Optimal control of a deterministic multiclass queuing system by serving several queues simultaneously

In this report we consider the optimal control problem of emptying a deterministic single server multiclass queuing system without arrivals. We assume that the server is able to serve several queues simultaneously, each at its own rate, independent of the number of queues being served. We showed that the optimal sequence of modes is ordered by rate of cost decrease. However, queues are not necessarily emptied. We propose a dynamic programming approach for solving the problem, which reduces the multiparametric QP (mpQP) to a series of problems that can be solved readily

Traffic flow on realistic road networks with adaptive traffic lights

We present a model of traffic flow on generic urban road networks based on cellular automata. We apply this model to an existing road network in the Australian city of Melbourne, using empirical data as input. For comparison, we also apply this model to a square-grid network using hypothetical input data. On both networks we compare the effects of non-adaptive vs adaptive traffic lights, in which instantaneous traffic state information feeds back into the traffic signal schedule. We observe that not only do adaptive traffic lights result in better averages of network observables, they also lead to significantly smaller fluctuations in these observables. We furthermore compare two different systems of adaptive traffic signals, one which is informed by the traffic state on both upstream and downstream links, and one which is informed by upstream links only. We find that, in general, both the mean and the fluctuation of the travel time are smallest when using the joint upstream-downstream control strategy.Comment: 41 pages, pdflate

Phase Synchronization in Railway Timetables

Timetable construction belongs to the most important optimization problems in public transport. Finding optimal or near-optimal timetables under the subsidiary conditions of minimizing travel times and other criteria is a targeted contribution to the functioning of public transport. In addition to efficiency (given, e.g., by minimal average travel times), a significant feature of a timetable is its robustness against delay propagation. Here we study the balance of efficiency and robustness in long-distance railway timetables (in particular the current long-distance railway timetable in Germany) from the perspective of synchronization, exploiting the fact that a major part of the trains run nearly periodically. We find that synchronization is highest at intermediate-sized stations. We argue that this synchronization perspective opens a new avenue towards an understanding of railway timetables by representing them as spatio-temporal phase patterns. Robustness and efficiency can then be viewed as properties of this phase pattern

Cognitive functions over the course of 1 year in multiple sclerosis patients treated with disease modifying therapies

Objectives: Disease-modifying therapies (DMTs) are applied to delay or prevent disease progression in multiple sclerosis (MS). While this has mostly been proven for physical symptoms, available studies regarding long-term effects of DMTs on cognitive functions are rare and sometimes inconsistent due to methodological shortcomings. Particularly in the case of fingolimod, comprehensive data on cognitive functions are not yet available. Therefore, we set out to reliably assess cognitive functions in patients with relapsing-remitting MS (RRMS) treated with DMTs over 1 year. Methods: Cognitive functions were assessed with eight tests at three timepoints: baseline, 6-month follow up and 12-month follow up. First, we investigated whether the stability of cognitive functions (i.e. not falling below the 5% cut-off in more than one test) over 1 year in RRMS patients (n = 41) corresponds to the stability in healthy individuals (n = 40) of a previous study. Second, we compared the percentage of declined and improved patients in the different tests. Third, we compared patients treated with fingolimod (n = 22) with patients treated with natalizumab (n = 11) with regard to cognitive stability. Fourth, based on the patient data, the Reliable Change Index was applied to compute cut-offs for reliable cognitive change. Results: Approximately 75% of RRMS patients treated with DMTs remained stable over the course of 1 year. The Paced Auditory Serial Addition Test (PASAT) and the Spatial Recall Test (SPART), produced improvements in 12.5% and 30.6%, respectively, probably due to practice effects. Patients treated with fingolimod did not differ from patients treated with natalizumab with regard to cognitive stability. Conclusions: Cognitive functions remain relatively stable under DMT treatment over 1 year, irrespective of the type of medication. Furthermore, the tests PASAT and SPART should be interpreted cautiously in studies examining performance changes over time. The provided RCI norms may help clinicians to determine whether a difference in two measurements observed in a RRMS patient is reliable

Optimization and performance study of a proton CT system for pre-clinical small animal imaging

