Emerging technologies and business models have contributed to the improvement of transportation systems and services towards a more sustainable approach to mobility. Shared mobility has become widespread as a viable solution to the increasing demand for transportation. Many cities worldwide have implemented shared mobility service and demonstrated that it could offer numerous environmental and operational benefits. However, their implementation in rural and suburban areas that feature lower population density and dispersed travel demand is not receiving the same attention. This research considers four suburban communities to evaluate the operation of a fleet of shared mobility as a potential substitute for the currently fix-route public transportation services. For each area, four scenarios were defined to consider different powertrain technologies. These scenarios include the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicles scenarios. While assessing the efficiency of the fleet composition system, four vehicle sizes are considered. Further, an optimized routing solution for serving the known travel demand is utilized to calculate the total cost of fleet ownership, which accounts for the purchase price, energy consumption, CO2, and driver labour costs. The results highlight potential benefits of adopting a fleet of shared Autonomous Electric Vehicles for the case studies and show approximately 67-68% and 69-70% savings compared to a shared fleet of conventional and Battery Electric vehicles, respectively, mainly due to the omission of the driver costs. In the absence of operationally safe Autonomous Electric Vehicles, the more conservative scenario of employing a fleet of shared Autonomous Electric Vehicles with the presence of safety attendants could result in 6-8% and 13-14% savings compared to a shared fleet of conventional and Battery Electric vehicles. Nevertheless, the results indicate low utilization rates for the fleet attributed to the inconsistency in demand throughout the day. The results provided in this research can inform policymakers and service providers and be used for further evaluations of such transportation services. / Thesis / Master of Applied Science (MASc) / In pursuit of more equitable, sustainable, and connected transportation services in rural and suburban areas, this research investigates the quantitative benefits and costs of operating a ride-sharing service for four suburban areas located in Hamilton, Ontario. The study considers and compares several options in vehicle sizes and technologies to provide a better ground of knowledge for service providers and policymakers.

In 2014, the European Union and its members agreed to reduce carbon dioxide emissions by 40 percent before 2030. The Bonus-Malus, a feebate tax scheme, was introduced in Sweden in 2018 in the hopes that it would result in lower carbon dioxide emission from Sweden’s transport sector. Sweden’s feebate is a regulatory measure to achieve an efficient cost-constrained environmental policy, thus reduce the negative externalities from the transport sector. Using a Difference-in-Differences approach, this paper aims to determine who benefits from tax incentives created from the implementation of the feebate tax in Sweden using panel data of list prices and vehicle characteristics between 2015 and 2020. The results indicates that there is no long-run price effect when introducing the Swedish feebate tax. Moreover, the results from the additional analysis indicate that the manufacturers’ list price adjustments to the Swedish feebate tax are overshadowed by the introduction of the EU carbon dioxide emission standards because of the close time proximity between the two policy measures. The lack of list price adjustments enables consumers in Sweden to exploit an arbitrage opportunity in that they can gain the entirety of the subsidy but also suffer the entire cost of the malus fees.

No description available.

The current airline practice is to assign aircraft capacity to scheduled flights well in advance of departure. At such an early stage in this process, the high uncertainty of demand poses a major impediment for airlines to best match the airplane capacities with the final demand. However, the accuracy of the demand forecast improves markedly over time, and revisions to the initial fleet assignment become naturally pertinent when the observed demand considerably differs from the assigned aircraft capacity. The Demand Driven Re-fleeting (DDR) approach proposed in this thesis offers a dynamic re-assignment of aircraft capacity to the flight network, as and when improved demand forecasts become available, so as to maximize the total revenue. Because of the need to preserve the initial crew schedule, this re-assignment approach is limited within a single family of aircraft and to the flights assigned to this particular family. This restriction significantly reduces the problem size. As a result, it becomes computationally tractable to include path level demand information into the DDR model, although the problem size can then get very large because of the numerous combinations of composing paths from legs. As an extension, models considering path-class level differences, day-of-week demand variations, and re-capture effects are also presented. The DDR model for a single family with path level demand considerations is formulated as a mixed-integer programming problem. The model's polyhedral structure is studied to explore ways for tightening its representation and for deriving certain classes of valid inequalities. Various approaches for implementing such reformulation techniques are investigated and tested. The best of these procedures for solving large-scale challenging instances of the problem turns out to be an integrated approach that uses certain selected model augmentations and valid inequalities generated via a suitable separation routine and a partial convex hull construction process. Using this strategy in concert with properly selected CPLEX options reduces the CPU time by an average factor of 7.48 over an initial model for a test-bed of problems each having 200 flights in total. Prompted by this integrated heuristic approach, a procedure for finding solutions within a prescribed limit of optimality is suggested. To demonstrate the effectiveness of these developed methodologies, we also solved two large-scale practical-sized networks that respectively involve 800 and 1060 flights, and 18196 and 33105 paths in total, with 300 and 396 flights belonging to the designated family. These problems were typically solved within 6 hours on a SUN Ultra 1 Workstation having 260 MB RAM and a clock-speed of 167 MHz, with one exception that required 14 hours of CPU time. This level of computational effort is acceptable considering that such models are solved at a planning stage in the decision process. / Master of Science

