Thesis--Northwestern University. / Vita. Includes bibliographical references (p. 137-139).

Thesis--Northwestern University. / Vita. Includes bibliographical references (p. 137-139).

This study deals with a) Understanding familiarity with transportation network companies (TNCs) and their use frequency b) Understanding travel choices in alcohol-related situations in Virginia. Ordered logistic regression models were used to identify factors associated with the respondents perceived familiarity with transportation network companies (TNCs) and use frequency. Based on the two models, the consistent factors were using a mobile wallet, a cell phone for entertainment, an app for taxi services, or an app for hotel booking/air transport arrangements, living in Northern Virginia, normally using multiple transportation modes for a single trip, higher education levels, and higher household income which were associated with increased TNC familiarity and use frequency. Self-identifying as White/Caucasian was also associated with increased TNC use frequency. Increased age was associated with decreasing TNC familiarity and use frequency. Subsequently, travel choices in alcohol related situations were studied with the objective of understanding the role of Transportation Network Companies (TNCs) in these situations and whether they have an impact on DUIs. For this objective, this study analyzes travel-choices associated with three scenarios alcohol related situations: (a) the last time the respondent consumed alcohol, (b) when avoiding driving after drinking, and (c) when avoiding riding with a driver who had been drinking. Multinomial Logistic Regression models were developed for all the three scenarios. For model (a), significant factors included use of a personal vehicle to arrive at the location where last consuming alcohol, being comfortable with having a credit card tied to a cell phone app, age, income, travelling alone when leaving the location where last consuming alcohol, having the highest educational attainment of high school graduate (GED), consumption of alcohol at bar/tavern/club, consumption of alcohol at home of friends/acquaintance place, and transportation network company (TNC – e.g., Uber, Lyft) weekly use frequency. For (b), use of a personal vehicle to arrive at the location where last consuming alcohol, consumption of alcohol at a bar/tavern/club, consumption of alcohol at the home of friends/acquaintance place, comfort with tying of credit card to apps, age, gender, income, multi-modal travel for a regular trip, TNC weekly use frequency, and use of an app for hotel reservations and/or air transportation arrangements are significant factors. For (c), use of a personal vehicle to arrive at the location where last consuming alcohol, walking to the location where last consuming alcohol, consumption of alcohol at a bar/tavern/club, comfort with tying a credit card to apps, age, income, TNC weekly use frequency, previously riding in a car with a driver who may have drunk too much to drive safely, and being employed full time are the significant factors. / Master of Science / The study intends to improve understanding of the characteristics of early adopters of TNC services and contribute towards understanding travel choices made by individuals in alcohol-related situations. Data for this study came from a telephone survey of just over 3000 respondents across three metropolitan regions of Virginia; Northern Virginia, Hampton Roads/Tidewater and the Richmond urban area. This study deals with a) Understanding familiarity with transportation network companies (TNCs) and their use frequency b) Understanding travel choices in alcohol-related situations in Virginia. Based on the surveys, ordinal logit models were developed to predict the degree of familiarity and use frequency of TNCs. The results showed that income was significantly associated with both increased familiarity and increased use frequency of TNCs. Educational attainment was also significant and positively associated with familiarity and use frequency. Age was significantly and negatively associated with TNC familiarity and use frequency. This may be important in understanding TNC use in locations with older populations. Individuals located in Northern Virginia were associated with increased TNC familiarity and use frequency. Individuals who used multiple modes to commute had a higher likelihood of being familiar with and using TNCs more frequently. Use of an app for sourcing taxi services was associated with increased TNC familiarity and use frequency. Similarly, using an app for hotel reservations and/or air transportation arrangements was associated with increased TNC use frequency. In addition, individuals using their phone for entertainment were more likely to be familiar with and use TNCs. Use of mobile wallet was associated with increased TNC familiarity and use frequency. Employment status “student” was significantly associated with TNC familiarity which suggests that information is easily accessible for this group of people. Also, individuals self-identifying their race as white had a higher probability of using TNCs. The second part of the research analysis included multinomial logistic regression models which identified factors associated with respondents’ travel choices in alcohol-related situations: (1) the last time the respondent consumed alcohol, (2) when avoiding driving after drinking, and (3) when avoiding riding with a driver who had been drinking. From the model results, it was found v that consumption of alcohol at a bar was statistically associated with use of TNC services in all three alcohol-related situations. TNCs were more likely to be used by younger people in all three alcohol-related situations examined in this study. Older people were more likely to ride with designated drivers than to use TNCs when avoiding driving after drinking and the last instance of consuming alcohol. Familiarity with, and regular use of TNCs increased the likelihood of using TNCs in all three alcohol-related situations in this study.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / To use Ethernet is the most convenient way to set up a transportation network for a telemetry data acquirement system. However, due to its CSMA/CD (Carrier Sense Multiple Access and Collision Detection) mechanics, Ethernet cannot transport data synchronously. This paper analyzed important features of transportation in a distributed data acquirement system, and presents a resolve for synchronously transporting data in a distributed data acquirement system by using direct Ethernet connection and TDM (time division multiplexing) technique.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 27). Also available in electronic version. Access restricted to campus users.

