This dissertation formulates and develops models and solution approaches for plug-in electric vehicle (PEV) charging station installation. The models are formulated in the form of bilevel programming and stochastic programming problems, while a meta-heuristic method, genetic algorithm, and Monte Carlo bounding techniques are used to solve the problems. Demand for PEVs is increasing with the growing concerns about environment pollution, energy resources, and the economy. However, battery capacity in PEVs is still limited and represents one of the key barriers to a more widespread adoption of PEVs. It is expected that drivers who have long-distance commutes hesitate to replace their internal combustion engine vehicles with PEVs due to range anxiety. To address this concern, PEV infrastructure can be developed to provide re-fully status when they are needed. This dissertation is primarily focused on the development of mathematical models that can be used to support decisions regarding a charging station location and installation problem. The major parts of developing the models included identification of the problem, development of mathematical models in the form of bilevel and stochastic programming problems, and development of a solution approach using a meta-heuristic method. PEV parking building problem was formulated as a bilevel programming problem in order to consider interaction between transportation flow and a manager decisions, while the charging station installation problem was formulated as a stochastic programming problem in order to consider uncertainty in parameters. In order to find the best-quality solution, a genetic algorithm method was used because the formulation problems are NP-hard. In addition, the Monte Carlo bounding method was used to solve the stochastic program with continuous distributions. Managerial implications and recommendations for PEV parking building developers and managers were suggested in terms of sensitivity analysis. First, in the planning stage, the developer of the PEV parking building should consider long-term changes in future traffic flow and locate a PEV parking building closer to the node with the highest destination trip rate. Second, to attract more parking users, the operator needs to consider the walkability of walking links.

This study investigates the relevance of dynamic traffic assignment models under uncertainty. In the last years researchers have dealt with advanced traffic control systems since road provision is not regarded as a proper solution to relieve congestion. Dynamic assignment which is an essential component of investment planning is regarded as a new research area in the field of urban transportation. In this study the performance of dynamic traffic assignment method, which incorporates time dependent flow, is compared with that of static model. Research outcomes showed that dynamic assignment method provides more reliable outcomes in predicting traffic flow / therefore its solution algorithm is integrated to conventional four staged model. Literature survey showed that researches have hot provided an appropriate framework for transforming networks. This study investigates travel demand variations in a dynamic city and discuses possible strategies to respond dynamic and uncertain properties of individuals&rsquo / travel behavior. Research findings showed that both external and internal uncertainties have significant influences on reliability of the model. Recommended procedure aims reducing uncertainty in order to improve reliability of model. Finally, the relevancy of the problem and the applicability of recently developed methods are discussed in Ankara case.

[pt] Nesta tese é desenvolvido o conceito e implementado computacionalmente um modelo para resolver o problema de alocação de equilíbrio de passageiros em uma rede de grande porte de transporte coletivo urbano com congestionamento. É considerado o primeiro princípio de ardrop, ou ótimo do usuário e utilizado um modelo de equilíbrio estático com demanda fixa. O fluxo de equilíbrio pode ser achado resolvendo um problema de minimização com uma função objetivo não linear e um conjunto de restrições lineares. É utilizada uma adaptação do algoritmo de Frank-Wolfe, o qual resulta eficiente para resolver problemas estocásticos de transporte e um modelo logit de alocação. E feita uma aplicação à rede da Região Metropolitana do Rio de Janeiro. / [en] The concept of a model that solves the transit equilibrium assignment problem for large scale transit networks and a computational system are developed. The First Principle of Equilibrium of Wardrop, also known as equilibrium user optimum, is applied in this work. A model with static equilibrium and fixed demand is considered. The equilibrium flow can be attained by solving a non- linear minimization problem that includes objective function non-linear and linear constraints. An adaptation of Frank-Wolfe algorithm (efficient to solve transportation stochastic problems) and a logit assignment model are used to solve the problem. This metodology is applied to a network of the Metropolitan Region of Rio de Janeiro. / [es] En esta tesis se desarrolla un modelo para resolver el problema de colocación de equilibrio de pasajeros en una red de gran porte de transporte colectivo urbano con congestionamiento. Se considera el primer principio de Ardrop, el óptimo del usuario y se utiliza un modelo de equilibrio estático con demanda fija. El flujo de equilibrio se encuentra a través de un problema de minimización con una función objetivo no lineal y un conjunto de restricciones lineales. Se utiliza una adaptación del algoritmo de Frank-Wolfe, que se muestra eficiente en la resolución de problemas estocásticos de transporte y un modelo logit de colocación. Finalmente se muestra una aplicación a la red de la Región Metropolitana del Rio de Janeiro.

