Dynamic traffic assignment (DTA) can be used to model impacts of network modification scenarios, including traffic control plans (TCPs), on traffic flow. However, using DTA for modeling construction project impacts is limited by the computational time required to simulate entire roadway networks. DTA modeling of a portion of the larger network surrounding these work zones can decrease the overall run time. However, impacts are likely to extend beyond typical boundaries, and determining the proper extents to be analyzed is necessary. Therefore, a methodology for selecting an adequate portion to analyze using DTA, along with provision for properly analyzing the resultant subnetwork, is necessary to determine the magnitude of construction impacts. The primary objectives of this research center on evaluating subnetwork sizes to determine the appropriate extents required to analyze network modifications and developing a strategy to account for impacts extending beyond the subnetwork boundary. The first objective is accomplished through an in-depth review of subnetwork sizes relative to multiple impact scenarios. Three statistical measures are implemented to evaluate the adequacy of a chosen subnetwork relative to the derived impact scenarios based on an assessment of boundary demand. Ultimately, the root mean squared error is used successfully to provide a series of recommended subnetwork sizes associated with an array of possible impact scenarios. These recommendations are validated, and application of the proposed methodology demonstrated, using five scenarios selected from real-world network modifications observed in the field. When a subnetwork is not large enough and impacts to inbound trips pass beyond the boundary, there is a change in flow at this location that can be represented by a change in the demand assigned to the subnetwork at each entry point. As such, two strategies for adjusting the demand at subnetwork boundaries are implemented and evaluated. This includes use of results from static traffic assignment (STA) models to identify where flow changes occur, and implementation of a logit formulation to estimate demand adjustments based on differences in internal travel times between base and impact scenario models. Based on preliminary results, the logit method was selected for large-scale implementation and testing. In the end, an inconsistent performance of the logit method for full implementation highlights the limitations of the methodology as applied for this study. However, the results suggest that a refined strategy that builds on the foundation established could work more effectively and produce valuable subnetwork demand estimates in the future. This research is used to provide recommendations for selecting and analyzing subnetworks using DTA for an array of common impact scenarios involving network modifications. The tradeoffs between improved efficiency and reduced accuracy associated with using subnetworks are thoroughly demonstrated. It is shown that a considerable amount of computational time and space, as well as effort on the part of an analyst, can be saved. A number of limitations associated with subnetworks are also identified and discussed. The proposed methodology is implemented and evaluated using several software programs and as a result, a number of useful tools and software scripts are developed as part of the research. Ultimately, the valuable experience gained from performing an extensive review of subnetwork analysis using DTA can be used as a basis from which to develop future research initiatives. / text

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

O presente trabalho aborda a temática da modelagem de redes de transporte para terminais multialocados e capacitados de carga parcelada através de métodos quantitativos aplicados em Pesquisa Operacional, onde o objetivo principal é minimizar o custo total, além de determinar a configuração ótima da rede, levandos e em consideração os custos de transporte ponto a ponto, a capacidade de processamento de carga dos hubs e os custos de alocação dos mesmos. Uma rede Hub and Spoke é configurada de forma que as estações geradoras de cargas (spoke) se comunicam única e exclusivamente com os terminais consolidadores (hubs) que, por sua vez, direcionam as cargas para as estações destino. Esta operação de consolidação gera economia de escala e é o princípio utilizado em muitos modelos de localização de redes de transporte de carga. Os modelos matemáticos utilizados para a resolução pertencem à família dos problemas de localização com custos fixos e particularmente será utilizado o método CMAHLP (Capacitated Multiple Allocation Hub Location Problem), onde para a sua resolução será utilizado o software AIMMS (Advanced Integrated Multidimensional Modeling Software) como ferramenta de apoio. / This paper addresses the issue of modeling transportation networks for multi allocated and capacitated terminals for parcel cargos through quantitative methods applied in Operational Research, where the main objective is to minimize the total cost and to determine the optimal configuration of the network, taking into account the transportation costs, the loading capacity of the hubs and the cost of allocation thereof. A Hub and Spoke network is configured in a way that the generating stations (spokes) communicate solely with consolidators terminals (hubs) which dispatch the cargo to the destination stations. This consolidation operation generates economies of scale and it is the principle used in many models of location problems. The mathematical models used for the settlement belongs to the family of location problems with fixed costs and particularly the CMAHLP (Capacitated Multiple Allocation Hub Location Problem) method is used with the AIMMS (Advanced Integrated Multidimensional Modeling Software) software, which will be used will be used as a support tool.

No description available.

