A ferrovia e o automóvel: ícones da modernidade na cidade de Bauru (1917-1939)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Lattices from subfields of Q (xi n)

In this paper we present a method for evaluating the center density of algebraic lattices from subfields of Q(xi n), where n is a positive integer. This method allows to reproduce rotated versions of dense lattices in some dimensions. Constellations on algebraic lattices with high packing density have been proposed for use in communications in Gaussian channels and also in Rayleigh fading channels in case they have high diversity.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

An introduction to China's rail transport Part 2: Urban rail transit systems, highway transport and the reform of China's railways

In this paper, an introduction is provided to some of the components of China's transport system. The authors include the urban rail transit systems, the highway transport systems and its competition for China's railways and the reform of China's railway industry. This is the second of two papers on the situation of rail transport in China.

Evaluation of the influence of toll systems on energy consumption and CO2 emissions: A case study of a Spanish highway

This paper studies the energy consumption and subsequent CO2 emissions of road highway transportation under three toll systems in Spain for four categories of vehicles: cars, vans, buses and articulated trucks. The influence of toll systems is tested for a section of AP-41 highway between Toledo and Madrid. One system is free flow, other is traditional stop and go and the last toll system operates with an electronic toll collection (ETC) technology. Energy consumption and CO2 emissions were found to be closely related to vehicle mass, wind exposure, engine efficiency and acceleration rate. These parameters affect, directly or indirectly, the external forces which determine the energy consumption. Reducing the magnitude of these forces through an appropriate toll management is an important way of improving the energy performance of vehicles. The type of toll system used can have a major influence on the energy efficiency of highway transportation and therefore it is necessary to consider free flow.

Systems analysis and design guidelines for highway advisory radio. Executive summary. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Systems analysis and design guidelines for highway advisory. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Recent international activity in cooperative vehicle-highway automation systems /

This report summarizes the current state of the art in cooperative vehicle-highway automation systems in Europe and Asia based on a series of meetings, demonstrations, and site visits, combined with the results of literature review. This review covers systems that provide drivers with a range of automation capabilities, from driver assistance to fully automated driving, with an emphasis on cooperative systems that involve active exchanges of information between the vehicles and the roadside and among separate vehicles. The trends in development and deployment of these systems are examined by country, and the similarities and differences relative to the U.S. situation are noted, leading toward recommendations for future U.S. action. The Literature Review on Recent International Activity in Cooperative Vehicle-Highway Automation Systems is published separately as FHWA-HRT-13-025.

Literature review on recent international activity in cooperative vehicle-highway automation systems /

This literature review supports the report, Recent International Activity in Cooperative Vehicle-Highway Automation Systems. It reviews the published literature in English dating from 2007 or later about non-U.S.-based work on cooperative vehicle-highway automation systems. This review covers work performed in Europe and Japan, with application to transit buses, heavy trucks, and passenger cars. In addition to fully automated driving of the vehicles (without human intervention), it also covers partial automation systems, which automate subsets of the total driving process. Recent International Activity in Cooperative Vehicle Highway Automation Systems is published separately as FHWA-HRT-12-033.

Standby power for railroad-highway grade crossing warning systems. Final report.

Federal Railroad Administration, Office of Rail Safety Research, Washington, D.C.

Potential means of cost reduction in grade crossing automatic gate systems. Volume I: overview and low cost railroad/highway grade crossing gate systems. Final report.

Transportation Systems Center, Cambridge, Mass.

Potential means of cost reduction in grade crossing automatic gate systems. Volume II: improved gate arm concepts for railroad/highway grade crossings. Final report.

Transportation Systems Center, Cambridge, Mass.

Innovative concepts and technology for railroad-highway grade crossing motorist warning systems. Vol. I: overview and concept generation and analysis. Final report.

Transportation Systems Center, Cambridge, Mass.

Innovative concepts and technology for railroad-highway grade crossing motorist warning systems. Vol. II: the generation and analysis of alternative concepts. Final report.

Transportation Systems Center, Cambridge, Mass.