<p> This research study presents results from two independent surveys. The objective of the first survey is to determine and rank the factors that influences owner operators and truck companies of Southern California in route selection. The second surveys objective is to determine the value of time (VOT) and the value of reliability (VOR) for owner operators and truck companies of Southern California. The two surveys require responses that were obtained via phone calls and interviews at numerous truck companies, truck stops, and distribution centers of Los Angeles County. Respondents of both the surveys are classified into 48 categories based on their load type, trip distance, and truck axles and this resulted in 48 distinctive results for the two surveys. </p><p> For the first survey results, the techniques of fuzzy Analytical Hierarchical Process (AHP) is used on 91 owner operators and 45 truck company responses to rank 19 factors that contributes the most in route selection. The 19 factors are identified through literature studies. Results indicate that travel time, travel time reliability, and safety are the most influencing factors regarding the route selection. </p><p> Furthermore, in the second study, a modern Stated Preference (SP) survey is conducted on 517 owner operators and 248 truck companies of southern California to determine the VOT and VOR by applying linear regression. The average VOT is $58/hr. and the average VOR is $14/hr. 48 other distinctive VOT and VOR results gives a wider scope.</p>

Thesis (M. Sc.)--University of Hong Kong, 1995. / Includes bibliographical references (leaf 105-108).

<p> The United States (US) witnessed remarkable growth in annual long distance travel over the past few decades. Over half of the long distance travel in the US is made for pleasure, including visiting friends and relatives (VFR) and leisure activities. This trend could continue with increased use of information and communication technologies for socialization, and enhanced mobility being achieved using fuel-efficient (electric/hybrid) and technology enhanced vehicles. Despite these developments, and recent interest to implement alternate mass transit options to serve this market, not much exists on the measurement, analysis and modeling of long distance pleasure travel in the U.S. </p><p> Statewide and national models are used to estimate long distance travel, but these are predominantly trip-based models, making it difficult to understand long distance trips as collection of household-level travel behavior. This form of travel behavior has been studied a lot in tourism, but in a piecemeal manner, such as to (from) a specific destination. Further, most of these studies are confined to analyzing leisure market, with VFR market gaining recognition only recently. In essence, annual household long distance pleasure travel behavior needs to be studied in a comprehensive manner rather than as isolated trips. This is because, most of these household travel decisions are undertaken considering their annual time and monetary budget, and their perceived cost to travel to one (or more) destination for given pleasure purpose on one (or more) occasion using a given mode of travel. Thus, the main objective of this dissertation is to develop a comprehensive behavioral model framework to analyze the above-discussed annual household long distance pleasure travel choices. </p><p> To start the above effort, it is first required to collect detailed annual household travel data, last collected over two decades ago (e.g.: ATS, 1995). No such recent effort has been pursued due to the significant labor and economic resource required to undertake it. There exist recent surveys (NHTS, 2001), but collected over a shorter (four week) period, and require significant processing even to arrive at aggregate annual travel estimates. Second, besides surveys, there is a need for additional data to estimate households&rsquo; annual pleasure travel budget, and their cost to travel and stay at each of their potential destination choices, which are not readily available. </p><p> Thus, as the first goal, this dissertation analyzes long distance travel reported across historical surveys (NPTS; ATS; NHTS), to understand the differences in their definition, enumeration of purpose and collection methods. The intent here is twofold, first to conceive a method to estimate annual travel from surveys with shorter collection period. Further, the second intent is to gather travel patterns from these historical datasets such that it informs the second goal of this dissertation, i.e. development of a behavioral framework to analyze annual household pleasure travel. To this effect, this research also analyzes pleasure expenditures using Consumer Expenditure Survey (CEX, BLS) data. Interestingly, the analysis reveals CEX pleasure travel expenditure pattern to be similar to the travel pattern reported for the same market segments in travel survey (ATS). </p><p> Importantly, the above analysis informs the development of behavioral models, pursued as two distinct tasks to achieve the second goal. As the first task, a novel econometric model and forecasting procedure is developed to analyze a household&rsquo;s annual long distance leisure travel decisions. Specifically, a households&rsquo; time spent across one (or more) destination and travel mode to such destination for leisure is modeled subject to time and money budget constraints. In this methodological framework, the destination choice is modeled as a continuous variable (time at destination) using Multiple-Discrete Continuous Extreme Value model (MDCEV). While, travel mode choice to these destination(s) are modeled as a discrete choice, through a nested Multinomial Logit Model (MNL), with price variation introduced across the above choice of destination(s) and travel modes (air/ground). This required estimating annual monetary budgets, travel cost and per night lodging cost for each sample household, with each of them having 210 potential destinations and 2 travel mode choices respectively. </p><p> The second task, involved the development of a broader national model system to analyze households&rsquo; annual pleasure travel decisions such as: choice (duration) at destination(s), travel purpose (VFR or leisure), mode (airplane or auto) choice and trip frequencies to these destination(s) using the same dataset. It was modeled in two stages, with the first stage estimating households&rsquo; annual pleasure time budget using a stochastic frontier model. This budget was then used as constraint to analyze households&rsquo; annual choice of destination and purpose using a nested MDCEV-MNL model in the second stage. A log sum variable from a nested joint multinomial logit model of trip frequency and mode choice for each purpose (VFR or leisure) is also introduced as input at this stage. This model was then validated using a prediction procedure, and further applied to test a policy scenario (increase in travel cost). The above national pleasure travel demand model could be further enhanced by including monetary constraints and price variation as in the first task. Overall, the model system proposed in this dissertation forms the foundation for a national comprehensive long distance travel model. This could be achieved through inclusion of other prominent travel purpose such as business and commuting to the national travel demand model presented in this research.</p>