The emergence and rapid growth of Transportation Network Companies (TNCs), such as Uber and Lyft, has challenged the transportation industry by offering a new mode of transportation to consumers. It is imperative that transit agencies and cities understand the effect of TNCs on public transit usage to make informed decisions. This study analyzes the impact of TNCs on Bay Area Rapid Transit (BART) ridership at the San Francisco International Airport (SFO) to measure the effect of TNCs on public transit. Using a fixed effects model to analyze hourly BART and TNC ridership data from 2011 to 2018, these findings suggest that TNCs are a substitute to BART. Before the entrance of TNCs, BART ridership at the BART SFO station increases. However, with the presence of TNCs, BART ridership at the SFO station decreases. Further research will proxy for transportation demand using hourly air traffic data at SFO and an instrumental variable for TNC supply to reduce endogeneity.

This research investigates whether Transportation Network Companies (TNCs), such as Uber and Lyft, live up to their stated vision of reducing congestion by complementing transit and reducing car ownership in major cities. The objective of this research study is to answer the question: are TNCs are correlated to traffic congestion in the city of San Francisco? If found to be so, do they increase or decrease traffic congestion for the case of San Francisco? If and how TNC pickups and drop-offs impact traffic congestion within San Francisco? And finally, how does the magnitude of this measured command of TNCs on congestion compare to that caused by pre-existing conventional drivers of traffic and congestion change? Apart from answering these questions, it is also sought to establish a framework to be able to include TNCs, a seemingly fledgling mode of transportation but one that is demonstrably shaping and modifying extant transportation and mode choice trends, as part of the travel demand models estimated by any geographic jurisdiction. Traffic congestion has worsened noticeably in San Francisco and other major cities over the past few years. Part of this change could reasonably be explained by strong economic growth or other standard factors such as road and transit network changes. The sharp increase in travel times and congestion also corresponds to the emergence of TNCs, raising the question of whether the two trends may be related. Existing research has produced conflicting results and been hampered by a lack of data. Using data scraped from the Application Programming Interfaces (APIs) of two TNCs, combined with observed travel time data, this research finds that contrary to their vision, TNCs are the biggest contributor to growing traffic congestion in San Francisco. Between 2010 and 2016, weekday vehicle hours of delay increased by 62%, compared to 22% in a counterfactual 2016 scenario without TNCs. The findings provide insight into expected changes in major cities as TNCs continue to grow, informing decisions about how to integrate TNCs into the existing transportation system. This research also decomposes the contributors to increased congestion in San Francisco between 2010 and 2016, considering contributions from five incremental effects: road and transit network changes, population growth, employment growth, TNC volumes, and the effect of TNC pick-ups and Drop-offs. It is so done through a series of controlled travel demand model runs, supplemented with observed TNC data. The results show that road and transit network changes over this period have only a small effect on congestion, population and employment growth are important contributors, and that TNCs are the biggest contributor to growing congestion over this period, contributing about half of the increase in vehicle hours of delay, and adding to worsening travel time reliability. This research contradicts several studies that suggest TNCs may reduce congestion and adds evidence in support of a recent empirical analysis showing that their net effect is to increase congestion. This research gives transportation planners a better understanding of the causes of growing congestion, allowing them to more effectively craft strategies to mitigate or adapt to it.

L’amélioration de la fluidité du trafic aux intersections a reçu une attention particulière depuis près d’un siècle. Avec la perspective de véhicules contrôlés et communicants, la régulation aux intersections connaît un nouvel essor. Dans cette thèse nous nous intéressons à la régulation coopérative des intersections par la synchronisation des vitesses. Afin d’éviter des arrêts inutiles aux intersections, les véhicules régulent leur vitesse en fonction non seulement des véhicules qui les devancent sur la même voie mais aussi des véhicules prioritaires provenant des autres voies en conflit. La synchronisation des vitesses grâce à la communication sans-fil a plusieurs avantages mais pour les exploiter pleinement, il est nécessaire d’aborder les problématiques des commandes longitudinale et latérale des véhicules. En ce qui ce concerne la commande longitudinale, la thèse s’intéresse à deux problématiques. Pour des raisons évidentes de sécurité, les délais de communication sans-fil avec les véhicules des autres voies, à savoir hors de la portée des capteurs, doivent être pris en compte. Pour ce faire, la commande longitudinale adoptée est une fonction non linéaire qui considère un temps maximal de communication et une borne de décélération. Si les contraintes ne sont pas respectées, la fonction déclenche l’arrêt du véhicule. Etant donné que les résultats de simulations sont concluants dans des cas extrêmes, la thèse aborde la problématique de fluidité du trafic à base de la commande proposée. En effet, le comportement du trafic dépend du choix du lieu où commence la synchronisation des vitesses. La thèse discute les deux approches classiques et propose une solution intermédiaire. Sur un circuit sous la forme d’un huit, l’approche proposée permet de réduire considérablement le recours au freinage contrairement aux deux autres approches actuelles. En ce qui concerne la commande latérale, l’intersection pose deux problèmes. Le premier est la limite du champ de vision à cause des courbures serrées des mouvements tournant et la deuxième est le délai du traitement par les caméras. Dans ce sens, la thèse propose une commande basée sur le calcul de la courbure de Frenet couplé à la correction des écarts. Le suivi des courbures et la correction sont tous les deux déduit à partir du mouvement circulaire induit par l’angle du volant. Les avantages de cette approche par rapport aux approches classiques (LQRwFF et Stanley) est d’une part, de ne pas être gourmande en termes de champs de vision nécessaire et d’autre part d’avoir des contraintes temps-réels plus souples que les approches de la littérature. La comparaison avec les techniques actuelles démontrent que notre approche, dans des conditions de circulation urbaine est capable de résister à des temps d’échantillonnage plus longs contrairement aux deux autres avec une visibilité plus faible. / In this thesis, we are interested in the cooperative intersection management by synchronizing the velocities of conflict vehicles. Thanks to the wireless communication, the synchronization of velocities has several advantages. But, for the purpose of full exploiting them, it is necessary to address at first the problems of the longitudinal and lateral control of vehicles. For the longitudinal control, the delay of wireless communication with the vehicles on other routes must be taken into account. The adopted longitudinal control is non-linear function that considers a maximum communication time and a deceleration boundary.The simulation results in extreme cases have concluded that the thesis addresses the problem of traffic fluidity. Indeed, the behavior of the traffic flow depends on the choice of the place where the synchronization of the speeds begins. The thesis discusses the two classical approaches and proposes a smoothing solution that significantly reduces the use of braking contrary to the two existing approaches. For the lateral control of vehicle at intersection, the thesis proposes a control based on the calculation of Frenet curvature coupled with correction of deviation from tracking path. Both the curve tracking and the correction are deduced from the circular motion induced by the steering wheel angle. The advantages of this approach compared to traditional approaches are to be not greedy in terms of the necessary field of vision and to have more flexible real-time constraints.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from Dissertation Abstracts.