Proton computed tomography (pCT) promises to reduce or even eliminate range uncertainties inherent in the conversion of Hounsfield units into relative stopping power (RSP) for proton therapy treatment planning. This is of particular interest for proton irradiation studies in animal models due to the high precision required and uncertainties in tissue properties. We propose a dedicated single-particle tracking pCT system consisting of low material budget floating strips Micromegas detectors for tracking and a segmented time-projection-chamber with vertical Mylar absorbers, functioning as a range telescope. Based on Monte Carlo simulations of a realistic in silico beam and detector implementation, a geometrical optimization of the system components was conducted to safeguard an ideal operation close to intrinsic performance limits at 75 MeV. Moreover, the overall imaging capabilities relevant for pre-clinical proton therapy treatment planning were evaluated for a mouse model. In order to minimize extrinsic uncertainties in the estimated proton trajectories, a spacing of the two tracking planes of at least 7 cm is required in both tracking detectors. Additionally, novel in-house developed and produced aluminum-based readout electrodes promise superior performance with around 3mm-1 spatial resolution due to the reduced material budget. Concerning the range telescope, an absorber thickness within 500 µm to 750 µm was found to yield the best compromise between water-equivalent path length resolution and complexity of the detector instrumentation, still providing sub-0.5% RSP accuracy. The optimized detector configuration enables better than 2% range accuracy for proton therapy treatment planning in pre-clinical data sets. This work outlines the potential of pCT for small animal imaging. The performance of the proposed and optimized system provides superior treatment planning accuracy compared to conventional X-ray CT. Thus, pCT can play an important role in translational and pre-clinical cancer research

DECENTRALIZED APPROACHES TO ADAPTIVE TRAFFIC CONTROL AND AN EXTENDED LEVEL OF SERVICE CONCEPT

Traffic systems are highly complex multi-component systems suffering from instabilities and non-linear dynamics, including chaos. This is caused by the non-linearity of interactions, delays, and fluctuations, which can trigger phenomena such as stop-and-go waves, noise-induced breakdowns, or slower-is-faster effects. The recently upcoming information and communication technologies (ICT) promise new solutions leading from the classical, centralized control to decentralized approaches in the sense of collective (swarm) intelligence and ad hoc networks. An interesting application field is adaptive, self-organized traffic control in urban road networks. We present control principles that allow one to reach a self-organized synchronization of traffic lights. Furthermore, vehicles will become automatic traffic state detection, data management, and communication centers when forming ad hoc networks through inter-vehicle communication (IVC). We discuss the mechanisms and the efficiency of message propagation on freeways by short-range communication. Our main focus is on future adaptive cruise control systems (ACC), which will not only increase the comfort and safety of car passengers, but also enhance the stability of traffic flows and the capacity of the road (“traffic assistance”). We present an automated driving strategy that adapts the operation mode of an ACC system to the autonomously detected, local traffic situation. The impact on the traffic dynamics is investigated by means of a multi-lane microscopic traffic simulation. The simulation scenarios illustrate the efficiency of the proposed driving strategy. Already an ACC equipment level of 10% improves the traffic flow quality and reduces the travel times for the drivers drastically due to delaying or preventing a breakdown of the traffic flow. For the evaluation of the resulting traffic quality, we have recently developed an extended level of service concept (ELOS). We demonstrate our concept on the basis of travel times as the most important variable for a user-oriented quality of service

Random planar graphs and the London street network

In this paper we analyse the street network of London both in its primary and dual representation. To understand its properties, we consider three idealised models based on a grid, a static random planar graph and a growing random planar graph. Comparing the models and the street network, we find that the streets of London form a self-organising system whose growth is characterised by a strict interaction between the metrical and informational space. In particular, a principle of least effort appears to create a balance between the physical and the mental effort required to navigate the city

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

An Agent-Based Approach to Self-Organized Production

The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c

Complexity, Development, and Evolution in Morphogenetic Collective Systems

Many living and non-living complex systems can be modeled and understood as collective systems made of heterogeneous components that self-organize and generate nontrivial morphological structures and behaviors. This chapter presents a brief overview of our recent effort that investigated various aspects of such morphogenetic collective systems. We first propose a theoretical classification scheme that distinguishes four complexity levels of morphogenetic collective systems based on the nature of their components and interactions. We conducted a series of computational experiments using a self-propelled particle swarm model to investigate the effects of (1) heterogeneity of components, (2) differentiation/re-differentiation of components, and (3) local information sharing among components, on the self-organization of a collective system. Results showed that (a) heterogeneity of components had a strong impact on the system's structure and behavior, (b) dynamic differentiation/re-differentiation of components and local information sharing helped the system maintain spatially adjacent, coherent organization, (c) dynamic differentiation/re-differentiation contributed to the development of more diverse structures and behaviors, and (d) stochastic re-differentiation of components naturally realized a self-repair capability of self-organizing morphologies. We also explored evolutionary methods to design novel self-organizing patterns, using interactive evolutionary computation and spontaneous evolution within an artificial ecosystem. These self-organizing patterns were found to be remarkably robust against dimensional changes from 2D to 3D, although evolution worked efficiently only in 2D settings.Comment: 13 pages, 8 figures, 1 table; submitted to "Evolution, Development, and Complexity: Multiscale Models in Complex Adaptive Systems" (Springer Proceedings in Complexity Series