935 resultados para 350405 Road and Rail Transportation


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Mode of access: Internet.

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Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

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The problem of modal choice between rail and air arises as public awareness of carbon dioxide (CO2) emissions by the transportation sector rises. In this paper, we answer this question quantitatively by performing an efficiency benchmarking analysis that takes into account life-cycle CO2 emission due to transport service provision. The paper employs nonparametric efficiency estimation methods, namely a slacks-based inefficiency measure, as well as a more conventional directional distance function approach. We apply them to a panel data set for three major railway companies and the aviation sector in Japan for the period from 1999 to 2007. Results shows that, contrary to the common argument, air transport can still be more socially efficient than rail transport, even when the environmental load due to CO2 emission is incorporated. This is due to the aviation sector's extremely low user cost, measured in terms of in-vehicle time. In other words, aviation is a necessary transportation mode for those with a very high willingness to pay for their time.

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Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

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Transportation Department, Office of the Assistant Secretary for Policy and International Affairs, Washington, D.C.

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Transportation Department, Office of the Assistant Secretary for Policy and International Affairs, Washington, D.C.

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Description based on: Adopted Jan. 2, 1971.

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Mode of access: Internet.

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A year ago, I became aware of the historical existence of the group CERFI— Le centre d’etudes, de recherches, et de formation institutionelles, or The Study Center for Institutional Research and Formation. CERFI emerged in 1967 under the hand of Lacanian psychiatrist and Trotskyite activist Félix Guattari, whose antonymous journal Recherches chronicled the group’s subversive experiences, experiments, and government-sponsored urban projects. It was a singularly bizarre meeting of the French bureaucracy with militant activist groups, the French intelligentsia, and architectural and planning practitioners at the close of the ‘60s. Nevertheless, CERFI’s analysis of the problems of society was undertaken precisely from the perspective of the state, and the Institute acknowledged a “deep complicity between the intellectual and statesman ... because the first critics of the State, are officials themselves!”1 CERFI developed out of FGERI (The Federation of Groups for Institutional Study and Research), started by Guattari two years earlier. While FGERI was created for the analysis of mental institutions stemming from Guattari’s work at La Borde, an experimental psychiatric clinic, CERFI marks the group’s shift toward urbanism—to the interrogation of the city itself. Not only a platform for radical debate on architecture and the city, CERFI was a direct agent in the development of urban planning schemata for new towns in France. 2 CERFI’s founding members were Guattari, the economist and urban theorist François Fourquet, feminist philosopher Liane Mozère, and urban planner and editor of Multitides Anne Querrien—Guattari’s close friend and collaborator. The architects Antoine Grumback, Alain Fabre, Macary, and Janine Joutel were also members, as well as urbanists Bruno Fortier, Rainier Hoddé, and Christian de Portzamparc. 3 CERFI was the quintessential social project of post-‘68 French urbanism. Located on the Far Left and openly opposed to the Communist Party, this Trotskyist cooperative was able to achieve what other institutions, according to Fourquet, with their “customary devices—the politburo, central committee, and the basic cells—had failed to do.”4 The decentralized institute recognized that any formal integration of the group was to “sign its own death warrant; so it embraced a skein of directors, entangled, forming knots, liquidating all at once, and spinning in an unknown direction, stopping short and returning back to another node.” Allergic to the very idea of “party,” CERFI was a creative project of free, hybrid-aesthetic blocs talking and acting together, whose goal was none other than the “transformation of the libidinal economy of the militant revolutionary.” The group believed that by recognizing and affirming a “group unconscious,” as well as their individual unconscious desires, they would be able to avoid the political stalemates and splinter groups of the traditional Left. CERFI thus situated itself “on the side of psychosis”—its confessed goal was to serve rather than repress the utter madness of the urban malaise, because it was only from this mad perspective on the ground that a properly social discourse on the city could be forged.

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We conducted on-road and simulator studies to explore the mechanisms underpinning driver-rider crashes. In Study 1 the verbal protocols of 40 drivers and riders were assessed at intersections as part of a 15km on-road route in Melbourne. Network analysis of the verbal transcripts highlighted key differences in the situation awareness of drivers and riders at intersections. In a further study using a driving simulator we examined in car drivers the influence of acute exposure to motorcyclists. In a 15 min simulated drive, 40 drivers saw either no motorcycles or a high number of motorcycles in the surrounding traffic. In a subsequent 45-60 min drive, drivers were asked to detect motorcycles in traffic. The proportion of motorcycles was manipulated so that there was either a high (120) or low (6) number of motorcycles during the drive. Those drivers exposed to a high number of motorcycles were significantly faster at detecting motorcycles. Fundamentally, the incompatible situation awareness at intersections by drivers and riders underpins the conflicts. Study 2 offers some suggestion for a countermeasure here, although more research around schema and exposure training to support safer interactions is needed.