conference paper
published journal article
conference paper
published journal article
working paper
This research examines the behavioral reactions to the impact of changes in the probability of non-recurrent incident and how this effects the expected costs of a commute trip. This basic approach combines the estimation of a travel demand model (estimated with data collected from a stated preference survey) with a supply side model of a congested highway. We also examine the impact of various socio-economic variables, including a detailed classification of occupational groupings. Our demand model is based on a theoretical model developed to explain how unreliability in travel times affects expected travel costs. We find that expected schedule delay (early and late), lateness probability, and expected travel time influence the expected costs of travel. Our parameter estimates confirm the anticipated values of these parameters: lateness probability has a high disutility, while expected schedule delay early is preferable to expected schedule delay late, and the disutility of expected travel time is between these two. We do not find a high level of significance for planning costs, as expressed by the variance in travel times. Our simulation model shows that schedule costs and lateness probability represent a large fraction of the total cost to the commuter; these are generally not affected by capacity increases but can be reduced by decreasing the probability of a non-recurrent incident.
working paper
As public funds become ever more scarce and demands on them ever greater, public scrutiny of their use increases. Means are sought to determine exactly how such funds are being used, and to determine where and how they could be better allocated. The quantitative evaluation of performance provides some measure of rational justification for political and policy decisions. Public transit is today in this position of stabilized or decreasing funds and increasing demands, yet there exist no readily applicable means of evaluating transit performance. Transit must adapt the evaluation techniques and learn from the experience of other public fields. Performance evaluation has long been an issue in the fields of public education, housing, and health. Many volumes of research are available discussing evaluation theory and experience with techniques ranging from performance contracts and peer ratings to subjective ratings of “satisfaction”. Performance evaluations are also conducted in many other public service fields, e.g. fire and police services. Yet, the fields of education, housing, and health are similar to public transit in that they: (1) must be provided on a continuous basis; (2) cannot be nor mally justified on a public safety basis, as can police and fire ser vices; and (3) are not utilized by the entire population on a regular basis. This paper will investigate each of the fields (public education, housing, and health) in turn, discussing the predominant evaluation techniques used or suggested for that field and the problems inhibit ing’ evaluation. For each area, appropriate parallels will be drawn to the evaluation of public transit.
Phd Dissertation
Parallel distributed computing has been widely studied and utilized to enable grids (or clusters) to meet the increasing demand of computation, especially in the field of scientific computation and modeling. The goal of distributed computing platforms is to provide the necessary infrastructure so that applications and their users can aggregate resources dynamically and shorten the processing time of the applications. With the rapid development of the Internet, the current distributed computing platforms are becoming more complicated. A typical type of modern distributed computing platforms is grid. Because the modern distributed computing platforms may contain numerous computational network nodes, one important challenge is how to schedule the load of tasks to these network nodes efficiently [1]. In addition, the environments of current computational platforms are becoming more complicated due to the availability of high performance network nodes and interconnects. Therefore, more advanced scheduling algorithms should be utilized to handle these problems. It is therefore necessary to create a new generation of schedulers that provides more comprehensive support for addressing the modern distributed computing platform requirements, so that the network nodes can be utilized effectively By analyzing and identifying the limitations of applying conventional scheduler technologies for distributed parallel applications, this dissertation presents a new design and its associated algorithms for enhancing conventional schedulers to provide better performance with considering more realistic factors. This dissertation also presents both mathematical and empirical analysis of three different proposed models. This dissertation provides three contributions to the field of task scheduling in distributed computing. First, current published algorithms are analyzed and weakness are exposed when real-world factors are considered, such as startup-costs, arbitrary processor times. Second, it contributes to the design of the scheduling algorithms by considering more realistic factors, which extend the usages of schedulers. Finally, it presents empirical and analytical results to demonstrate the effectiveness and the advantage of the proposed algorithms. The work in this dissertation has a broader impact beyond the algorithms in which they were developed, as it provides deeper understanding of scheduling tasks in the more realistic models, which will allow us to design more efficient algorithms.
published journal article
This paper analyzes strategic interaction between intercontinental airport regulators, each of which levies airport charges paid by airlines and chooses its airport capacity under conditions of congestion. Congestion from intercontinental flights is common across intercontinental airports since departure and arrival airports are linked one to one, while purely domestic traffic also uses each airport. The paper focuses on two questions. First, if both continents can strategically set separate airport charges for domestic and intercontinental flights, how will the outcome differ from the first-best solution? Second, how is strategic airport behavior affected by the extent of market power of the airlines serving the intercontinental market? We see that strategic airport pricing and capacity choices by regulators lead to a welfare loss: the regulators both behave as monopolists in the market for intercontinental flights, charging a mark-up and decreasing capacity. This welfare loss even overshadows possible negative effects from imperfect competition within the intercontinental airline market. We further discuss how the presence of multiple regulators on one continent or a simple pricing rule might constrain the welfare loss created by strategic airport regulation. (C) 2013 Elsevier Ltd. All rights reserved.
research report
This study shows that as freight transportation costs decline due to autonomous driving technology and online shopping increases, warehousing becomes more consolidated, the number and size of distribution centers increase, drayage truck mileage is reduced but delivery truck mileage increases, leading to a net mileage increase.
published journal article
This paper proposes a hybrid approach to model usage at public bikeshare system (PBS) stations. The proposed Cluster Stations and Regress (CSR) modeling approach involves first clustering PBS stations based on the types of trips they attract using k-means or fuzzy c-means clustering techniques. After obtaining station-cluster membership values for each station, the authors estimate multilevel mixed-effect regression models with interactions between the station-cluster membership variables and determinants of PBS station usage. Determinants considered in the empirical models include the socio-demographic and commute characteristics of the residents in each PBS stationâ??s census tract, weather variables, temporal variables, and PBS station proximity to restaurants, jobs, transit stops, rail stations, the central business district (CBD), bicycle infrastructure, and other PBS stations. The model results clearly indicate that determinants of PBS station usage vary across station-clusters and including station-cluster interaction terms significantly improves model fit. Additionally, the results of cross-validation tests indicate that the CSR approach is a promising method to model monthly PBS station usage. The empirical results also clear up conflicting findings in the literature in terms of the impact of nearby PBS stations on station usage. The authors find that station usage increases with the number of other PBS stations within 1â??5â?¯km for member trips. However, after controlling for this effect, station usage decreases as the number of other PBS stations within 0.8â?¯km increases.