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

L'optimisation de l'exploitation d'un réseau de transport de gaz naturel (RTGN) est typiquement un problème d'optimisation multiobjectif, faisant intervenir notamment la minimisation de la consommation énergétique dans les stations de compression, la maximisation du rendement, etc. Cependant, très peu de travaux concernant l'optimisation multiobjectif des réseaux de gazoducs sont présentés dans la littérature. Ainsi, ce travail vise à fournir un cadre général de formulation et de résolution de problèmes d'optimisation multiobjectif liés aux RTGN. Dans la première partie de l'étude, le modèle du RTGN est présenté. Ensuite, diverses techniques d'optimisation multiobjectif appartenant aux deux grandes classes de méthodes par scalarisation, d'une part, et de procédures évolutionnaires, d'autre part, communément utilisées dans de nombreux domaines de l'ingénierie, sont détaillées. Sur la base d'une étude comparative menée sur deux exemples mathématiques et cinq problèmes de génie des procédés (incluant en particulier un RTGN), un algorithme génétique basé sur une variante de NSGA-II, qui surpasse les méthodes de scalarisation, de somme pondérée et d'ε-Contrainte, a été retenu pour résoudre un problème d'optimisation tricritère d'un RTGN. Tout d'abord un problème monocritère relatif à la minimisation de la consommation de fuel dans les stations de compression est résolu. Ensuite un problème bicritère, où la consommation de fuel doit être minimisée et la livraison de gaz aux points terminaux du réseau maximisée, est présenté ; l'ensemble des solutions non dominées est répresenté sur un front de Pareto. Enfin l'impact d'injection d'hydrogène dans le RTGN est analysé en introduisant un troisième critère : le pourcentage d'hydrogène injecté dans le réseau que l'on doit maximiser. Dans les deux cas multiobjectifs, des méthodes génériques d'aide à la décision multicritère sont mises en oeuvre pour déterminer les meilleures solutions parmi toutes celles déployées sur les fronts de Pareto. / The optimization of a natural gas transportation network (NGTN) is typically a multiobjective optimization problem, involving for instance energy consumption minimization at the compressor stations and gas delivery maximization. However, very few works concerning multiobjective optimization of gas pipelines networks are reported in the literature. Thereby, this work aims at providing a general framework of formulation and resolution of multiobjective optimization problems related to NGTN. In the first part of the study, the NGTN model is described. Then, various multiobjective optimization techniques belonging to two main classes, scalarization and evolutionary, commonly used for engineering purposes, are presented. From a comparative study performed on two mathematical examples and on five process engineering problems (including a NGTN), a variant of the multiobjective genetic algorithm NSGA-II outmatches the classical scalararization methods, Weighted-sum and ε-Constraint. So NSGA-II has been selected for performing the triobjective optimization of a NGTN. First, the monobjective problem related to the minimization of the fuel consumption in the compression stations is solved. Then a biojective problem, where the fuel consumption has to be minimized, and the gas mass flow delivery at end-points of the network maximized, is presented. The non dominated solutions are displayed in the form of a Pareto front. Finally, the study of the impact of hydrogen injection in the NGTN is carried out by introducing a third criterion, i.e., the percentage of injected hydrogen to be maximized. In the two multiobjective cases, generic Multiple Choice Decision Making tools are implemented to identify the best solution among the ones displayed of the Pareto fronts.

The major transit systems operating in San Francisco are San Francisco Municipal (MUNI), Bay Area Rapid Transit (BART), and Caltrain. The system of interest for this paper is MUNI, in particular the bus and light rail systems. During the past decade transit ridership in the area has experienced diverging growth, with bus ridership declining while rail ridership is growing significantly (Erhardt et al. 2017). Our data show that between 2009 and 2016, MUNI rail ridership increases from 146,000 to 171,400, while MUNI bus ridership decreases from 520,000 to 450,000. Direct ridership models (DRMs) are used to determine what factors are influencing MUNI light rail and bus ridership. The DRMs predict ridership fairly well, within 10% of the observed change. However, the assumption of no multi-collinearity is voided. Variables, such as employment and housing density, are found to be collinear. Fixed-effects panel models are used to combat the multi-collinearity issue. Fixed-effects panel models assign an intercept to every stop, so that any spatial correlation is removed. A transportation network company, Uber and Lyft, variable is introduced (TNC) to the panel models, to quantify the effect they have on MUNI bus and light rail ridership. The addition of a TNC variable and elimination of multi-collinearity helps the panel models predict ridership better than the daily and time-of-day DRMs, both within 5% of the observed change. TNCs are found to complement MUNI light rail and compete with MUNI buses. TNCs contributed to a 7% growth in light rail ridership and a 10% decline in bus ridership. These findings suggest that the relationship TNCs have with transit is complex and that the modes cannot be lumped together.