Rail and truck freight transportation systems provide vital logistics services today. Rail systems are generally used to transport heavy and bulky commodities over long distances, while trucks tend to provide fast and flexible service for small and high-value products. In this dissertation, we study two different distribution planning problems that arise in rail and truck transportation systems. In the railroad industry, shipments are often grouped together to form a block to reduce the impact of reclassification at train yards. We consider the time and capacity constrained routing (TCCR) problem, which assigns shipments to blocks and train-runs to minimize overall transportation costs, while considering the train capacities and shipment due dates. Two mathematical formulations are developed, including an arc-based formulation and a path-based formulation. To solve the problem efficiently, two solution approaches are proposed. The sequential algorithm assigns shipments in order of priority while considering the remaining train capacities and due dates. The bump-shipment algorithm initially schedules shipments simultaneously and then reschedules the shipments that exceed the train capacity. The algorithms are evaluated using a data set from a major U.S. railroad with approximately 500,000 shipments. Industry-sized problems are solved within a few minutes of computational time by both the sequential and bump-shipment algorithms, and transportation costs are reduced by 6% compared to the currently used trip plans. For truck transportation systems, trailer fleet planning (TFP) is an important issue to improve services and reduce costs. In this problem, we consider the quantities and types of trailers to purchase, rent, or relocate among depots to meet time varying demands. Mixed-integer programming models are developed for both homogeneous and heterogeneous TFP problems. The objective is to minimize the total fleet investment costs and the distribution costs across multiple depots and multiple time periods. For homogeneous TFP problem, a two-phase solution approach is proposed. Phase I concentrates on distribution costs and determines the suggested fleet size. A sweep-based routing heuristic is applied to generate candidate routes of good quality. Then a reduced mathematical model selects routes for meeting customer demands and determines the preferred fleet size. Phase II provides trailer purchase, relocation, and rental decisions based on the results of Phase I and relevant cost information. This decomposition approach removes the interactions between depots and periods, which greatly reduces the complexity of the integrated optimization model. For the heterogeneous TFP problem, trailers with different capacities, costs, and features are considered. The two-phase approach, developed for the homogeneous TFP, is modified. A rolling horizon scheme is applied in Phase I to consider the trailer allocations in previous periods when determining the fleet composition for the current period. Additionally, the sweep-based routing heuristic is also extended to capture the characteristics of continuous delivery practice where trailers are allowed to refill products at satellite facilities. This heuristic generates routes for each trailer type so that the customer-trailer restrictions are accommodated. The numerical studies, conducted using a data set with three depots and more than 400 customers, demonstrate the effectiveness of the two-phase approaches. Compared to the integrated optimization models, the two-phase approaches obtain quality solutions within a reasonable computational time and demonstrate robust performance as the problem sizes increase. Based on these results, a leading industrial gas provider is currently integrating the proposed solution approaches as part of their worldwide distribution planning software. / Ph. D.

