Source: Dissertation Abstracts International, Volume: 40-09, Section: A, page: 5217. / Thesis (Ph.D.)--The Florida State University, 1979.

Source: Dissertation Abstracts International, Volume: 38-04, Section: A, page: 2375. / Thesis (Ph.D.)--The Florida State University, 1976.

This dissertation proposes solutions to a selected set of detection and optimization problems, whose applications are focused on transportation systems. The goal is to help build smarter and more efficient transportation systems, hence smarter cities. Problems with dynamics evolving in two different time-scales are considered: (1) In a fast time-scale, the dissertation considers the problem of detection, especially statistical anomaly detection in real-time. From a theoretical perspective and under Markovian assumptions, novel threshold estimators are derived for the widely used Hoeffding test. This results in a test with a much better ability to control false alarms while maintaining a high detection rate. From a practical perspective, the improved test is applied to detecting non-typical traffic jams in the Boston road network using real traffic data reported by the Waze smartphone navigation application. The detection results can alert the drivers to reroute so as to avoid the corresponding areas and provide the most urgent "targets" to the Transportation department and/or emergency services to intervene and remedy the underlying cause resulting in these jams, thus, improving transportation systems and contributing to the smart city agenda. (2) In a slower time-scale, the dissertation investigates a host of optimization problems, including estimation and adjustment of Origin-Destination (OD) demand, traffic assignment, recovery of travel cost functions, and joint recovery of travel cost functions and OD demand (joint problem). Integrating these problems leads to a data-driven predictive model which serves to diagnose/control/optimize the transportation network. To ensure good accuracy of the predictive model and increase its robustness and consistency, several novel formulations for the travel cost function recovery problem and the joint problem are proposed. A data-driven framework is proposed to evaluate the Price-of-Anarchy (PoA; a metric assessing the degree of congestion under selfish user-centric routing vs. socially-optimal system-centric routing). For the case where the PoA is larger than expected, three viable strategies are proposed to reduce it. To demonstrate the effectiveness and efficiency of the proposed approaches, case-studies are conducted on three benchmark transportation networks using synthetic data and an actual road network (from Eastern Massachusetts (EMA)) using real traffic data. Moreover, to facilitate research in the transportation community, the largest highway subnetwork of EMA has been released as a new benchmark network.

<p> The purpose of this research was to qualitatively study the public&rsquo;s trust and knowledge of unmanned aviation safety through data collection by interviewing research subjects. The researcher sought to determine whether the research subjects would be willing to fly as passengers in Unmanned Aircraft Systems (UAS), and if publicity about the UAS industry, its development and integration into the National Airspace System (NAS) have influenced their perceptions of UAS safety, which could affect their decision to travel as passengers in UAS in the future. The researcher also examined data to identify if any observable Dunning-Kruger Effect existed that would suggest if any of the subjects believed they had more knowledge about the factors that affect UAS safety than what they knew when deciding whether to fly as passengers in UAS.</p><p>

Thesis (Ph. D.)--University of Oregon, 2006. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 103-109). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--UCLA, 2009. / Vita. Description based on print version record. Includes bibliographical references (leaves 148-163).

Each mode of transport has their limitation but multimodal transport which combines various transport modes is an alternative solution to breakthrough such limitation by way of synergy. To achieve such synergy, containerization and electronic commerce are, inter alia, the two indispensible factors for the rapid development of the multimodal transport. In the modern supply chain operation, containerization facilitates the interchange of goods among different transport modes whereas electronic commerce expedites the documentation flow in a more efficient and secured manners. As a result, multimodal transport has become more efficient than ever so as to create a room for lower transportation cost and shorter travelling time. Nevertheless, it is observed that the prevailing liability system of the multimodal transport, in which, not a single and uniform convention for the international multimodal transport has been in place, is unable to keep pace with the astonishing growth of the multimodal transport. This results in unpredictability and uncertainty as to the obligation and liability of all the parties including shippers, multimodal transport operators, carriers and insurance companies. This paper discusses the effectiveness of the Rotterdam Rules which is a maritime-plus convention in multimodal transport to which many attempts such as the Multimodal Transport Convention 1980 and the UNCTAD/ICC Rules have been taken. To evaluate such effectiveness, a comparative study has been adopted that incorporates three aspects, namely the horizontal comparison with the Hague-Visby Rules and the Hamburg Rules, the vertical comparison with the Multimodal Transport Convention 1980 and the UNCTAD/ ICC Rules and the harmonization comparison with the multimodal aspects of other unimodal conventions. Regarding the first two horizontal and vertical comparisons, they are made on the basis of five multimodal parameters including door-to-door delivery, intermodality, just-in-time delivery, containerization and electronic commerce. Furthermore, a common law case “Quantum Corp Inc and others v Plane Trucking Ltd and another” is selected for the case study on how well the Rotterdam Rules tackled the typical issues of unspecific or optional carriage contracts in the multimodal transport if they were put in the real operation. The results show that the “Outward Approach” adopted in the Rotterdam Rules is a feasible alternative different from the traditional “Inward Approach” to regulate the multimodal transport. Besides, in view of the recourse action for unlocalized damages, the use of maritime-basis liability amount is seen as the fair balance of interest and risk among the stakeholders. In the comparative and case studies, it is found that the general results are Expand, Possess, Harmonize and Apply (EPHA) in the respective areas of the comparisons and case analysis. On the whole, the Rotterdam Rules are viewed as an effective convention in multimodal transport. / published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