<p>Beam-powered aircraft are a promising solution to reducing the air transportation system's operating costs and emissions due to their reliance on typically more efficient ground-based electricity sources.</p> <p>However, modeling these aircraft is a non-trivial task due to their multi-disciplinary nature and the required interconnectedness between the aircraft, air transportation network, and power-beaming models.</p> <p><br></p> <p>This thesis establishes a methodology for holistically modeling beam-powered aircraft as a freight transportation asset in the context of their operating environment.</p> <p>This methodology accounts for elements of aircraft conceptual design, the limits of power-beaming technology, and non-idealities associated with the air transportation network.</p> <p>As a product of this methodology, this thesis also approximates beam-powered aircraft's economic and environmental feasibility based on current and future technological capabilities.</p> <p><br></p> <p>This work concludes that with an optimistic enough "engine absent" mass fraction and with sufficiently advanced technologies -- particularly with higher power density rectennas -- beam-powered aircraft are both economically and environmentally feasible, having a lower operating cost and emitting less carbon dioxide per ton-mile compared to current-day and near-future freight transportation aircraft.</p> <p><br></p> <p>More specifically, this work concludes that when using a simplified and more optimistic engine absent mass fraction model, power train specific power only needs to improve by a factor of 1.2-3.7 and rectenna power density only needs to improve by a factor of 20-30 compared to the baseline technologies considered in this work in order for beam-powered aircraft to be a feasible alternative to jet fuel powered aircraft in a freight transportation role.</p> <p>However, with a more pessimistic albeit more realistic engine absent mass fraction model, this work concludes that beam-powered aircraft are not feasible in a freight transportation role with the technology levels considered in this work.</p>