Pour relever les défis grandissants auxquels est confronté le système de mobilité en termes de durabilité, les autorités publiques françaises ont entrepris de soutenir l'innovation, notamment dans le domaine automobile. Les entreprises occupent une position particulière au sein du système de mobilité : leurs décisions influencent les comportements de mobilité bien au-delà des seuls déplacements professionnels. Chaque année en France, 4 véhicules légers sur 10 parmi les voitures particulières et véhicules utilitaires neufs mis sur le marché sont acquis par des entreprises. Pourtant, la mobilité professionnelle en général, et les flottes automobiles d'entreprise en particulier, demeurent des zones d'ombre de la connaissance du système de mobilité. L'objet de notre travail et sa contribution principale est de démontrer que, compte tenu de leurs effets sur l'ensemble du système de mobilité d'une part, de leur sensibilité aux politiques publiques d'autre part, les flottes automobiles d'entreprise constituent un objet pertinent tant pour la recherche que pour l'action publique. Notre investigation s'appuie sur des méthodes multiples : outre une synthèse de sources bibliographiques variées (journaux professionnels, archives légales, etc.), nous proposons des recoupements originaux entre, d'une part, des données quantitatives sur la composition et l'usage des flottes automobiles d'entreprise issues d'enquêtes de grande envergure et, d'autre part, les résultats qualitatifs d'une enquête exploratoire menée auprès de gestionnaires de flotte en région parisienne. Nous développons un ensemble de définitions et de cadres analytiques pour étudier les flottes automobiles d'entreprise, et notamment une typologie de véhicules basée sur les différents niveaux de « droits » accordés à l'utilisateur du véhicule d'entreprise. Nous montrons que les flottes automobiles d'entreprise totalisent 15% de l'ensemble des véhicules légers en France, 25% de leur kilométrage et 25% à 30% de leurs émissions de CO2.Par ailleurs, nous révélons le rôle essentiel que peuvent jouer les flottes automobiles d'entreprise pour amorcer des changements dans le parc automobile français. Nous montrons que les usages quotidiens des véhicules d'entreprise sont très divers, et dans certains cas compatibles avec les véhicules électriques. Enfin, nous mettons en évidence les effets tangibles des politiques fiscales sur la dynamique de diffusion des innovations au sein des flottes automobiles d'entreprise. Nous examinons les implications de ces résultats en termes de politiques publiques, en soulignant le besoin d'une plus grande intégration entre politiques industrielles, politiques de transport et politiques fiscales. Nous mettons en particulier en évidence le besoin d'une coordination accrue entre les politiques publiques menées à différentes échelles et d'un phasage approprié de ces politiques. Dans le contexte actuel, une plus grande transparence semble requise quant à la pérennité des mesures d' « amorçage » (par exemple, le bonus à l'achat) et au volontarisme des mesures de « soutien » (par exemple, les zones à basses émissions) qui pourraient être adoptées à moyen ou long terme / The mobility system in France faces increasing sustainability challenges. In response, French public authorities have endeavoured to foster innovation in the mobility system, with a particular focus on the automotive subsystem, where the challenges are most acute. Corporations have a special position in the mobility system: their decisions influence mobility behaviours well beyond corporate mobility patterns alone. Every year in France, 4 out of 10 new light-duty vehicles (including passenger cars and light commercial vehicles) are sold to corporations. Yet, corporate mobility in general, and corporate car fleets in particular, are still blind spots in the collective understanding of the mobility system. The main contribution of our work is to demonstrate that, given their effects on the larger mobility system, and given their sensitivity to public policies, corporate car fleets are a relevant object for research and a relevant matter for public policy discussion. Our research is a multi-method investigation, collecting information from a wide range of sources, including professional journals and legal archives, and cross-checking quantitative results on the composition and use patterns of corporate car fleets from large mobility surveys in France against qualitative insights gained from an exploratory survey of fleet managers in the Paris region. We develop a set of definitions and analytical frameworks for investigating corporate car fleets, including a typology of vehicles based on the various levels of ‘rights' granted to the employee over the vehicle. We show that corporate car fleets could account for 15% of the total light-duty vehicle fleet in France, 25% of its total mileage and 25% to 30% of its CO2 emissions. We also reveal the instrumental role that corporate car fleets can play in setting new trends for France's global vehicle stock. We highlight that the daily patterns of use of corporate vehicles are highly diverse, and partly compatible with electric vehicles. Finally, we show that tax policies have significant effects on the dynamics of the spread of innovations in corporate car fleets. We discuss the implications of these results for policy-making and stress the need for further integration between industrial policies, transport policies, and tax policies. We further emphasise the need for greater coordination between the various levels of government, and for adequate phasing of public policies. At present, more transparency is needed about how long current ‘initiating' policies (e.g. purchase bonus) will last, and how strong the ‘supporting' policies (e.g. low-emission zones) will be in the medium- to long-term