<p> This dissertation examines the impact of parking pricing on travel demand and behavior, using the University of California (UC), Berkeley campus as a study site. Parking pricing is often implemented to recover costs or to serve as a source of revenue for cities or private parking operators. However, parking pricing can also be an effective transportation demand management tool. Parking price can be set at market rates or can be set to meet other objectives, such as reducing emissions or traffic. In either case, by increasing the direct cost of driving, parking pricing can lead travelers to shift to public transportation or non-motorized modes. Parking pricing can also help to reduce total distance traveled through cruising reduction, and through trip reduction or consolidation, and in so doing can decrease congestion, air pollution and other transportation externalities. Understanding the role of parking pricing in influencing travel demand and behavior is crucial for determining whether a flexible and variable pricing structure can be effective in managing parking demand and scarce land resources, yet at the same time, generating adequate economic revenue. </p><p> The main objective of this dissertation is to analyze whether and to what extent changes in parking policies can alter transportation mode choice and parking preferences given different travel constraints, options and needs. Changes in parking policies examined in this dissertation not only include price, but also payment type (i.e. monthly, daily, or hourly), proximity of parking location to workplace and other incentives bundled together with specific parking options. Therefore, parking preference is defined as the pricing type and location of the chosen parking space. The types of parking pricing analyzed in this dissertation include paying by month, day, or hour, together with transit incentives bundled with different types of parking pricing options, while parking location is broadly divided into on-campus and off-campus parking. In order to better evaluate the impact of parking pricing and other transportation policies on travel behavior and demand, it is also necessary to understand how travel and parking behavior can be influenced by employment type and its respective flexibility of work schedule. In addition to accounting for the socioeconomic characteristics of the employees, this dissertation therefore investigates their job characteristics and the flexibility of their work schedule, both of which affect transportation mode choice and parking location because of their effects on time of travel, time, duration of stay at the workplace and frequency of commute trips. </p><p> The UC Berkeley campus was selected as a study site to reevaluate current parking policies and to improve parking pricing to lower transportation demand and to reduce cruising for parking. The University is situated adjacent to the City of Berkeley's downtown, in the inner suburban ring of the San Francisco Bay Area. The campus is served directly by several AC Transit bus routes and a Bay Area Rapid Transit (BART) station. UC Berkeley is one of the largest employers and trip generators in the region, with more than 36,000 students, 1,377 faculty members, and more than 12,000 non-academic staff. As a result, it generates more than 50,000 trips per day, whereas there are only approximately 5,000 parking spaces available on campus. There is a clear constraint on parking availability and transportation demand management tools are vital in maintaining a relatively low driving mode share. Current parking policies are designed to cover current operating costs, but fall well short of replacement costs, with an annual budget of approximately $13 million, except for bond payments. Furthermore, there is a wide range of employment types, job levels, work schedules, residential locations, and socioeconomic characteristics at UC Berkeley, which reflect varying employee attitudes, commute and parking choices. Therefore, findings from this dissertation can be applied to other regions. UC Berkeley students are excluded in this study. Campus parking regulations restrict parking permits to students who live off campus at a distance of two miles or more, and only 26 percent of students meet this criterion. As a result, only eight parking lots or garages are available for student parking. The study focuses instead on faculty and staff transportation demand and parking behavior. </p><p> A total of four different research methods were used to investigate attitudes and behavior, namely, open-ended interviews, focus groups, a transportation and parking survey, and discrete choice analysis. The combination of quantitative and qualitative methods provides complementary yet independent observations, as each method examines different facets of the research question. The survey was designed to examine current transportation demand and parking behavior, as well as potential changes in behavior under various parking pricing scenarios. Hence, it was used to collect both revealed preference (RP) and stated preference (SP) data. (Abstract shortened by UMI.)</p>