This dissertation is concerned with travel time uncertainty in transportation networks due to ephemeral phenomena such as incidents or poor weather. Such events play a major role in nonrecurring congestion, which is estimated to comprise between one-third and one-half of all delay on freeways. Although past research has considered many individual aspects of this problem, this dissertation is unique in bringing a comprehensive approach, beginning with study of its causes, moving to discussion of its effects on traveler behavior, and then demonstrating how these models can be applied to mitigate the effects of this uncertainty. In particular, two distinctive effects of uncertainty are incorporated into all aspects of these models: nonlinear traveler behavior, encompassing risk aversion, schedule delay, on-time arrival, and other user objectives that explicitly recognize travel time uncertainty; and information and adaptive routing, where travelers can adjust their routes through the network as they acquire information on its condition. In order to accurately represent uncertain events in a mathematical model, some quantitative description of these events and their impacts must be available. On freeways, a large amount of travel data is collected through intelligent transportation systems (ITS), although coverage is far from universal, and very little data is collected on arterial streets. This dissertation develops a statistical procedure for estimating probability distributions on speed, capacity, and other operational metrics by applying regression to locations where such data is available. On arterials, queueing theory is used to develop novel expressions for expected delay conditional on the signal indication. The effects of this uncertainty are considered next, both at the individual (route choice) and collective (equilibrium) levels. For individuals, the optimal strategy is no longer a path, but an adaptive policy which allows for flexible re-routing as information is acquired. Dynamic programming provides an efficient solution to this problem. Issues related to cycling in optimal policies are examined in some depth. While primarily a technical concern, the presence of cycling can be discomforting and needs to be addressed. When considering collective behavior, the simultaneous choices of many self-optimizing users (who need not share the same behavioral objective) can be expressed as the solution to a variational inequality problem, leading to existence and uniqueness results under certain regularity conditions. An improved policy loading algorithm is also provided for the case of linear traveler behavior. Finally, three network improvement strategies are considered: locating information-providing devices; adaptive congestion pricing; and network design. Each of these demonstrates how the routing and equilibrium models can be applied, using small networks as testbed locations. In particular, the information provision and adaptive congestion pricing strategies are extremely difficult to represent without an adaptive equilibrium model such as the one provided in this dissertation. / text

Transportation Network Companies (TNC) are companies that use online-enabled platforms to connect passengers with drivers. In recent years, they have sparked controversy with the taxi industry, which accuses TNCs of operating unfairly. In my study, I look at taxi regulation, consumer transportation preferences, and costs and benefits of TNCs. I analyze data comparing three of these companies, Uber, Lyft, and Sidecar, with a traditional taxicab, and evaluate trends in taxi employment from the Bureau of Labor Statistics. I find that Transportation Network Companies generally have shorter wait times, cheaper prices, and increased convenience, aspects that appeal to consumer preferences. I also find that taxi driver employment tends to fluctuate with economic conditions, however cities that are more likely to use TNCs exhibit smaller growth. I predict that at current conditions, TNCs such as Uber and Lyft will overtake taxi services. Thus, the taxi industry must focus on increasing TNC regulation, creating innovative technology, and modifying its service to appeal to consumers.