The goal of the thesis ``Assessment of Transport Accessibility in the Central Bohemia Region{\crq}q is to analyze the transport situation and transport accessibility.

Dans cette thèse, nous avons étudier une méthode de classification et d'évaluation des modalités de transport utilisées par les porteurs de mobile durant leurs trajets quotidiens. Les informations de mobilité sont collectées par un opérateur au travers des logs du réseau téléphonique mobile qui fournissent des informations sur les stations de base qui ont été utilisées par un mobile durant son trajet. Les signaux (appels/SMS/3G/4G) émis par les téléphones sont une source d'information pertinente pour l'analyse de la mobilité humaine, mais au-delà de ça, ces données représentent surtout un moyen de caractériser les habitudes et les comportements humains. Bien que l'analyse des metadata permette d'acquérir des informations spatio-temporelles à une échelle sans précédent, ces données présentent aussi de nombreuses problématiques à traiter afin d'en extraire une information pertinente. Notre objectif dans cette thèse est de proposer une solution au problème de déduire la trajectoire réelle sur des réseaux de transport à partir d'observations de position obtenues grâce à l'analyse de la signalisation sur les réseaux cellulaires. Nous proposons « CT-Mapper" pour projecter les données de signalisation cellulaires recueillies auprès de smartphone sur le réseau de transport multimodal. Notre algorithme utilise un modèle de Markov caché et les propriétés topologiques des différentes couches de transport. Ensuite, nous proposons « LCT-Mapper » un algorithme qui permet de déduire le mode de transport utilisé. Pour évaluer nos algorithmes, nous avons reconstruit les réseaux de transport de Paris et de la région (Ile-de-France). Puis nous avons collecté un jeu de données de trajectoires réelles recueillies auprès d'un groupe de volontaires pendant une période de 1 mois. Les données de signalisation cellulaire de l'utilisateur ont été fournies par un opérateur français pour évaluer les performances de nos algorithmes à l'aide de données GPS. Pour conclure, nous avons montré dans ce travail qu'il est possible d'en déduire la trajectoire multimodale des utilisateurs d'une manière non supervisée. Notre réalisation permet d'étudier le comportement de mobilité multimodale de personnes et d'explorer et de contrôler le flux de la population sur le réseau de transport multicouche / Around half of the world population is living in cities where different transportation networks are cooperating together to provide some efficient transportation facilities for individuals. To improve the performance of the multimodal transportation network it is crucial to monitor and analyze the multimodal trajectories, however obtaining the multimodal mobility data is not a trivial task. GPS data with fine accuracy, is extremely expensive to collect; Additionally, GPS is not available in tunnels and underground. Recently, thanks to telecommunication advancement cellular dataset such as Call Data Records (CDRs), is a great resource of mobility data, nevertheless, this kind of dataset is noisy and sparse in time. Our objective in this thesis is to propose a solution to this challenging issue of inferring real trajectory and transportation layer from wholly cellular observation. To achieve these objectives, we use Cellular signalization data which is more frequent than CDRs and despite their spatial inaccuracy, they provide a fair source of multimodal trajectory data. We propose 'CT-Mapper’ to map cellular signalization data collected from smart phones over the multimodal transportation network. Our proposed algorithm uses Hidden Markov Model property and topological properties of different transportation layers to model an unsupervised mapping algorithm which maps sparse cellular trajectories on multilayer transportation network. Later on, we propose ‘LCT-Mapper’ an algorithm to infer the main mode of trajectories. The area of study in this research work is Paris and region (Ile-de-France); we have modeled and built the multimodal transportation network database. To evaluate our proposed algorithm, we use real trajectories data sets collected from a group of volunteers for a period of 1 month. The user's cellular signalization data was provided by a french operator to assess the performance of our proposed algorithms using GPS data as ground truth. An extensive set of evaluation has been performed to validate the proposed algorithms. To summarize, we have shown in this work that it is feasible to infer the multimodal trajectory of users in an unsupervised manner. Our achievement makes it possible to investigate the multimodal mobility behavior of people and explore and monitor the population flow over multilayer transportation network

In this paper, a new cyclic structure of a max pressure travel time-based traffic signal control is developed to seek an optimal coordination in large-scale urban networks. The focus of the current paper is on dynamic manipulation of cycle lengths within cyclic structure. Following the application of a decentralized approach, which requires only local information in order to offer proper phase durations, the control strategy aims at maximizing the overall network throughput. Previous works of cyclic max-pressure control have presented a cyclic notion to actuate the controller in a cyclic manner. However, no input has been provided on the optimal cycle length for each intersection to be chosen in a network, and along with the dynamic and stochastic nature of the trips, it is not clear what are the main phases of the intersections and how to coordinate them. The developed cyclic max pressure control schemes are compared with an exiting cyclic scheme in the literature. Simulation results show that the newly proposed cyclic structure of the time-based approach offers better decision-making.