Cette thèse propose une modélisation des interactions entre le Transport de Marchandises en Ville (TMV) et la dynamique du trafic. Ces deux composantes, pourtant imbriquées, ne sont que très rarement étudiées simultanément. Plus précisément, cette thèse investigue les impacts du TMV sur les états de trafic ; et inversement, les impacts des états de trafic sur le TMV. Les recherches s’articulent autour de deux axes : le TMV à l’échelle (i) de la livraison et (ii) de la tournée de livraison, et la dynamique du trafic à l’échelle (iii) d’un jour et (iv) d’un catalogue de jours. (i) Le TMV réalisé par des véhicules routiers peut engendrer des formes de congestion, et par conséquent des nuisances sonores et atmosphériques. Néanmoins, il s’agit d’un « mal nécessaire » car le transport de ces marchandises est essentiel pour l’économie des villes. Une pratique courante est la livraison en double file. Ces « stationnements sauvages » réduisent l’écoulement des véhicules dans le réseau de transport. Une étude de sensibilité quantitative en simulation microscopique met en lumière une dégradation significative des états de trafic sur un boulevard urbain à partir d’un faible nombre de stationnements en double file. Ces phénomènes locaux et temporaires semblent essentiels à intégrer dans les simulations du trafic afin d’étudier au mieux les performances globales du système de transport. (ii) Les tournées de livraison planifiées peuvent être améliorées par l’intégration des conditions de circulation. Les algorithmes existants d’optimisation de tournées se basent sur une certaine qualité et quantité de données. Nous investiguons l’influence de plusieurs niveaux de granularité d’information du trafic sur l’ordonnancement optimale des tournées. De plus, nous comparons les temps de parcours estimés par les algorithmes, et les temps de parcours effectifs estimés à l’aide d’une simulation microscopique. Les états de trafic attendus peuvent être sujets à quelques variations. Nous proposons une méthodologie de génération de tournées intégrant de l’incertitude dans la dynamique du trafic. (iii) À l’échelle de la ville, les états de trafic sont naturellement variables, que ce soit dans l’espace ou au cours du temps. Le partitionnement permet de découper un réseau de transport en zones homogènes. Une zone est définie par un ensemble de liens connectés ayant des conditions de circulation similaires. Nous proposons une approche spatio-temporelle définissant des zones en 3 Dimensions (3D). L’idée est de résumer la majeure partie de la dynamique du trafic d’une ville en utilisant peu d’information : la vitesse moyenne par zone spatio-temporelle. Deux familles de méthodes de clustering fondamentalement différentes sont comparées et évaluées. Le cas d’étude est le réseau d’Amsterdam avec des données réelles. (iv) D’un jour à l’autre, la dynamique du trafic peut être similaire. Nous proposons une méthodologie regroupant les jours par leurs motifs de congestion. L’existence d’une régularité dans les motifs journaliers est introduite par la notion de jour-type. Un jour-type est le jour de référence d’un groupe de jours. Nous validons notre modèle en comparant les temps de parcours effectifs et les temps de parcours estimés par les jours-types. Diverses applications peuvent être raffinées à partir de quelques jours-types, comme l’assistance routière et la génération de tournées. / This thesis aims to modeling the interactions between the urban freight and the traffic dynamic. Although both are intertwined, they have rarely been studied considering a combined approach. Specifically, the main purpose is to analyze the impacts of the urban freight on traffic states, and vice versa. This research is focused on two axes: the urban freight considering (i) the delivery and (ii) the delivery route scales, and two traffic dynamic scales describing (iii) a day and (iv) a set of days. (i) The delivery of goods carried by vehicles can produce traffic congestion, noise and air pollution. Nevertheless, the transport of goods is essential for the economy of cities. The double parking is a common way for delivery trucks. This illegal parking reduces the vehicle capacity of the transportation network. A sensitivity analysis in traffic microscopic simulation model for urban freight highlight a significant decreasing of the traffic conditions on an urban corridor considering a low number of double parking. These local and temporal phenomena are essential to be integrated into the traffic simulation in order to better study the overall performance of the transportation system. (ii) The delivery route planner can be improved by integrating traffic conditions. The route optimization algorithms are based on quality and quantity of given data available. We investigate the influence of several levels of granularity on traffic information data for the optimal route scheduling. Moreover, the travel time estimated by algorithms and the effective travel time estimated by a microscopic simulation are compared. In addition, the expected traffic conditions can be subject to variations. We propose a methodology of delivery route planner integrating the uncertainty of the traffic dynamics. (iii) At the city level, the traffic conditions are varied through space and time. A partitioning of urban transportation networks makes possible to identify homogeneous zones. A zone is defined by a set of connected links with similar traffic conditions. We proposed a spatial and temporal approach to define the 3D zones. The idea is to summarize the majority of the traffic dynamics of a given city using only a few information: the mean speed per spatial and temporal zone. Two fundamentally different methods of clustering are compared and evaluated. The study case is the Amsterdam network with its real-world traffic data. (iv) From day to day, the traffic dynamic can be similar. We proposed a methodology grouping days by their similar congestion patterns. The existence of a regularity through daily patterns are introduced by consensual speed map. A consensual speed map is the reference day representing a group of days. Our model is validated by using the effective travel time and estimated ones by the consensual speed maps. Numerous applications can be refined from a couple of consensual speed maps, as the route guidance and delivery route planning.