This thesis presents a program of research exploring the multilevel organisational structure of fleet safety management. The aim of this research was to investigate three current fleet safety initiatives, and individual and contextual factors influencing safe driving behaviour in a work vehicle. Three studies were conducted to achieve this aim. This research utilised a sample of employees from a range of Queensland Government agencies.----- Study one evaluated three current fleet safety initiatives within the Queensland Government. From a sample of fleet co-ordinators (N=24) and drivers (N=88), this study established the extent to which specific psychological processes underlying the fleet safety initiatives were adopted, and the attitude change associated with their use. This study found mixed support for the Hypotheses, with the influence of the fleet safety initiatives on fleet co-ordinators' and drivers' attitude change being consistent with processes associated with the persuasive communication framework, and behaviour management. However, the study found no support for the behavioural management processes hypothesised to underlie the incentive scheme (CPP). The findings of the study suggested that while fleet safety initiatives can have an influence on fleet co-ordinator and driver attitude change, their impact depends on the extent to which safety issues are viewed as relevant, and the extent to which there is reinforcement within the organisational environment to support these safety initiatives. Therefore, the findings from this study, combined with existing research into the impact of safety climate, suggest the workplace context needs to be taken into account. For this reason, study two investigated the role of perceptions of the safety climate, in addition to individual attributes, as predictors of self-reported crash involvement.----- Study two applied a framework incorporating driver attributes, including attitudes towards traffic safety and self-efficacy, and drivers' perceptions of the safety climate, as predictors of self-reported crashes in a work vehicle. Within this framework, drivers' perception of the safety climate, and their individual attributes were conceptualised as antecedents of driving performance, and driver safety motivation and knowledge mediated the relationship between these factors and self-reported crashes. A total of 385 drivers participated in this study, which found motivation to drive safely mediated the relationship between driver attributes and self-reported crashes. The initial analysis did not find a significant relationship between safety climate and safety motivation. However, posthoc analyses exploring this non-significant relationship found managerial safety values could be distinguished from other facets of the safety climate construct. Subsequently, the results indicated managerial safety values predicted safety motivation, when drivers perceived a strong safety climate. This study provided a more thorough understanding of the variables predicting driver behaviour at an individual level of analysis. However, a shortcoming is the study did not consider the various influences impacting on drivers' safety perceptions, and individual attributes within the context of the work environment.----- Study three extended on the framework established in study two, and investigated the contribution of leader attributes to the prediction of drivers' safety perceptions, and individual attributes. The leader attribute measures, specifically, perceptions of the safety climate, motivation, knowledge, and work overload were collected from a sample of fleet co-ordinators (N=52) and supervisors (N=88). Through multi-level analyses, both supervisors and fleet co-ordinators were shown to influence the safety perceptions and individual attributes of individuals who drive work vehicles. Support was found for positive relationships between supervisor safety knowledge, and the individual attributes. However, there was a large amount of variation due to group membership unaccounted for by supervisor safety knowledge and the safety performance factors investigated within the supervisor groups. These findings suggested supervisors may not be interacting with drivers in relation to fleet safety matters, but that other factors associated with work group membership are having an impact on drivers' safety perceptions. In comparison, there was a small amount of variation accounted for by fleet co-ordinator group membership. However, the results suggested the fleet co-ordinator leader attributes accounted for a high percentage of this variation in group membership. Support was found for a positive relationship between fleet co-ordinator safety perceptions, and driver safety perceptions. Other results found fleet co-ordinators were engaging in higher workloads to enhance the safety perceptions, and attitudes towards traffic safety of drivers within their groups.----- Overall, these studies establish a multilevel organisational process of effect, whereby individual and leader attributes, and organisational initiatives all play a role in influencing the safety performance of work-related drivers. The results also indicated an unclear structure in the management of fleet safety, as perceived by drivers, and through the roles and responsibilities of supervisors and fleet co-ordinators. The implications of these results for the management of fleet safety are discussed.