<p> There has been an increasing focus in recent years on efficient response to large-scale disasters due to the severity of devastation under several natural and man-made disasters. From a transportation perspective, a key objective in this context is disaster-related mass evacuation to avoid/mitigate the potential loss of life. It addresses the movement of people (demand) from the region affected or threatened by a disaster to areas of safety using the available transportation system (supply). In an operational context, the mass evacuation problem is shaped by the dynamics of three underlying aspects: demand, supply, and disaster. Hence, it is critical to integrate the time-dependent effects, and consequent interactions, of these three aspects to determine effective evacuation strategies within a deployable framework. However, most current studies focus primarily on the supply-side management, while addressing the other two aspects in a comparatively notional or simplified manner. Additionally, there is the lack of systematic paradigms for real-time operation that capture the dynamics of the evacuation network resulting from the intricate interactions between these three aspects, especially evacuee behavior, evolving traffic conditions, and disaster spatio-temporal characteristics. </p><p> This dissertation proposes the concept of evacuation risk and behavior-consistent information strategies to develop a stage-based operational framework for mass evacuation that integrates the dynamics of demand, supply and disaster characteristics. Evacuation risk, a measure based on whether the population at a location in the affected region can be safely evacuated before the disaster impacts it, uses the estimated time-dependent lead time to disaster impact at a location and the estimated time-dependent clearance time based on evolving traffic conditions, to characterize the time-dependent risk associated with that location. Thereby, it factors the time-dependent effects of the supply and disaster characteristics to prioritize locations in terms of when they should be recommended to evacuate to mitigate the substantial impact of a large demand impinging on a finite transportation capacity in a short duration as is common under a mass evacuation scenario. The prioritization of the locations is done by determining evacuation risk zones (ERZs) based on their time-dependent evacuation risks. An innovative aspect of the concept of evacuation risk is that it enables the proposed framework to be independent of the specific characteristics of a disaster or disaster type. This feature enables the operational framework to be generalized relative to the disaster type and/or its characteristics, and represents a key departure from existing approaches in this domain. </p><p> The behavior-consistent information strategies of the disaster response operator provide evacuation recommendation and route guidance information to people in the disaster-affected region to minimize the total system travel time in that region. The strategies are behavior-consistent because they explicitly factor the disaster response operator's objectives and the estimation of evacuee response behavior to the provided information in the determination of the information strategies. This entails the consideration of the time-dependent interactions of the demand and supply characteristics. The evacuee behavior is modeled with several elements of realism. It factors emergent behavioral processes as the problem is characterized by a potential threat from the extreme event, time pressure, and herding mentality. It uses fuzzy logic to capture subjective and qualitative elements that govern evacuee decision-making under information provision. Due to limitation on the data availability in real-world operations, the associated behavior models are developed at an aggregate level, which allows model calibration based on measurable traffic data. A mixed logit structure is applied to accommodate the behavioral heterogeneity across individual evacuees. Together, this fidelity and realism in modeling the behavioral aspects of evacuation represent a key new capability to address disaster-related evacuation operations. </p><p> To enable real-time deployment from a computational standpoint, the stage-based framework is implemented using a rolling horizon approach by identifying an ERZ in each stage. The ERZ is a spatially bounded subzone of the affected region encompassing the population currently with the highest evacuation risk, in which the limited evacuation response resources (such as personnel and equipment) can be deployed to synergistically aid system performance under the information strategies adopted for that stage. Thereby, the ERZ-based strategies seamlessly integrate demand, supply and disaster characteristics to foster a generalized evacuation operational framework.</p>

Thesis (Ph.D.) -- University of Adelaide, Dept. of Mathematics, 1971. / Reprint from published paper in back pocket.