Sustainable transportation aims encouragement of non-motorized (pedestrian and bicyclist) and shared-ride transportation modes instead of car-dependent travels. This is important for university campuses, as they have better chance to implement such policies in a rather controlled traffic network, and can set an example to other communities. Most of sustainable campus transportation programs boil down to reduction of car-based emission cost of campus mobility, which is always the first step in developing more sustainable transportation policies. Middle East Technical University (METU), Ankara has a large campus area and a population over 30,000 people. To develop sustainable campus transportation policies, it was important to quantify the current levels of mobility and vehicle emissions within the campus, which was the main motivation behind this study. This required determination of i) campus origin-destination matrix, ii) in-campus vehicle-km-travelled (vehicle-km), and iii) carbon emissions. Travel data obtained from different sources, including the gate entry with RFID systems enabled analysis of different user groups, such as academic and administrative personnel and students, separately. The traffic simulations were prepared in PTV VISUM, which provided both speed and vehicle-km values for road segments, and could represent multi-user group demand matrices in a single traffic assignment. Based on the base case mobility and emission values, more sustainable campus transportation policies were simulated in PTV VISUM, and assessed in terms of carbon emission impacts. Discouraging of private car usage by students seemed the first and simplest action.

For many years, research on user acceptance of different technologies has been one of the most important topics within the field of information systems. In markets with the sheer size and uniqueness of the Chinese mobile economy fostered rapid development of sharing economy firms. Transportation Network Companies (TNC) can be regarded as a context of the sharing economy that focuses on personal transportation. Intrigued by the immense success of TNC and notorious competition between TNC companies Uber and DiDi in China, we study why users are susceptible to TNC. In this study, user acceptance is defined as intention to use TNC and the actual use of TNC. This study aims to examine what factors affect user acceptance of TNC in China and to what extent. By this, the thesis aims to provide TNC with adequate recommendations for success. The state of the art user acceptance model UTAUT2 has been used in this research with an explanatory purpose and a deductive approach. The UTAUT2 model consists of factors related to user acceptance, such as Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value and Habit. These factors were individually tested with Simple Linear Regression to determine their influence on user acceptance. These calculations were executed upon quantitative data from an electronically distributed survey. Upon analysis of the findings, research and practical implications are provided such as managerial recommendations for how TNC can raise user acceptance and increase market share.

De nombreux systèmes de transport peuvent être modélisées par des synchronisations ordinaires (pour tout k>=l, l'occurrence k de l'événement B se produit au moins t unités de temps après l'occurrence k-l de l'événement A). Ces systèmes sont linéaires dans l'algèbre (max,+). Pour certaines applications, il est primordial de modéliser la simultanéité entre événements. Comme la synchronisation ordinaire ne suffit pas à exprimer ce phénomène, nous introduisons la synchronisation partielle (l'événement B ne peut se produire que quand l'événement A se produit). Dans ce mémoire, des méthodes développées pour la modélisation et le contrôle de systèmes linéaires dans l'algèbre (max,+) sont étendues à des systèmes régis par des synchronisations ordinaires et partielles. Nous considérons uniquement des systèmes divisés en un système principal et un système secondaire et gouvernés par des synchronisations ordinaires entre événements dans le même système et des synchronisations partielles d'événements dans le système secondaire par des événements dans le système principal. Nous introduisons une commande optimale et une commande prédictive pour cette classe de systèmes par analogie avec les résultats disponibles pour les systèmes linéaires dans l'algèbre (max,+). En considérant un comportement donné pour le système principal, il est aussi possible de représenter le système secondaire par une fonction de transfert et de modifier sa dynamique pour suivre un modèle de référence. / Many transportation networks can be modeled by (max,+)-linear systems, i.e., discrete event systems ruled by standard synchronizations (conditions of the form: "for all k>=l, occurrence k of event B is at least t units of time after occurrence k-l of event A"). In some applications, it is also necessary to model simultaneity between events (e.g., for a road equipped with traffic lights, a vehicle can cross an intersection only when the associated traffic light is green). Such conditions cannot be expressed using standard synchronizations. Hence, we introduce the partial synchronization (condition of the form: "event B can only occur when event A occurs"). In this thesis, we consider a class of discrete event systems ruled by standard and partial synchronizations, called (max,+)-systems with partial synchronization. Such systems are split into a main system and a secondary system such that there exist only standard synchronizations between events in the same system and partial synchronizations of events in the secondary system by events in the main system. We adapt some modeling and control approaches developed for (max,+)-linear systems to (max,+)-systems with partial synchronization. Optimal feedforward control and model predictive control for (max,+)-linear systems are extended to (max,+)-systems with partial synchronization. Furthermore, transfer relation and model reference control are provided for the secondary system under a predefined behavior of the main system.

