Dynamic traffic assignment on parallel computers in TRANSIMS

Rickert, M.; Nagel, Kai

doi:10.1016/s0167-739x(00)00032-7

Cited by 70 publications

(25 citation statements)

References 11 publications

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“…In general, lane changing destabilizes laminar flow, that is, as a tendency it decreases times to breakdown in Figure 7. This effect can be reduced when drivers make a strong effort to not disturb vehicles behind them when they change lanes (Rickert et al 1996).…”

Section: Multilane Trafficmentioning

confidence: 99%

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

Nagel¹,

Wagner

Woesler

2003

Operations Research

Self Cite

288

165

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Certain aspects of traffic flow measurements imply the existence of a phase transition. Models known from chaos and fractals, such as nonlinear analysis of coupled differential equations, cellular automata, or coupled maps, can generate behavior which indeed resembles a phase transition in the flow behavior. Other measurements point out that the same behavior could be generated by geometrical constraints of the scenario. This paper looks at some of the empirical evidence, but mostly focuses on different modeling approaches. The theory of traffic jam dynamics is reviewed in some detail, starting from the well-established theory of kinematic waves and then veering into the area of phase transitions. One aspect of the theory of phase transitions is that, by changing one single parameter, a system can be moved from displaying a phase transition to not displaying a phase transition. This implies that models for traffic can be tuned so that they display a phase transition or not.This paper focuses on microscopic modeling, i.e., coupled differential equations, cellular automata, and coupled maps. The phase transition behavior of these models, as far as it is known, is discussed. Similarly, fluid-dynamical models for the same questions are considered. A large portion of this paper is given to the discussion of extensions and open questions, which makes clear that the question of traffic jam dynamics is, albeit important, only a small part of an interesting and vibrant field. As our outlook shows, the whole field is moving away from a rather static view of traffic toward a dynamic view, which uses simulation as an important tool.

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Section: Multilane Trafficmentioning

confidence: 99%

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

Nagel¹,

Wagner

Woesler

2003

Operations Research

Self Cite

288

165

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“…The team had, when it started with the Java-based MATSim (cf. 46.2.1.4), considerable experience in parallel computing (Nagel and Schleicher, 1994;Rickert and Nagel, 2001;Nagel and Rickert, 2001;Cetin et al, 2003) as well as with more general message-based approaches (Gloor and Nagel, 2005) that resemble today's Protocol Bu ers (Google Developers, 2015). However, the move to Java (see Section 46.2.1.4), a decision for faster conceptual progress and reduced maintenance e ort, also had the consequence that the MPI (Message Passing Interface) approach to parallel computing could no longer be used and was thus given up.…”

Section: Chapter 40mentioning

confidence: 99%

The Multi-Agent Transport Simulation MATSim

Axhausen¹

2016

497

123

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PrefaceDeveloping complex so ware for over a decade with a heterogeneous group of engineers and scientists, each with widely di erent skill levels and expertise across multiple locations around the world, requires dedication and mechanisms unusual for a university environment. This book is one of these mechanisms. It allows us, collectively, to take stock and present a coherent state-of-the-system: for us and anyone interested in this approach. It highlights basics for the student who wants to undertake a small rst research project as part of his or her degree, provides a description of the main functionalities, in detail, for the engineer setting up MATSim (MultiAgent Transport Simulation) to conduct a policy analysis and, nally, ts the approach into the theoretical background of complex systems in computer science and physics.The choice of the additional e-book format is an advantage, as it allows us to keep the book upto-date with future chapters, revisions and, if necessary, errata. Equally importantly it allows you, the readers, to select those sections relevant to your needs.The book comes at an important time for the system; for most of the rst decade, its use was limited to the original developers and users in Berlin and Zürich. It is now much more widely consulted around the world, as we document in the chapter summarizing contributions on scenarios so far.Scenario: This term will occur again and again. In MATSim context, it is de ned as the combination of speci c agent populations, their initial plans and activity locations (home, work, education), the network and facilities where, and on which, they compete in time-space for their slots and modules, i.e., behavioral dimensions, which they can adjust during their search for equilibrium. Within these scenarios, the user can experiment and explore with behavioral utility function parameters, with the sampling rate of the population between 1 % and 100 %, with algorithm parameters, e.g., the share of the sample engaged in replanning in any iteration, or behavioral dimensions or exact settings necessary to avoid gridlock due to the tra c ow dynamics. The creation of a scenario is a substantial e ort, and the framework makes a number of tools available to accelerate it: population synthesizers, network editors, network converters between popular formats and the MATSim representation, e.g., OSM (OpenStreetMap) or GTFS (General Transit Feed Speci cation), semi-automatic network matching to join information, among others.A large group of colleagues has been involved and many of them are contributors to this book; this is a list of those involved, other than ourselves, in Berlin, Singapore and Zürich. Additional contributors are mentioned as authors of their respective chapters in this book. We hope to acknowledge the contributions of more colleagues from other groups in future versions of this book and in the so ware.Special thanks go to a number of people who greatly helped improving this book beyond their own chapters. Benjamin Kickhöfer's deep knowledge of ...

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“…24 As part of the TRANSIMS, Dallas/Fort Worth (Texas) is reconstructed based on the data of the Portland (Oregon) metropolitan area as a demonstrative study. 25 Based on TRANSIMS, further research about disease outbreaks in urban social networks are developed, which is called EpiSims. EpiSims combines realistic estimates of population mobility with parameterized models, and simulates the progress of a disease within a host and transmission between hosts.…”

Section: Individual-based Modelingmentioning

confidence: 99%

Virtual city: An individual-based digital environment for human mobility and interactive behavior

Meng

Cao

et al. 2014

SIMULATION

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Increasing computing capability and high-resolution digital tracing of human behavior make large-scale computational models for individual-based realistic simulation available. Reconstructing a virtual computational environment is crucial for designing and implementing individual interactions in an artificial society as human beings behave in the real world. In this paper, we propose a methodology to recreate a virtual city by utilizing statistical data and geographic information. The synthetic population and physical environment are baseline components of the virtual city. Individual-based modeling is used to specify individuals' demographic characteristics, and each individual is endowed with heterogeneous social attributes. Various physical environments are generated with geographic locations and mapped with individuals to support daily mobility, migration, and interaction. A series of algorithms are proposed to bridge the gap between macroscopic data and microscopic models, and guarantee equivalence between them. Based on the methodology, we reconstructed a virtual city of Beijing, and presented the statistical analysis of population structure, spatial distribution of physical environments, human travel characteristics, and spatial topologies of social networks. Our synthetic population can represent individual actors in the form of households and household members, and the synthetic population is statistically equivalent to a real population. The proposed methodology is efficient to recreate a synthetic virtual city and can serve as a base for computational experiments.

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Dynamic traffic assignment on parallel computers in TRANSIMS

Cited by 70 publications

References 11 publications

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

The Multi-Agent Transport Simulation MATSim

Virtual city: An individual-based digital environment for human mobility and interactive behavior

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