Thesis (Ph. D.)--University of Rhode Island, 2006. / Typescript. Includes bibliographical references (leaves 141-150).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 245-256).

Thesis (M. Soc. Sc.)--University of Hong Kong, 1984.

Thesis (MComm)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Thesis (M.Soc.Sc.)--University of Hong Kong, 1984. / Also available in print.

Thesis (M.P.A.)--University of Hong Kong, 2004. / Also available in print.

The continuous operation of civil and marine structures is essential for maintaining the flow of people and goods. However, structures are exposed to extreme or progressive events during their service time. The uncertainties associated with the occurrence and the magnitude of extreme events (e.g. flooding and scour) may change, leading to unprecedented loading conditions, while the progressive events (e.g. corrosion and fatigue) may jeopardize the structural capacity to resist loads. In order to maintain or improve the structural capacity, repair and maintenance actions need to be applied to structures. However, the determination of these actions may be challenging for decision makers due to (a) limited financial resources to be allocated for a group of structures, (b) uncertainties associated with current structure conditions and future loading conditions, and (c) various decision-making factors (e.g. reliability threshold, decision time, and risk attitude). In order to address these issues, the focus of the research in this dissertation is to enhance the development of management strategies with the application in (a) management of bridge networks under hydraulic events and climate changes, (b) service life extension of ships considering financial feasibility and decision-making factors, and (c) determination of reliability threshold in the decision-making process. The management of bridge networks involves the quantification of regional hazards imposed on the network, performance assessment of structures, and consequence evaluation of potential bridge failure. Regional hazards such as floods may be affected by the changes in the intensity of precipitation due to anticipated climate changes. These hazards may cause extensive damage to bridges, and failure may cause significant costs to bridge managers and result in inconvenience on the daily traffic commute. This research focuses on enhancing the assessment and management of bridges networks vulnerable to regional hydraulic events and climate changes. The integration of transportation network analysis, which reflects the redistribution of traffic flow in the event of bridge failure, is shown to be essential when determining the risk level of bridges. Furthermore, this work includes proposed methodologies for determining optimal management strategies that account for the connection between global climate predictions and regional hydrologic conditions. The crux of determining management strategies, especially for extending ship service lives, is to ensure an adequate safety margin within and beyond the design life. In addition to the loading effect and structural capacity, the safety margin of ships is related to the deterioration acting on the structure. During ship operation, in-service condition surveys are conducted on ship details to assess structural conditions and to inform maintenance actions. This research focuses on the integration of condition surveys of ship details, as well as the timing of conducting surveys, to improve the service life extension for ship structures. While decision makers strive to maintain the safe operation of ships, they should also identify the management strategy that can deliver the best return given the limited budget. This research, from the perspective of cost-effectiveness and profitability, proposes optimization frameworks to clarify the financially feasible life expectancy of different management strategies as well as identify the optimal duration of extended service life for different categories of commercial ships. The last focus of this research emanates from the reliability threshold when determining management strategies. In addition to facilitating decision-making on the management of civil and marine structures, the reliability threshold in terms of target reliability index has been extensively used in design guidelines to ensure adequate safety margin for structures. The level of safety is typically related to the failure mode and severity of failure consequences (e.g. number of potential fatalities). Driven by the emerging application of unmanned ships where there are fewer or no crew members on board, this research specifically focuses on the integration of different acceptance criteria for human safety into the determination of the target reliability index.