22 resultados para Toll roads.


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In some countries, such as Spain, it is very common that in the same corridor there are two roads with the same origin and destination but with some differences. The most important contrast is that one is a toll highway which offers a better quality than the parallel road in exchange of a price. The users decide if the price of the toll is worth to pay for the advantages offered. This problem is known as the untolled alternative and it has been largely studied in the academic literature, particularly related to economic efficiency and the optimal welfare toll. However, there is a gap in the literature academic regarding how it affects income distribution to the optimal toll. The main objective of the paper is to fill this gap. In this paper a theoretical model in order to obtain the optimal welfare price in a toll highway that competes for capturing the traffic with a conventional road is developed. This model is done for non-usual users who decide over the expectation of free flow conditions. This model is finally applied to the variables we want to focus on: average value of travel time (VTT) which is strongly related with income, dispersion of this VTT and traffic levels, from free flow to congestion. Derived from the results, we conclude that the higher the average VTT the higher the optimal price, the higher the dispersion of this VTT the lower the optimal price and finally, the more the traffic the higher the optimal toll.

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Sight distance plays an important role in road traffic safety. Two types of Digital Elevation Models (DEMs) are utilized for the estimation of available sight distance in roads: Digital Terrain Models (DTMs) and Digital Surface Models (DSMs). DTMs, which represent the bare ground surface, are commonly used to determine available sight distance at the design stage. Additionally, the use of DSMs provides further information about elements by the roadsides such as trees, buildings, walls or even traffic signals which may reduce available sight distance. This document analyses the influence of three classes of DEMs in available sight distance estimation. For this purpose, diverse roads within the Region of Madrid (Spain) have been studied using software based on geographic information systems. The study evidences the influence of using each DEM in the outcome as well as the pros and cons of using each model.

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Dimitris Pikionis: Roads of the Times

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The paper identifies the potential spatial and social impacts of a proposed road-pricing scheme for different social groups in the Madrid Metropolitan Area (MMA). We appraise the accessibility of different districts within the MMA in terms of the actual and perceived cost of using the road infrastructure ‘before’ and ‘after’ implementation of the scheme. The appraisal framework was developed using quantitative survey data and qualitative focus group discussions with residents. We then simulated user behaviours (mode and route choice) based on the empirical evidence from a travel demand model for the MMA. The results from our simulation model demonstrated that implementation of the toll on the orbital metropolitan motorways (M40, M30, for example) decreases accessibility mostly in the districts where there are no viable public transport alternatives. Our specific study finding is that the economic burden of the road-pricing scheme particularly affects unskilled and lower income individuals living in the south of the MMA. The focus groups confirmed that low income drivers in the south part of the MMA would reduce their use of tolled roads and have to find new arrangements for these trips: i.e. switch to public transport, spend double the time travelling or stay at home. More generally, our research finds that European transport planners are still a long way from recognising the social equity implications of their policy decisions and that more thorough social appraisals are needed to avoid the social exclusion of low income populations when road tolling is proposed.

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The paper explores the spatial and social impacts arising from implementation of a road-pricing scheme in the Madrid Metropolitan Area (MMA). Our analytical focus is on understanding the effects of the scheme on the transport accessibility of different social groups within the MMA. We define an evaluation framework to appraise the accessibility of different districts within the MMA in terms of the actual and perceived cost of using the road infrastructure "before" and "after" the implementation of the scheme. The framework was developed using quantitative survey data and qualitative data from focus group discussions with residents. We then simulated user behaviors (mode and route choice) based on the empirical evidence from a travel demand model for the MMA. The results from our simulation model demonstrated that implementation of the toll on the orbital metropolitan motorways (M40, M30, for example) decreases accessibility, mostly in the districts where there are no viable public transport alternatives. Our key finding is that the economic burden of the road-pricing scheme particularly affects unskilled and lower income individuals living in the south of the MMA. Consequently lower income people reduce their use of tolled roads and have to find new arrangements for these trips: i.e. switch to the public transport, spend double the time for their commuter trips or stay at home. The results of our research could be applicable more widely for anyone wishing to better understand the important relationship between increased transport cost and social equity, especially where there is an intention to introduce similar road-pricing schemes within the urban context.

