225 research outputs found
The MATSim Network Flow Model for Traffic Simulation Adapted to Large-Scale Emergency Egress and an Application to the Evacuation of the Indonesian City of Padang in Case of a Tsunami Warning
The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as evacuation of Houston in the case of Hurricane Rita or the evacuation of coastal cities in the case of Tsunamis. This paper describes a complex evacuation simulation framework for the city of Pandang, with approximately 1,000,000 inhabitants. Padang faces a high risk of being inundated by a tsunami wave. The evacuation simulation is based on the MATSim framework for large-scale transport simulations. Different optimization parameters like evacuation distance, evacuation time, or the variation of the advance warning time are investigated. The results are given as overall evacuation times, evacuation curves, an detailed GIS analysis of the evacuation directions. All these results are discussed with regard to their usability for evacuation recommendations.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie
Integrating CEMDAP and MATSIM to Increase the Transferability of Transport Demand Models
At the time of publication C.R. Bhat was at the University of Texas at Austin, while D. Ziemke and K. Nagel were at the University of Berlin.An activity-based approach to transport demand modeling is considered the most behaviorally
sound procedure to assess the impacts of transport policies. In this paper, it is investigated whether
it is possible to transfer an estimated model for activity generation from elsewhere (the estimation
context) and use local area (application context) traffic counts to develop a local area
activity-based transport demand representation. Here, the estimation context is the Dallas-Fort
Worth area, and the application context is Berlin, Germany. Results in this paper suggest that such
a transfer approach is feasible, based on comparison with a Berlin travel survey. Additional studies
in the future need to be undertaken to examine the stability of the results obtained in this paper.Civil, Architectural, and Environmental Engineerin
Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation
This article reports on the calibration and analysis of a fully disaggregate (agent-based) transport simulation for the metropolitan area of Zurich. The agent-based simulation goes beyond traditional transport models in that it equilibrates not only route choice but all-day travel behavior, including departure time choice and mode choice. Previous work has shown that the application of a novel calibration technique that adjusts all choice dimensions at once from traffic counts yields cross-validation results that are competitive with any state-of-the-art four-step model. While the previous study aims at a methodological illustration of the calibration method, this work focuses on the real-world scenario, and it elaborates on the usefulness of the obtained results for further demand analysis purpose
Towards a multi-agent based modeling approach for air pollutants in urban regions
Urban environments are often associated with high traffic density. Especially road traffic is a major source for air pollution in cities. The cause-and-effect chain from the traffic activity towards the concentration of air pollutants is complex. Modeling the outcome needs a lot of inputs in terms of methodology and data. Against this background, an approach is developed that links the agent-based transport model MATSim with the emission factors and traffic situations of HBEFA. The goal is to approximate link travel times as well as the resulting emissions of air pollutants while still being applicable to large-scale scenarios. This paper aims at laying down the foundations for this innovative approach. A test case is developed where link travel times are simulated and the resulting emissions are calculated for MATSim test vehicles. The results are then compared to real-world data. Further, it is discussed how to extend this approach to a large-scale scenario and what prerequisites are needed. Finally, it is analyzed what additional information the model provides in order to achieve a more sustainable transport and urban planning.Urbane Regionen weisen zumeist eine hohe Verkehrsdichte auf. Die durch den Straßenverkehr hervorgerufenen Luftschadstoffemissionen tragen in einem großen Maße zur Luftverschmutzung bei. Der Ursache–Wirkungspfad von der Verkehrsaktivität bis hin zu den Auswirkungen auf die Luftschadstoffkonzentration ist komplex. Seine Abbildung ist methodisch aufwendig und geht mit einem erheblichen Datenaufwand einher. Vor diesem Hintergrund wird ein Ansatz entwickelt, der das agentenbasierte Verkehrsmodell MATSim mit HBEFA Emissionsfaktoren und Verkehrssituationen koppelt. Ziel ist es straßenfeine Reisezeiten und die resultierenden Luftschadstoffemissionen zu approximieren ohne die Anwendbarkeit auf großräumige Szenarien zu verlieren. Diese Studie legt die Grundlagen für diesen innovativen Ansatz. Es wird eine Teststrecke simuliert, für die Reisezeiten und die resultierenden Emissionen eines Testfahrzeugs berechnet werden. Die Ergebnisse werden mit realen Daten verglichen. Des Weiteren wird diskutiert, wie dieser Ansatz auf großräumige Szenarien angewendet werden kann und welche Voraussetzungen dafür nötig sind. Abschließend wird analysiert, welchen Beitrag das Modell für eine nachhaltigere Transport- und Stadtplanung leisten kann
Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation
This article reports on the calibration and analysis of a fully disaggregate (agent-based) transport simulation for the metropolitan area of Zurich. The agent-based simulation goes beyond traditional transport models in that it equilibrates not only route choice but all-day travel behavior, including departure time choice and mode choice. Previous work has shown that the application of a novel calibration technique that adjusts all choice dimensions at once from traffic counts yields cross-validation results that are competitive with any state-of-the-art four-step model. While the previous study aims at a methodological illustration of the calibration method, this work focuses on the real-world scenario, and it elaborates on the usefulness of the obtained results for further demand analysis purposes