Ethernet is a common practice to reconstruct a networked telemetry system. However, Ethernet switch cannot best meet the requirement of data transportation in a telemetry system because of its asynchronous mode and the uncertainty of latency time. In addition, the temporal order of the telemetry data will be disrupted when using an Ethernet switch. A device similar to Ethernet switch is presented in this paper, which can transport data synchronously without losing the original temporal order of the telemetry data. Meantime, a special condition is arranged by the device that the timing signal could be transmit from the device to the receiver in a certain delay time, so a timing mechanism derived from IEEE 1588 PTP protocol could be adopted for high accuracy of timing and synchronous sampling control.

Traffic information, now available through a number of different sources, is re-shaping the way planners, operators and users think about the transportation network. It provides a powerful tool to mitigate the negative impacts of uncertainty, and an invaluable resource to manage and operate the network in real-time. More information also invites to think about traditional transportation problems from a different perspective, searching for a better utilization of the improved knowledge of the network state. This dissertation is concerned with modeling and evaluating the system-level impacts of providing information to network users, assuming that the data is utilized to guide an Adaptive System-Optimum (ASO) routing behavior. Within this context, it studies the optimal deployment of sensors for the support of ASO strategies, and it introduces a novel SO assignment approach, the Information-Based System Optimum (IBSO) assignment paradigm. The proposed sensor deployment model explicitly captures the impact of sensors' location on the expected cost of ASO assignment strategies. Under such strategies, a-priori routing decisions may be adjusted based on real-time information. The IBSO assignment paradigm leads to optimal flow patterns which take into account the ability of vehicles to collect information as they travel. The approach regards a subset of the system's assets as probes, which may face higher expected costs than regular vehicles in the search for information. The collected data is utilized to adjust routing decisions in real time, improving the expected system performance. The proposed problem captures the system-level impact of adaptive route choices on stochastic networks. The models developed in this work are rigorously formulated, and their properties analyzed to support the generation of specialized solution methodologies based on state-space partitioning and Tabu Search principles. Solution techniques are tested under a variety of scenarios, and implemented to the solution of several case studies. The magnitude and nature of the information impacts observed in this study illustrate problem characteristics with important theoretical, methodological and practical implications. The findings presented in this dissertation allow envisioning a number of practical applications which may promote a more efficient utilization of novel sensing and communication technologies, allowing the full realization of their potential. / text

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.

The calculation of path travel times is an essential component for the dynamic traffic assignment and equilibrium problems. This paper presents a simulation method for calculating actual path travel times for the traffic network with dynamic demands. The method is based on a path-based macroscopic simulation model of network traffic dynamics. There is no need to explicitly model intersection delays in this method. Discontinuity in the travel time caused by traffic light control can be captured by this method. It's flexible in terms that the model is not limited to a specific velocity-density relationship. Some numerical results for signalized and unsignalized networks are reported. / Singapore-MIT Alliance (SMA)

Includes bibliographical references (p. 128-135).