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In some countries, such as Spain, it is very common that in the same corridor there are two roads with the same origin and destination but with some differences. The most important contrast is that one is a toll highway which offers a better quality than the parallel road in exchange of a price. The users decide if the price of the toll is worth paying for the advantages offered. This problem is known as the untolled alternative and it has been largely studied in the academic literature, particularly related to economic efficiency and the optimal welfare toll. However, there is a gap in the academic literature regarding how income distribution affects the optimal toll. The main objective of the paper is to fill this gap. In this paper a theoretical model is developed in order to obtain the optimal welfare price in a toll highway that competes with a conventional road for capturing the traffic. This model is done for non-usual users who decide over the expectation of free flow conditions. This model is finally applied to the variables we want to focus on: average value of travel time (VTT) which is strongly related with income, dispersion of this VTT and traffic levels, from free flow to congestion. Derived from the results, we conclude that the higher the average VTT the higher the optimal price, the higher the dispersion of this VTT the lower the optimal price and finally, the more the traffic the higher the optimal toll

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El planteamiento tradicional de análisis de la accidentalidad en carretera pasa por la consideración de herramientas paliativas, como son la identificación y gestión de los puntos negros o tramos de concentración de accidentes, o preventivas, como las auditorías e inspecciones de seguridad vial. En esta tesis doctoral se presenta un planteamiento complementario a estas herramientas, desde una perspectiva novedosa: la consideración de los tramos donde no se producen accidentes; son los denominados Tramos Blancos. La tesis persigue demostrar que existen determinados parámetros del diseño de las carreteras y del tráfico que, bajo características generales similares de las vías, tienen influencia en el hecho de que se produzcan o no accidentes, adicionalmente a la exposición al riesgo, como factor principal, y a otros factores. La propia definición de los Tramos Blancos, entendidos como tramos de carreteras de longitud representativa donde no se han producido accidentes con víctimas mortales o heridos graves durante un periodo largo de tiempo, garantiza que esta situación no se produzca como consecuencia de la aleatoriedad de los accidentes, sino que pudiera deberse a una confluencia específica de determinados parámetros de la geometría de la vía y del tráfico total y de vehículos pesados. Para el desarrollo de esta investigación se han considerado la red de autopistas de peaje y las carreteras convencionales de la Red del Estado de España, que supone un total de 17.000 kilómetros, y los datos de accidentes con víctimas mortales y heridos graves en el periodo 2006-2010, ambos incluidos, en estas redes (un total de 10.000 accidentes). La red viaria objeto de análisis supone el 65% de la longitud de la Red de Carreteras del Estado, por la que circula el 33% de su tráfico; en ella se produjeron en el año 2013 el 47% de los accidentes con víctimas y el 60% de las víctimas mortales de la Red de Carreteras del Estado. Durante la investigación se ha desarrollado una base de datos de 250.130 registros y más de 3.5 millones de datos en el caso de las autopistas de peaje de la Red de Carreteras del Estado y de 935.402 registros y más de 14 millones de datos en el caso de la red convencional del Estado analizada. Tanto las autopistas de peaje como las carreteras convencionales han sido clasificadas según sus características de tráfico, de manera que se valoren vías con nivel de exposición al riesgo similar. Para cada tipología de vía, se ha definido como longitud de referencia para que un tramo se considere Tramo Blanco la longitud igual al percentil 95 de las longitudes de tramos sin accidentes con heridos graves o víctimas mortales durante el periodo 2006-2010. En el caso de las autopistas de peaje, en la tipología que ha sido considerada para la definición del modelo, esta longitud de referencia se estableció en 14.5 kilómetros, mientras que en el caso de las carreteras convencionales, se estableció en 7.75 kilómetros. Para cada uno de los tipos de vía considerados se han construido una base de datos en la que se han incluido las variables de existencia o no de Tramo Blanco, así como las variables de tráfico (intensidad media diaria total, intensidad de vehículos pesados y porcentaje de vehículos pesados ), la velocidad media y las variables de geometría (número de carriles, ancho de carril, ancho de arcén derecho e izquierdo, ancho de calzada y plataforma, radio, peralte, pendiente y visibilidad directa e inversa en los casos disponibles); como variables adicionales, se han incluido el número de accidentes con víctimas, los fallecidos y heridos graves, índices de peligrosidad, índices de mortalidad y exposición al riesgo. Los trabajos desarrollados para explicar la presencia de Tramos Blancos en la red de autopistas de peaje han permitido establecer las diferencias entre los valores medios de las variables de tráfico y diseño geométrico en Tramos Blancos respecto a tramos no blancos y comprobar que estas diferencias son significativas. Así mismo, se ha podido calibrar un modelo de regresión logística que explica parcialmente la existencia de Tramos Blancos, para rangos de tráfico inferiores a 10.000 vehículos diarios y para tráficos entre 10.000 y 15.000 vehículos diarios. Para el primer grupo (menos de 10.000 vehículos al día), las variables que han demostrado tener una mayor influencia en la existencia de Tramo Blanco son la velocidad media de circulación, el ancho de carril, el ancho de arcén izquierdo y el porcentaje de vehículos pesados. Para el segundo grupo (entre 10.000 y 15.000 vehículos al día), las variables independientes más influyentes en la existencia de Tramo Blanco han sido la velocidad de circulación, el ancho de calzada y el porcentaje de vehículos pesados. En el caso de las carreteras