Disaggregate path flow estimation in an iterated DTA microsimulation
This text describes the first application of a novel path flow and origin/destination (OD) matrix estimator for iterated dynamic traffic assignment (DTA) microsimulations. The presented approach, which operates on a trip-based demand representation, is derived from an agent-based DTA calibration methodology that relies on an activity-based demand model (Flötteröd et al., 2011a). The objective of this work is to demonstrate the transferability of the agent-based approach to the more widely used OD matrix-based demand representation. The calibration (i) operates at the same disaggregate level as the microsimulation and (ii) has drastic computational advantages over conventional OD matrix estimators in that the demand adjustments are conducted within the iterative loop of the DTA microsimulation, which results in a running time of the calibration that is in the same order of magnitude as a plain simulation. We describe an application of this methodology to the trip-based DRACULA microsimulation and present an illustrative example that clarifies its capabilities
OTSS: Oulu traffic simulation system
Abstract. This thesis presents the design and the implementation of Oulu Traffic Simulation System (OTSS), a traffic simulation system for the City of Oulu, Finland. Following agent-based approach, the simulation generates artificial agents that represent the population synthesis of the City of Oulu. Data from several sources, including official statistics, government-organized open data and crowdsourced information were collected and used as input for the simulation. Two traffic demand models are presented in this thesis: (1) the random model which generates traffic trips as random, discrete events; and (2) the activity-based model which defines traffic trips as sequential events in the agents’ day plan. The software development of the system follows the spiral model of software development and enhancement. During the implementation, several development cycles were conducted before the UML software design. The system was executed on two computation systems to test its real-time performance. To evaluate the traffic models, data extracted from the simulation was compared with aggregated survey data from Finnish Transport Agency and traffic count stations around the city. The results showed that a typical server is capable of running the simulation, and even though there were differences in the duration and distance of individual trips, the simulation reflects real-life traffic count significantly well
Big data for activity based transport models
Our civilization needs to know as much information about itself as possible in order to keep running. One of the important fields is the field of transportation and since we could not measure all the movements happening on planet Earth, we need transport modelling. As of 2018, for the area of a metropolis the four-step model still seems to be a state of practice of modelling transportation. This comes with several disadvantages such as lack of detail (aggregation to zones) or oversimplifying of the travel demand phenomena (trips are not combined into daily schedules). To remedy these disadvantages, the scientific community came up with activity-based models that addressed those issues. The in-creased level of detail has however increased the demand for data. Nowadays the data is obtained from costly travel surveys that make the methodology less viable option for the practitioners. Therefore, in this thesis the focus are possible new sources of data for the model and using the open datasets to build an activity-based model.
First, we examine the existing big data sources and evaluate their usefulness for the model. As a result of this evaluation, we carry on to create synthetic data handling the movements of the studied population, as no big data source related to movement of people was found useful for creating the data suitable for the model.
We used the Capital region of Helsinki, Finland as a region for the case study to deal with the real data environment. The data is generated by disaggregation of statistical data aiming at preserving the variability in a maximum achievable way. Where needed, assumptions are used to forward the process.
Using the synthetic big data a transport model was created. Despite the fact that the ac-curacy of the model in terms of error on link volumes does not reach the level of some other previously developed models, it is still surprisingly precise regarding the idea that solely open data and statistics were used. In the discussion possible synergies with other big datasets is described with respect to the experiences from the case study
SHOW Deliverable 10.1: Simulation scenarios and tools
This document identifies all simulation tools which are used by all partners participating in Work Package 10 of the SHOW project. Their applications range from vehicle level of shared CCAVs up to mobility level, and they are used to enrich all field experiment results of the SHOW pilots. In addition, a relation of tools to application areas and to SHOW pilots is presented. Furthermore, multiple simulation scenarios are introduced,
which define the used tools to evaluate the scenario, their expected results as well as the addressed KPIs from A9.4. After a short presentation of the SHOW sites that are investigated in simulation in this WP, the simulation plans of all participating partners are presented and linked to at least one of the pilot sites. Additionally, data inputs that are required from the SHOW sites are stated
Cadyts a free calibration tool for dynamic traffic simulations
This article reports on the realization and on first applications of the Cadyts (Calibration of dynamic traffic simulations) calibration tool. The presented first version of Cadyts calibrates disaggregate demand models of dynamic traffic assignment simulators from traffic counts. The tool is broadly applicable in that it (i) makes only very mild assumptions about the calibrated simulators workings and (ii) allows for various modes of technical interaction with the simulation software. The article provides a both conceptual and technical overview of the tool and exemplary demonstrates its applicability to two different traffic microsimulators
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