Bakgrund Trafikverket är ansvarig förvaltare över Sveriges järnvägar. De hanterar den långsiktiga infrastrukturen samt byggandet och driften av järnvägarna. För att visualisera och hantera dessa järnvägar digitalt använder sig Trafikverket av ett system kallat Baninformationssystemet (BIS). Järnvägsnätet hanteras på två olika nivåer, makronivå och mikronivå. Makronivån visar driftplatser med dess kopplingar emellan dem och är den enklaste nivån av nätverket. Mikronivån är betydligt mer detaljerad och visar alla objekt och kopplingar som finns på en driftplats. Syfte Målet med studien är att implementera ett transportnätverk i form av en järnväg i en grafdatabas på mikronivå. I studien undersöks metoder för att hantera svängningsrestriktioner på transportnätverket. Utöver detta utför studien en rad kortaste vägen-sökningar för att validera transportnätverket. Metod Studien använder sig av forskningsstrategin design and creation där en IT-artefakt skapas. En litteraturundersökning görs för att finna tidigare forskning som kan hjälpa utvecklingen av IT-artefakten samt besvara forskningsfrågorna. Systematiska observationer utförs för att validera IT-artefakten, i form av kortaste vägen-sökningar som jämförs med samma sökning i Trafikverkets system BIS. Resultat Studien har resulterat i en implementation av ett transportnätverk med svängningsrestriktioner på mikronivå i en grafdatabas. En lösning i Neo4j vid namn Neomap används för visualisering och testning av transportnätverket. Studien presenterar också en jämförelse mellan Trafikverkets system BIS och studiens transportnätverk. Slutsatser Jämförelsen visar att den alternativa graf som föreslagits har implementerats som ett korrekt transportnätverk på mikronivå. Transportnätverket hanterar de flesta av de svängningsrestriktioner som Trafikverket använder då den använda data var begränsad. Neomap användes för både felsökning och validering av transportnätverket och visar att sökningarna från Neo4j är nästan identiska med BIS. / Background The Swedish Transport Administration is the responsible manager of Sweden’s railways. They handle the long-term infrastructure as well as the construction and operation of the railways. To visualize and manage these railways digitally, the Swedish Transport Administration uses a system called Baninformationssystemet (BIS). The railway network is managed at two different levels, macro-level and micro-level. The macro-level only shows operating sites with their connections between them and is the simplest level of the network. The micro-level is significantly more detailed showing all objects and connections located at an operating site. Aim The aim of the study is to implement a transportation network in the form of a railway in a graph database at micro-level. The study examines methods for managing turning restrictions on the transportation network. In addition, the study performs a series of shortest path searches to validate the transportation network. Method The study uses the research strategy design and creation where an IT artifact is created. A literature review is done to find previous research that can help the development of the IT artifact and answer the research questions. Systematic observations are performed to validate the IT artifact by doing various shortest road searches that are compared with the same searches in the Swedish Transport Administration’s system. Results The study has resulted in the implementation of a transportation network with turning restrictions on a micro-level in a graph database. A solution in Neo4j called Neomap is used for visualization and testing of the transportation network. A comparison is presented where the study’s transportation network was compared with the Swedish Transport Administration’s system BIS. Conclusions The comparison shows that the alternative graph proposed has been implemented as a correct transportation network on a micro-level. The transportation network handles most of the turning restrictions that Trafikverket uses due to limited data. Neomap is used for both troubleshooting and validation of the transportation network and shows that the searches from Neo4j are almost identical to the searches from BIS.