convencionales, los diferentes análisis realizados no han permitido identificar un modelo que consiga una buena clasificación de los Tramos Blancos. Aun así, se puede afirmar que los valores medios de las variables de intensidad de tráfico, radio, visibilidad, peralte y pendiente presentan diferencias significativas en los Tramos Blancos respecto a los no blancos, que varían en función de la intensidad de tráfico. Los resultados obtenidos deben considerarse como la conclusión de un análisis preliminar, dado que existen otros parámetros, tanto de diseño de la vía como de la circulación, el entorno, el factor humano o el vehículo que podrían tener una influencia en el hecho que se analiza, y no se han considerado por no disponer de esta información. En esta misma línea, el análisis de las circunstancias que rodean al viaje que el usuario de la vía realiza, su tipología y motivación es una fuente de información de interés de la que no se tienen datos y que permitiría mejorar el análisis de accidentalidad en general, y en particular el de esta investigación. Adicionalmente, se reconocen limitaciones en el desarrollo de esta investigación, en las que sería preciso profundizar en el futuro, reconociendo así nuevas líneas de investigación de interés. The traditional approach to road accidents analysis has been based in the use of palliative tools, such as black spot (or road sections) identification and management, or preventive tools, such as road safety audits and inspections. This thesis shows a complementary approach to the existing tools, from a new perspective: the consideration of road sections where no accidents have occurred; these are the so-called White Road Sections. The aim of this thesis is to show that there are certain design parameters and traffic characteristics which, under similar circumstances for roads, have influence in the fact that accidents occur, in addition to the main factor, which is the risk exposure, and others. White Road Sections, defined as road sections of a representative length, where no fatal accidents or accidents involving serious injured have happened during a long period of time, should not be a product of randomness of accidents; on the contrary, they might be the consequence of a confluence of specific parameters of road geometry, traffic volumes and heavy vehicles traffic volumes. For this research, the toll motorway network and single-carriageway network of the Spanish National Road Network have been considered, which is a total of 17.000 kilometers; fatal accidents and those involving serious injured from the period 2006-2010 have been considered (a total number of 10.000 accidents). The road network covered means 65% of the total length of the National Road Network, which allocates 33% of traffic volume; 47% of accidents with victims and 60% of fatalities happened in these road networks during 2013. During the research, a database of 250.130 registers and more than 3.5 million data for toll motorways and 935.042 registers and more than 14 million data for single carriageways of the National Road Network was developed. Both toll motorways and single-carriageways have been classified according to their traffic characteristics, so that the analysis is performed over roads with similar risk exposure. For each road type, a reference length for White Road Section has been defined, as the 95 percentile of all road sections lengths without accidents (with fatalities or serious injured) for 2006-2010. For toll motorways, this reference length concluded to be 14.5 kilometers, while for single-carriageways, it was defined as 7.75 kilometers. A detailed database was developed for each type of road, including the variable “existence of White Road Section”, as well as variables of traffic (average daily traffic volume, heavy vehicles average daily traffic and percentage of heavy vehicles from the total traffic volume), average speed and geometry variables (number of lanes, width of lane, width of shoulders, carriageway width, platform width, radius, superelevation, slope and visibility); additional variables, such as number of accidents with victims, number of fatalities or serious injured, risk and fatality rates and risk exposure, have also been included. Research conducted for the explanation of the presence of White Road Sections in the toll motorway network have shown statistically significant differences in the average values of variables of traffic and geometric design in White Road Sections compared with other road sections. In addition, a binary logistic model for the partial explanation of the presence of White Road Sections was developed, for traffic volumes lower than 10.000 daily vehicles and for those running from 10.000 to 15.000 daily vehicles. For the first group, the most influent variables for the presence of White Road Sections were the average speed, width of lane, width of left shoulder and percentage of heavy vehicles. For the second group, the most influent variables were found to be average speed, carriageway width and percentage of heavy vehicles. For single-carriageways, the different analysis developed did not reach a proper model for the explanation of White Road Sections. However, it can be assumed that the average values of the variables of traffic volume, radius, visibility, superelevation and slope show significant differences in White Road Sections if compared with others, which also vary with traffic volumes. Results obtained should be considered as a conclusion of a preliminary analysis, as there are other parameters, not only design-related, but also regarding traffic, environment, human factor and vehicle which could have an influence in the fact under research, but this information has not been considered in the analysis, as it was not available. In parallel, the analysis of the circumstances around the trip, including its typology and motivation is an interesting source of information, from which data are not available; the availability of this information would be useful for the improvement of accident analysis, in general, and for this research work, in particular. In addition, there are some limitations in the development of the research work; it would be necessary to develop an in-depth analysis in the future, thus assuming new research lines of interest.