Estimating the impact of time-based road user charges on risk taking by drivers.

This study, conducted for ethical reasons on a driving simulator, has indicated that drivers take more risks when they are being charged for their use of roadspace on the basis of time, than they do when they are not subject to such charges. This effect is highly significant for some measures of risk taking (e.g. red light violation and illegal overtaking) but less so for others. The effect is apparent even at very low charge levels and is observed irrespective of whether the charge is based on total travel time or time spent below specified speeds (‘congestion charges’). There are however some differences in the types of risky behaviour engendered by these two charging regimes. These results have obvious and serious implications for the implementation of time-based road user charges

Robust Queueing Theory

We propose an alternative approach for studying queues based on robust optimization. We model the uncertainty in the arrivals and services via polyhedral uncertainty sets, which are inspired from the limit laws of probability. Using the generalized central limit theorem, this framework allows us to model heavy-tailed behavior characterized by bursts of rapidly occurring arrivals and long service times. We take a worst-case approach and obtain closed-form upper bounds on the system time in a multi-server queue. These expressions provide qualitative insights that mirror the conclusions obtained in the probabilistic setting for light-tailed arrivals and services and generalize them to the case of heavy-tailed behavior. We also develop a calculus for analyzing a network of queues based on the following key principles: (a) the departure from a queue, (b) the superposition, and (c) the thinning of arrival processes have the same uncertainty set representation as the original arrival processes. The proposed approach (a) yields results with error percentages in single digits relative to simulation, and (b) is to a large extent insensitive to the number of servers per queue, network size, degree of feedback, and traffic intensity; it is somewhat sensitive to the degree of diversity of external arrival distributions in the network

Micro-simulation of the impact of different speeds on safety road travel and urban travel time: case study in the city of Guimarães

In recent days, the use of micro-simulation as an additional tool for the study of the network makes this management faster and more efficient, avoiding in situ studies. However, although it is a useful tool, it is necessary that the model under study is the best represented possible in order to obtain results that best fit the reality of the road, and a poor calibration of the model can provide results that do not fit the good management of the road under study. In this sense, using micro-simulation, more precisely to the VISSIM PTV software, a road network at the microscopic level will be evaluated as well as the parameters that most influence the route of the users within that network. The parameters will be modified according to the modeler so as to obtain a model as close to reality as possible. The most appropriate criteria for the calibration and validation of the model will also be chosen. The road safety of the network will also be analyzed using the SSAM software. Here the network's points of conflict will be analyzed, characterizing them as to the type and its severity. Subsequently, a sensitivity analysis will be introduced, where some parameters will be modified individually or together, in order to assess their influence on the network, thus assessing the importance of each in the vehicles.(undefined

Separation of timescales in a two-layered network

We investigate a computer network consisting of two layers occurring in, for example, application servers. The first layer incorporates the arrival of jobs at a network of multi-server nodes, which we model as a many-server Jackson network. At the second layer, active servers at these nodes act now as customers who are served by a common CPU. Our main result shows a separation of time scales in heavy traffic: the main source of randomness occurs at the (aggregate) CPU layer; the interactions between different types of nodes at the other layer is shown to converge to a fixed point at a faster time scale; this also yields a state-space collapse property. Apart from these fundamental insights, we also obtain an explicit approximation for the joint law of the number of jobs in the system, which is provably accurate for heavily loaded systems and performs numerically well for moderately loaded systems. The obtained results for the model under consideration can be applied to thread-pool dimensioning in application servers, while the technique seems applicable to other layered systems too.Comment: 8 pages, 2 figures, 1 table, ITC 24 (2012

Models and methods for operational planning in freight railroads

textRailroads are facing increasing demand for freight transportation. Effective planning and scheduling are crucial to improve the utilization of expensive resources (such as crew and track), reduce operational costs, and provide on-time service. This dissertation focuses on problem modeling and solution method development for real planning problems faced by railroads. It consists of three chapters that study two important planning problems in the daily operations of U.S. freight railroads: crew assignment and train movement planning. Chapter 2 proposes an optimization model to decide crew-to-train assignments and deadheads for double-ended crew districts. We develop an effective solution approach, combining optimization and a standalone heuristic, that generates optimal solutions in minutes. The excellent performance of this solution approach makes it well-suited for implementation within a real-time decision support tool for crew dispatchers. Chapter 3 discusses crew repositioning given the uncertainty in trains’ arrival and departure times. We propose models that minimize the expected crew holding, train delay, and deadheading cost, and develop both exact and heuristic solution methods to provide insights for crew planning under train schedule uncertainty. The last chapter studies the movement planning problem for trains traveling in a territory with multiple through tracks (mainlines) and various junctions. We explore a number of heuristic algorithms to obtain good solutions within a reasonable amount of time. The contributions of this dissertation include modeling enhancements, algorithmic development, implementation and computational testing, and validation using real data.Operations Research and Industrial Engineerin

QUANTIFYING FAIRNESS IN QUEUING SYSTEMS: PRINCIPLES, APPROACHES, AND APPLICABILITY

In this article we discuss fairness in queues, view it in the context of social justice at large, and survey the recently published research work and publications dealing with the issue of measuring fairness of queues. The emphasis is placed on the underlying principles of the different measurement approaches, on reviewing their methodology, and on examining their applicability and intuitive appeal. Some quantitative results are also presented. The article has three major parts (sections) and a short concluding discussion. In the first part we discuss fairness in queues and its importance in the broader context of the prevailing conception of social justice at large, and the distinction between fairness of the queue and fairness at large is illuminated. The second part is dedicated to explaining and discussing three main properties expected of a fairness measure: conformity to the general concept of social justice, granularity, and intuitive appeal and rationality. The third part reviews the fairness of the queue evaluating and measuring approaches proposed and studied in recent years. We describe the underlying principles of the different approaches, present some of their results, and review them in context of the three main properties expected from a measure. The short discussion that follows centers on future research issue