Guide for forecasting traffic on the interstate system for use in preparing cost estimates /

"Circular memorandum to: Division Engineers".

Update of TSC highway traffic noise prediction code (1974) /

Mode of access: Internet.

Evaluación de la distribución de riesgos en los distintos modelos de asociación público-privada para la provisión de infraestructura carretera en México

México es de los pocos países en el mundo que ha realizado dos grandes programas para la construcción de autopistas en colaboración con el sector privado. El primero, fue realizado entre 1989 y 1994, con resultados adversos por el mal diseño del esquema de concesiones; y, el segundo con mejores resultados, en operación desde 2003 mediante nuevos modelos de asociación público-privada (APP). El objetivo de la presente investigación es estudiar los modelos de asociación público-privada empleados en México para la provisión de infraestructura carretera, realizando el análisis y la evaluación de la distribución de riesgos entre el sector público y privado en cada uno de los modelos con el propósito de establecer una propuesta de reasignación de riesgos para disminuir el costo global y la incertidumbre de los proyectos. En la primera parte se describe el estado actual del conocimiento de las asociaciones público-privadas para desarrollar proyectos de infraestructura, incluyendo los antecedentes, la definición y las tipologías de los esquemas APP, así como la práctica internacional de programas como el modelo británico Private Finance Initiative (PFI), resultados de proyectos en la Unión Europea y programas APP en otros países. También, se destaca la participación del sector privado en el financiamiento de la infraestructura del transporte de México en la década de 1990. En los capítulos centrales se aborda el estudio de los modelos APP que se han utilizado en el país en la construcción de la red de carreteras de alta capacidad. Se presentan las características y los resultados del programa de autopistas 1989-94, así como el rescate financiero y las medidas de reestructuración de los proyectos concesionados, aspectos que obligaron a las autoridades mexicanas a cambiar la normatividad para la aprobación de los proyectos según su rentabilidad, modificar la legislación de caminos y diseñar nuevos esquemas de colaboración entre el gobierno y el sector privado. Los nuevos modelos APP vigentes desde 2003 son: nuevo modelo de concesiones para desarrollar autopistas de peaje, modelo de proyectos de prestación de servicios (peaje sombra) para modernizar carreteras existentes y modelo de aprovechamiento de activos para concesionar autopistas de peaje en operación a cambio de un pago. De estos modelos se realizaron estudios de caso en los que se determinan medidas de desempeño operativo (niveles de tráfico, costos y plazos de construcción) y rentabilidad financiera (tasa interna de retorno y valor presente neto). En la última parte se efectúa la identificación, análisis y evaluación de los riesgos que afectaron los costos, el tiempo de ejecución y la rentabilidad de los proyectos de ambos programas. Entre los factores de riesgo analizados se encontró que los más importantes fueron: las condiciones macroeconómicas del país (inflación, producto interno bruto, tipo de cambio y tasa de interés), deficiencias en la planificación de los proyectos (diseño, derecho de vía, tarifas, permisos y estimación del tránsito) y aportaciones públicas en forma de obra. Mexico is one of the few countries in the world that has developed two major programs for highway construction in collaboration with the private sector. The first one was carried out between 1989 and 1994 with adverse outcomes due to the wrong design of concession schemes; and, the second one, in operation since 2003, through new public-private partnership models (PPPs). The objective of this research is to study public-private partnership models used in Mexico for road infrastructure provision, performing the analysis and evaluation of risk’s distribution between the public and the private sector in each model in order to draw up a proposal for risk’s allocation to reduce the total cost and the uncertainty of projects. The first part describes the current state of knowledge in public-private partnership to develop infrastructure projects, including the history, definition and types of PPP models, as well as international practice of programs such as the British Private Finance Initiative (PFI) model, results in the European Union and PPP programs in other countries. Also, it stands out the private sector participation in financing of Mexico’s transport infrastructure in 1990s. The next chapters present the study of public-private partnerships models that have been used in the country in the construction of the high capacity road network. Characteristics and outcomes of the highway program 1989-94 are presented, as well as the financial bailout and restructuring measures of the concession projects, aspects that forced the Mexican authorities to change projects regulations, improve road’s legislation and design new schemes of cooperation between the Government and the private sector. The new PPP models since 2003 are: concession model to develop toll highways, private service contracts model (shadow toll) to modernize existing roads and highway assets model for the concession of toll roads in operation in exchange for a payment. These models were analyzed using case studies in which measures of operational performance (levels of traffic, costs and construction schedules) and financial profitability (internal rate of return and net present value) are determined. In the last part, the analysis and assessment of risks that affect costs, execution time and profitability of the projects are carried out, for both programs. Among the risk factors analyzed, the following ones were found to be the most important: country macroeconomic conditions (inflation, gross domestic product, exchange rate and interest rate), deficiencies in projects planning (design, right of way, tolls, permits and traffic estimation) and public contributions in the form of construction works.

Urban transportation energy conservation /

Vol. 1 has title: Analytical procedures for urban transportation energy conservation.

Impact of demographic and migration trends on future travel in metropolitan areas.

Mode of access: Internet.

Consequences of small sample 0-D data collection in the transportation planning process /

Mode of access: Internet.

A Novel Framework for Real-time Traffic Flow Parameter Estimation from Aerial Videos

Thesis (Master's)--University of Washington, 2016-06

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Estimation of the Traffic Intensity in a Piecewise-stationary Mt/Gt/1 Queue with Probing

We use a probing strategy to estimate the time dependent traffic intensity in an Mt/Gt/1 queue, where the arrival rate and the general service-time distribution change from one time interval to another, and derive statistical properties of the proposed estimator. We present a method to detect a switch from a stationary interval to another using a sequence of probes to improve the estimation. At the end, we compare our results with two estimators proposed in the literature for the M/G/1 queue.

A safety assessment methodology applied to CNS/ATM-based air traffic control system

In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm, based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining ""absolute"" and ""relative"" safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 [14], using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the ""Automatic Dependent Surveillance-Broadcasting"" (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric. (C) 2011 Elsevier Ltd. All rights reserved.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)