The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. This research project intends to enhance the GDM capabilities. A Fratar model is implemented for the distribution of the forecast demand during each year. The Fratar model uses a 3,974 by 3,974 origin-destination matrix to distribute the demand among 55,612 unique routes in the network. Moreover, the GDM is capable to estimate the aircraft fleet mix per route and the number of flights per aircraft that are needed to satisfy the forecast demand. The model adopts the aircraft fleet mix from the Official Airline Guide data for the year 2015. Once the aircraft types are distributed and flights are assigned, the GDM runs an aircraft retirement and replacement analysis to remove older generation aircraft from the network and replace them with existing or newer aircraft. The GDM continues to evolve worldwide aircraft fleet by introducing 14 new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA. / Master of Science / The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. The previous study done by Alsaous, predicts how many seats will be departing out of the 3,974 airports worldwide. This project intends to use the outputs of the GDM and distribute the seats predicted among the airports. The objective is to predict how many seats will be offered that will be departing from airport “A” and arriving at airport “B”. For this, a Fratar model was implemented. The second objective of this project is to estimate what will the aircraft fleet be in the future and how many flights will be needed to satisfy the predicted air travel demand. If the number of seats going from airport A to airport B is known, then, by analyzing real data it can be estimated what type of aircraft will be flying from airport “A” to airport “B” and how many flights each aircraft will have to perform in order to satisfy the forecasted demand. Besides of estimating the type of aircraft that will be used in the future, the modeled created is capable of introducing new aircraft that are not part of the network yet. Fourteen new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA.

No description available.

As usinas sucroalcooleiras utilizam grandes áreas para o cultivo da cana-de-açúcar, conhecidas como fundos agrícolas. Nesses fundos agrícolas, as atividades são realizadas por uma grande quantidade de máquinas agrícolas diferentes. As necessidades dessas máquinas, como combustível, óleo lubrificante e outras, são supridas pelos comboios de manutenção. Este trabalho visa propor um método para alocação e dimensionamento da frota de comboios de manutenção para o atendimento às máquinas. Para tanto foi utilizado um Sistema de Informações Geográficas aplicado a transportes (SIG-T), denominado comercialmente por TransCAD. Um estudo de caso foi realizado na Usina da· Barra S.A., localizada no município de Barra Bonita, centro oeste do Estado de São Paulo. Diversas simulações de atendimento, com configurações diferentes de distribuição das máquinas, foram realizadas. O atendimento às situações reais de distribuição das máquinas também foi analisado, com o objetivo de confrontar os dados reais de atendimento com os resultados obtidos através da aplicação da metodologia proposta. Foram obtidas as rotas e, conseqüentemente, o número de comboios necessários para o atendimento no período de safra e de entressafra. Com relação à aplicação do TransCAD na roteirização, pode-se constatar uma redução de até 19,6% na distância total percorrida pela frota de comboios no primeiro turno de trabalho em um dos dias analisados. / The sugar-cane industries use large areas for the cultivation of the sugar-cane. In these areas, different agricultural machines carry out several activities. The basic needs of these machines, such as fuel, lubrication and others, are supplied by a fleet of vehicles. The objective of this work is to propose a method to analyze the number of vehicles to compose the fleet already mentioned, based on the application of a Geographical lnformation System (GIS), commercially denominated by TransCAD. A case study was done in the Usina da Barra S.A. company, located at Barra Bonita city, State of São Paulo. Several situations of attendance were simulated with different distribution of machines, based in the initial annual planning of the company. We also analyzed the attendance of real distribution of machines with the objective of comparing the results obtained through the application of the proposed method and the real operation. The routes were obtained and, consequently, the necessary number of vehicles for the attendance. In relation to the application of TransCAD in the routing, a reduction of 19,6% was verified in the total distance traveled by the fleet of vehicles.