Dans cette thèse, nous questionnons l’impact du terrorisme international et des mesures de sûreté sur le comportement des usagers du réseau de transport aérien mondial. A l’aide d’un modèle économétrique, nous analysons une base de données inédite, AirNetTerror, composée de l’ensemble des vols internationaux à destination des Etats-Unis de 1990 à 2006, et des données du terrorisme international par pays sur cette période. La pertinence de notre travail est double. D’une part, nos interrogations sur les comportements des voyageurs et leurs éventuelles substitutions d’itinéraires en lien avec le terrorisme international n’ont, à notre connaissance, jamais été traitées. D’autre part, en abordant le transport aérien sous l’angle du réseau, nous proposons une vision dynamique des répercussions des comportements des usagers en lien avec la menace terroriste et les mesures de sûreté. En particulier, la prise en compte de la situation de sûreté interdépendante régissant le réseau aérien mondial nous permet de questionner l’existence de failles dans les mesures de sûreté. Nos résultats soulignent l’impact avéré et significatif des événements du terrorisme international, mais aussi des mesures de sûreté sur le réseau de transport aérien mondial. De plus, nous observons localement des substitutions d’itinéraires des voyageurs aériens en lien avec ces phénomènes. Ainsi, l’effet combiné de la menace terroriste internationale et des mesures de sûreté semble être à l’origine de ruptures d’équilibre, certes limitées mais réelles, des flux de passagers du réseau de transport aérien mondial. Notre thèse, parce qu’elle place le comportement du voyageur au centre des interactions stratégiques entre les acteurs de la sûreté et les terroristes, permet d’apporter une vision inédite de l’impact du terrorisme international sur le transport aérien. / In our dissertation, we question the impact of both international terrorism and security measures on the behavior of the users of the global air transportation network. Using an econometric model, we analyze a new database, AirNetTerror, which contains data on all international passenger flows toward the U.S. from 1990 to 2006 as well as the events of international terrorism by country for the same period. The relevance of our research is twofold. On the one hand, our investigation regarding air travelers’ behavior and their possibilities of modifying their itinerary in light of international terrorism has – so far as we know – never been studied. On the other hand, as we analyze passenger flows from the perspective of the network, we propose a dynamic representation of the impact of travelers’ behavior changes related to terrorist threats and security measures. In particular, taking into account the interdependent security that rules the global air transport network, allows us to question the existence of failures in security measures. Our results underline a significant impact of both international terrorist events and security measures. Furthermore, we locally observe itinerary modifications of travelers that are linked to the previous phenomena. Thus, the combined effect of terrorist threats and security measures seems to lead to equilibrium breaks – that are limited but real – in passenger flows of the global air network. Our thesis offers a different representation of the impact of international terrorism on air transport by placing the traveler’s behavior at the center of the strategic interactions between security actors and terrorists.

I examine whether Uber and Lyft are currently complements or substitutes of public transit, and how partnerships between cities and ride sharing companies can increase their complementary relationship and solve parking and mobility issues. The results suggest that transportation network companies (TNCs) like Uber and Lyft do not have a statistically significant effect on public transit ridership overall, but are complements of public transit for certain populations. Policies that give discounts for TNC rides taken to and from transit stops help solve the first mile / last mile problem, which consequently help increase transit ridership.

Tato disertační práce se zabývá vývojem, modelováním a analýzou poptávkově orientovaných úloh, které zahrnují marketingová, operační a logistická rozhodnutí. Úlohy jsou zvoleny tak, aby mohly být dále rozšířeny o koncept tzv. dynamického oceňování a jiných dynamických marketingových rozhodnutí. V práci jsou využity dvě základní poptávkově orientované úlohy: a) úloha kolportéra novin, která je zvolena pro její jednoduchou formu a která tak slouží jako nástroj pro ilustrativní ukázky rozhodovacích procesů v podobných typech úloh, a b) úloha návrhu dopravní sítě, kde jsou využity některé výsledky a znalosti získané při řešení úlohy kolportéra novin. Kolportér (či obecně maloobchodník) čelí náhodné poptávce, která může být postupně ovlivněna oceňováním, marketingovými (tj. reklamními) rozhodnutími a nakonec jejich kombinací. Poptávka obsahuje tedy náhodnou složku, která je pomocí přístupů stochastické optimalizace modelována ve specifickém tvaru (tj. aditivní či multiplikativní tvar). Závislost cena-poptávka je zachycena pomocí nelineární klesající poptávkové funkce, zatímco (vhodná) reklama vede ke zvýšení poptávky (běžně rostoucí s-křivka či konkávní funkce). Výsledky získané při řešení úlohy kolportéra novin s oceňováním jsou následně využity v úloze návrhu dopravní sítě. Tato stochastická úloha je modelována (reformulována) pomocí dvou přístupů stochastické optimalizace: wait-and-see přístup a here-and-now přístup. Jelikož tato implementace vede na lineární či nelineární celočíselnou (navíc scénářovou) úlohu, jsou v práci zmíněny taky výpočetní nástroje. Autor pro řešení používá (původní) tzv. hybridní algoritmus, což je kombinace heuristického (genetického) algoritmu a nástroje optimalizačního softwaru. Potenciální aplikace sestavených modelů, obzvláště v oblasti odpadového hospodářství, jsou diskutovány v závěrečné části disertační práce.