The purpose of this research project was to evaluate the techniques outlined in the National Cooperative Highway Research Program Technical Report 255 Highway Traffic Data for Urbanized Area Project Planning and Design (NCHRP-255), published in 1982 by the Transportation Research Board. This evaluation was accomplished by using a regional travel demand forecast model calibrated and validated for the year 1990 and developing a highway forecast for the year 2000. The forecasted volumes along the Capital Beltway (I-495/I-95) portion located in the State of Maryland were compared to observed count data for that same year. A series of statistical measures were used to quantitatively evaluate the benefits of the techniques documented in NCHRP-255. The primary research objectives were: • To critically evaluate the ability of a regional travel demand forecast model to accurately forecast freeway corridor volumes by comparing link forecast volumes to the actual count data. • To evaluate and determine the significance of post-processing techniques as outlined in NCHRP-255. The most important lesson learned from this research is that although it was originally written in 1982, NCHRP-255 is still a very valuable resources for supplementing travel demand forecast model output. The "raw" model output is not reliable enough to be used directly for highway design, operational analysis, nor alternative or economic evaluations. The travel demand forecast model is a tool that is just part of the forecasting process. It is not a turn-key operation, and travel demand forecasts cannot be done without the application of engineering judgment. / Master of Science

Long-range demand planning and capacity management play an important role for policy makers and airline managers alike. Each makes decisions regarding allocating appropriate levels of funds to align capacity with forecasted demand. Decisions today can have long lasting effects. Reducing forecast errors for long-range range demand forecasting will improve resource allocation decision making. This research paper will focus on improving long-range demand planning and forecasting errors of passenger traffic in the U.S. domestic airline industry. This paper will look to build upon current forecasting models being used for U.S. domestic airline passenger traffic with the aim of improving forecast errors published by Federal Aviation Administration (FAA). Using historical data, this study will retroactively forecast U.S. domestic passenger traffic and then compare it to actual passenger traffic, then comparing forecast errors. Forecasting methods will be tested extensively in order to identify new trends and causal factors that will enhance forecast accuracy thus increasing the likelihood of better capacity management and funding decisions.

A tool to model both current rail and future high-speed rail (HSR) corridors has been presented in this work. The model is designed as an addition to the existing TSAM (Transportation System Analysis Model) capabilities of modeling commercial airline and automobile demand. TSAM is a nationwide county to county multimodal demand forecasting tool based on the classical four step process. A variation of the Box-Cox logit model is proposed to best capture the characteristic behavior of rail demand in US. The utility equation uses travel time and travel cost as the decision variables for each model. Additionally, a mode specific geographic constant is applied to the rail mode to model the North-East Corridor (NEC). NEC is of peculiar interest in modeling, as it accounts for most of the rail ridership. The coefficients are computed using Genetic Algorithms. A one county to one station assignment is employed for the station choice model. Modifications are made to the station choice model to replicate choices affected by the ease of access via driving and mass transit. The functions for time and cost inputs for the rail system were developed from the AMTRAK website. These changes and calibration coefficients are incorporated in TSAM. The TSAM model is executed for the present and future years and the predictions are discussed. Sensitivity analysis for cost and speed of the predicted HSR is shown. The model shows the market shift for different modes with the introduction of HSR. Limited data presents the most critical hindrance in improving the model further. The current validation process incorporates essential assumptions and approximations for transfer rates, short trip percentages, and access and egress distances. The challenges for the model posed by limited data are discussed in the model. / Master of Science

Dans le cadre du protocole de Kyoto, la France s’est engagée à diviser par quatre ses émissions de gaz à effet de serre (GES) de 1990 à l'horizon 2050. Le Mexique a pour objectif d’atteindre une réduction de 50% en 2050 par rapport à l’année 2000. En vue du poids croissant du secteur des transport dans les villes d’environ 1 million d’habitants dans le total des émissions de CO2, nous souhaitons vérifier dans quelles mesures les expériences observées dans le Nord (plafonnement de la mobilité, diffusion de nouvelles technologies sur les véhicules) peuvent se répéter dans le Sud. Nous nous sommes pour cela appuyé sur des études de cas en France (Paris et Lille) et au Mexique (Juarez et Puebla). Le premier objectif de cette thèse a été d’identifier les déterminants de la mobilité urbaine. Le deuxième objectif a été d’appliquer le modèle âge-cohorte pour la prévision de la demande de transport, afin de prendre en compte l’évolution de la structure de la population (vieillissement) et les changements de comportement. Finalement, nous avons développé des diagnostics des émissions de GES. En France, nous avons observé des tendances vers une réduction des émissions de GES due à la baisse de la mobilité et aux nouvelles technologies, mais qui est encore loin d'être suffisante pour atteindre les objectifs fixés. Les études de cas du Mexique montrent l’incapacité à inverser la tendance à l'augmentation des émissions de GES ; par conséquent les objectifs de réduction seront difficilement atteints. Le cas du Mexique peut nous donner un aperçu des tendances dans les pays émergents, qui sont très loin d'atteindre un développement durable et resteront face à un grand défi dans le futur. / In the context of the Kyoto Protocol, France has set Greenhouse Gas (GHG) emission reduction targets of 75% below 1990 levels by 2050. More recently, Mexico has set the objective to achieve a 50% reduction by 2050 with respect to the base year 2000. Since the transport sector in urban areas with approximately 1 million inhabitants accounts for most CO2 emissions and will continue to increase its share, we wanted to determine to what extent the experiences observed in cities from developed countries (peak travel, dissemination of new vehicle technologies) may be repeated in urban areas from developing nations. For this purpose, we focus on case studies in France (Paris and Lille) and Mexico (Juarez and Puebla). The first objective of this thesis was to identify the determinants of mobility on each urban region. The second objective was to apply the age-cohort model for the development of long-term travel demand forecasts in order to take into account changes in the population structure (ageing) and in travel behaviour. The last objective was to develop GHG emissions assessments from observed travel demand. The decline in mobility and the dissemination of new vehicle technologies in France led to a reduction in GHG emissions. However, these changes are not sufficient to achieve the GHG reduction targets. The case studies in Mexico show the inability to reverse the trend towards the increase of GHG emissions; therefore the reduction targets will be hardly achieved. The case of Mexico give us an overview of trends in emerging countries, which are very far from achieving sustainable development and will face a major challenge in the coming decades.