Self-Control of Traffic Lights and Vehicle Flows in Urban Road Networks

Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks [D. Helbing and P. Moln\'ar, Phys. Eev. E 51 (1995) 4282--4286], we propose a self-organization approach to traffic light control. The problem can be treated as multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as ``green waves'' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes

Optimal Policies for the Acceptance of Living- and Cadaveric-Donor Livers

Transplantation is the only viable therapy for end-stage liverdiseases (ESLD) such as hepatitis B. In the United States,patients with ESLD are placed on a waiting list. When organsbecome available, they are offered to the patients on this waitinglist. This dissertation focuses on the decision problem faced bythese patients: which offer to accept and which to refuse? Thisdecision depends on two major components: the patient's currentand future health, as well as the current and future prospect fororgan offers. A recent analysis of liver transplant data indicatesthat 60\% of all livers offered to patients for transplantationare refused.This problem is formulated as a discrete-time Markov decisionprocess (MDP). This dissertation analyzes three MDP models, eachrepresenting a different situation. The Living-Donor-Only Modelconsiders the problem of optimal timing of living-donor livertransplantation, which is accomplished by removing an entire lobeof a living donor's liver and implanting it into the recipient.The Cadaveric-Donor-Only Model considers the problem ofaccepting/refusing a cadaveric liver offer when the patient is onthe waiting list but has no available living donor. In this model,the effect of the waiting list is incorporated into the decisionmodel implicitly through the probability of being offered a liver.The Living-and-Cadaveric-Donor Model is the most general model.This model combines the first two models, in that the patient isboth listed on the waiting list and also has an available livingdonor. The patient can accept the cadaveric liver offer, declinethe cadaveric liver offer and use the living-donor liver, ordecline both and continue to wait.This dissertation derives structural properties of all threemodels, including several sets of conditions that ensure theexistence of intuitively structured policies such as control-limitpolicies. The computational experiments use clinical data, andshow that the optimal policy is typically of control-limit type

Creation and Simulation of a Model for a Discrete Time Buffer System with Interrupted Poisson Arrivals and Uncorrelated Server Interruptions

A mathematical model for a discrete-time buffer system with both arrival and server interruptions is developed. In this model fixed-size packets arrive at the buffer according to a Poisson distribution and are stored there until they can be transmitted over the output channel. Service times are constant and the buffer is assumed to be of infinite size. Both arrival stream as well as the service of the packets are subjected to random interruptions described by Bernoulli processes, where the interruption process of the Poisson input stream is uncorrelated to the interruptions of the output line. Expressions are derived for the mean waiting time, the mean queue length, the average lengths of idle and busy periods of the server, and for the server utilization. The behavior of the system is demonstrated with a computer simulation; the simulation results are used to indicate optimal buffer sizes