A new method to calculate emissions with simulated traffic conditions

Hirschmann, Karin; Zallinger, Michael Stefan; Fellendorf, Martin; Hausberger, Stefan

doi:10.1109/itsc.2010.5625030

Cited by 35 publications

(27 citation statements)

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“…In Table 4 the applied value ranges and number of levels are sum- seconds, which is the minimum/maximum values measured at the three intersections investigated in [9], minus/plus two times the standard deviation (compare Table 1 The result is a feasible region for possible parameter combinations to achieve a saturation flow rate and start up delay as measured during snowy road conditions (see Figure 5). As the preparation of trajectory data from video data is a very costly process, measurements of time headways at local detectors or driving cycles recorded with GPS tracking devices can be used as additional information for calibration [8]. For a complete simulation of traffic at intersections, reduction of saturation flow rates on turning lanes due to adverse weather conditions has to be investigated.…”

Section: Calibration Resultsmentioning

confidence: 99%

“…Important examples are the impact of Variable Message Signs on speed adaptation of drivers and signal timing optimisation and its impact on traffic performance and traffic-related emissions (see e.g. [7], [8]). Thus microscopic traffic simulators like VISSIM are important tools for improving existing and introducing new Intelligent Transportation Systems (ITS).…”

Section: Introductionmentioning

confidence: 99%

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Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Asamer

Zuylen

Heilmann

2013

IET Intelligent Transport Systems

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Section: Calibration Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Asamer

Zuylen

Heilmann

2013

IET Intelligent Transport Systems

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“…Additionally, micro-RTMs are typically calibrated and validated for aggregate traffic measures (e.g. traffic average speed, traffic flow and average delay) rather than for driving patterns of individual vehicles (Hirschmann et al 2010;Song, Yu, and Zhang 2012;Toffolo et al 2013;Song, Yu, and Xu 2013). Therefore, driving pattern outputs from micro-RTMs are rarely properly validated, and do not necessarily accurately represent the real-world (Song, Yu, and Zhang 2012;Song, Yu, and Xu 2013), whereas link-level traffic variable outputs are more likely to be accurate.…”

Section: Discussionmentioning

confidence: 99%

Local government authority attitudes to road traffic CO₂ emissions modelling: a British case study

Grote

Williams

Preston

et al. 2016

Transportation Planning and Technology

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Local government authorities (LGAs) play a key role in facilitating mitigation of road traffic CO 2 emissions and must engage in emissions modelling to quantify the impact of transport interventions. Existing Emissions Model (EM) methodologies range from aggregate to disaggregate approaches, with more detail normally entailing more resources. However, it is not clear which approaches LGAs actually utilise. This article reports results of a survey designed to discover the level of detail considered practical by British LGAs (n = 34). Results show that resource scarcity is important, with particular importance attached to EM reusability and convenient input data sources. Most LGA EMs use traffic variable inputs (predominantly traffic flow and traffic average speed), with this approach being the best-fit for LGA resources. Link-by-link sources of data rated highly for convenience are Road Traffic Models and Urban traffic control systems. ARTICLE HISTORY

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“…Additionally, similar macroscopic emission models are typically unable to capture certain microscopic behavior accurately (see, e.g., Ahn and Rakha, 2008). Hirschmann et al (2010) link the microscopic tra c ow simulator VISSIM (Verkehr In Städten -SImulationsModell) with the instantaneous emission model PHEM (Passenger Car and Heavy-duty Emission Model).…”

Section: Integrated Approaches For Modeling Transport and Emissionsmentioning

confidence: 99%

The Multi-Agent Transport Simulation MATSim

Axhausen¹

2016

479

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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A new method to calculate emissions with simulated traffic conditions

Cited by 35 publications

References 0 publications

Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Local government authority attitudes to road traffic CO₂ emissions modelling: a British case study

The Multi-Agent Transport Simulation MATSim

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A new method to calculate emissions with simulated traffic conditions

Cited by 35 publications

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Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Local government authority attitudes to road traffic CO2 emissions modelling: a British case study

The Multi-Agent Transport Simulation MATSim

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Local government authority attitudes to road traffic CO₂ emissions modelling: a British case study