The aim of this master thesis is to analyze the present condition of sharing economy and design a critical success factors model on a IT startups which operate as a transportation network companies. The result is finally validated on few representative businesses. The problem is solved by the modified qualitative critical success factors method whose author is John F. Rockart. The gained factors were finally used in the causal model which is based on the principles of system dynamics. The outcomes of this thesis are enabling to understand the relations which are hidden behind success of transportation network companies in the area of sharing economy. The information can be useful not only for startups but also for academic sphere and possible investors.

Dynamic Traffic Assignment (DTA) is gaining wider acceptance among agencies and practitioners because it serves as a more realistic representation of real-world traffic phenomena than static traffic assignment. Many metropolitan planning organizations and transportation departments are beginning to utilize DTA to predict traffic flows within their networks when conducting traffic analysis or evaluating management measures. To analyze DTA-based optimization applications, it is critical to obtain the dual (or gradient) information as dual information can typically be employed as a search direction in algorithmic design. However, very limited number of approaches can be used to estimate network-wide dual information while maintaining the potential to scale. This dissertation investigates the theoretical/practical aspects of DTA-based dual approximation techniques and explores DTA applications in the context of various transportation models, such as transportation network design, off-line DTA capacity calibration and dynamic congestion pricing. Each of the later entities is formulated as bi-level programs. Transportation Network Design Problem (NDP) aims to determine the optimal network expansion policy under a given budget constraint. NDP is bi-level by nature and can be considered a static case of a Stackelberg game, in which transportation planners (leaders) attempt to optimize the overall transportation system while road users (followers) attempt to achieve their own maximal benefit. The first part of this dissertation attempts to study NDP by combining a decomposition-based algorithmic structure with dual variable approximation techniques derived from linear programming theory. One of the critical elements in considering any real-time traffic management strategy requires assessing network traffic dynamics. Traffic is inherently dynamic, since it features congestion patterns that evolve over time and queues that form and dissipate over a planning horizon. It is therefore imperative to calibrate the DTA model such that it can accurately reproduce field observations and avoid erroneous flow predictions when evaluating traffic management strategies. Satisfactory calibration of the DTA model is an onerous task due to the large number of variables that can be modified and the intensive computational resources required. In this dissertation, the off-line DTA capacity calibration problem is studied in an attempt to devise a systematic approach for effective model calibration. Congestion pricing has increasingly been seen as a powerful tool for both managing congestion and generating revenue for infrastructure maintenance and sustainable development. By carefully levying tolls on roadways, a more efficient and optimal network flow pattern can be generated. Furthermore, congestion pricing acts as an effective travel demand management strategy that reduces peak period vehicle trips by encouraging people to shift to more efficient modes such as transit. Recently, with the increase in the number of highway Build-Operate-Transfer (B-O-T) projects, tolling has been interpreted as an effective way to generate revenue to offset the construction and maintenance costs of infrastructure. To maximize the benefits of congestion pricing, a careful analysis based on dynamic traffic conditions has to be conducted before determining tolls, since sub-optimal tolls can significantly worsen the system performance. Combining a network-wide time-varying toll analysis together with an efficient solution-building approach will be one of the main contributions of this dissertation. The problems mentioned above are typically framed as bi-level programs, which pose considerable challenges in theory and as well as in application. Due to the non-convex solution space and inherent NP-complete complexity, a majority of recent research efforts have focused on tackling bi-level programs using meta-heuristics. These approaches allow for the efficient exploration of complex solution spaces and the identification of potential global optima. Accordingly, this dissertation also attempts to present and compare several meta-heuristics through extensive numerical experiments to determine the most effective and efficient meta-heuristic, as a means of better investigating realistic network scenarios. / text