system and improve the traffic performance on Dutch highways. It consists of two interactive subsystems: cooperative adaptive cruise control (CACC) and connected cruise control (CCC). To assess the traffic performance, a traffic simulation model will be established for large-scale evaluation and providing feedbacks to system designs. This paper studies the factors determining the traffic performance and discusses challenges and difficulties to establish such a traffic simulation model

    Offline reconstruction of missing vehicle trajectory data from 3D LIDAR

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    LIDAR has become an important part of many autonomous vehicles with its advantages on distance measurement and obstacle detection. LIDAR produces point clouds which have important information about surrounding environment. In this paper, we collected trajectory data on a two lane urban road using a Velodyne VLP-16 Lidar. Due to dynamic nature of data collection and limited range of the sensor, some of these trajectories have missing points or gaps. In this paper, we propose a novel method for recovery of missing vehicle trajectory data points using microscopic traffic flow models. While short gaps (less than 5 seconds) can be recovered with simple linear regression, and longer gaps are recovered with the proposed method that makes use of car following models calibrated by assigning weights to known points based on proximity to the gaps. Newell's, Pipes, IDM and Gipps' car following models are calibrated and tested with the ground truth trajectory data from LIDAR and NGSIM I-80 dataset. Gipps' calibrated model yielded the best result
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