Modelling instantaneous traffic emission and the influence of traffic speed limits

Panis, Luc Int; Broekx, Steven; Liu, Ronghui

doi:10.1016/j.scitotenv.2006.08.017

Cited by 294 publications

(127 citation statements)

References 19 publications

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“…In addition, the results of this study address previous conclusions (Int Panis et al, 2006) regarding evaluating speed management policies in Europe through modeling instantaneous traffic emissions and the influence of using an average speed approach. Int Panis et al concluded that active speed management has no significant impact on pollutant emissions.…”

Section: Resultssupporting

confidence: 66%

“…Int Panis et al concluded that active speed management has no significant impact on pollutant emissions. They also concluded that "the analysis of the environmental impacts of any traffic management and control policies is a complex issue and requires detailed analysis of not only their impact on average speeds but also on other aspects of vehicle operation such as acceleration and deceleration" (Int Panis et al, 2006). This study limited the pollutants to only CO 2 , CO, PM2.5, PM10 and NOx; however, methods have been demonstrated that can be used for other mobile-source pollutants.…”

Section: Resultsmentioning

confidence: 99%

“…In an earlier attempt by Int Panis et al (2006) to model instantaneous traffic emissions and the influence of traffic speed limits, they concluded that the speed management impact on vehicle emissions is complex. The frequent acceleration and deceleration movements in the network may significantly reduce the benefits of changing the overall average speed.…”

Section: Literature Reviewmentioning

confidence: 99%

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Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway

Abou-Senna

Radwan

Westerlund

et al. 2013

Journal of the Air & Waste Management Association

100

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The Intergovernmental Panel on Climate Change (IPCC) estimates that baseline global GHG emissions may increase 25-90% from 2000 to 2030, with carbon dioxide (CO 2 ) emissions growing 40-110% over the same period. On-road vehicles are a major source of CO 2 emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, for example, carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). Therefore, the need to accurately quantify transportation-related emissions from vehicles is essential. The new U.S. Environmental Protection Agency (EPA) mobile source emissions model, MOVES2010a (MOVES), can estimate vehicle emissions on a second-by-second basis, creating the opportunity to combine a microscopic traffic simulation model (such as VISSIM) with MOVES to obtain accurate results. This paper presents an examination of four different approaches to capture the environmental impacts of vehicular operations on a 10-mile stretch of Interstate 4 (I-4), an urban limited-access highway in Orlando, FL. First (at the most basic level), emissions were estimated for the entire 10-mile section "by hand" using one average traffic volume and average speed. Then three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-by-second link drive schedules (LDS), and second-by-second operating mode distributions (OPMODE). This paper analyzes how the various approaches affect predicted emissions of CO, NOx, PM2.5, PM10, and CO 2 . The results demonstrate that obtaining precise and comprehensive operating mode distributions on a secondby-second basis provides more accurate emission estimates. Specifically, emission rates are highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach.Implications: Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways.

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Section: Resultssupporting

confidence: 66%

Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway

Abou-Senna

Radwan

Westerlund

et al. 2013

Journal of the Air & Waste Management Association

100

View full text Add to dashboard Cite

show abstract

“…Simulation results can be obtained throughout the evolution and on not just the means but also variances and probability distributions both within-day and between days. The full details of the DRACULA suite of models and their applications have been reported elsewhere (e.g., Hollander and Liu, 2008;Liu et al, 2006;Liu and Tate, 2004;Panis et al, 2006) and will therefore not be detailed herein.…”

Section: Dracula -A Microscopic Simulation Dta Modelmentioning

confidence: 99%

Disaggregate Path Flow Estimation in an Iterated Dynamic Traffic Assignment Microsimulation

Flötteröd

Liu

2013

Journal of Intelligent Transportation Systems

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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. 2The 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.

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“…Namdeo et al 2002;or Nejadkoorki et al 2008); and microscopic traffic flow models with instantaneous or power-based emission models (e.g. Rakha and Ahn 2004;or Int Panis et al 2006). However, macroscopic traffic flow models, which represent traffic as a continuum and consider only aggregate traffic behaviour, have recently been integrated with different types of emission models in an attempt to improve on the low-fidelity of whole-link traffic flow models while avoiding the high costs associated with microscopic traffic flow models in terms of their computation, data requirements, and calibration.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Propagation from the Cell Transmission Traffic Flow Model to Emission Predictions: A Data-Driven Approach

Sayegh¹,

Connors²,

Tate³

2018

Transportation Science

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Road traffic exhaust emission predictions are used to inform transport policy and investment decisions aimed at reducing emissions and achieving sustainable mobility. Emission predictions are also used as inputs when modelling air quality and human exposure to traffic-related air pollutants.To be effective, such policies and/or integration must be based on robust models that not only provide point-based predictions, but also inform these with an interval of confidence that properly accounts for the propagation of uncertainties through the complex chain of models involved. This paper develops a data-driven methodological framework which enables calculating the uncertainty in average speed-based emission predictions induced by uncertainty in its traffic data inputs which are most often predictions (or outputs) of traffic flow models. An ensemble-based optimisation approach is used to estimate both calibration and validation errors arising from uncertainty in the structure and parameterisation of the Cell Transmission Model (CTM); a discretised first-order macroscopic traffic flow model that is often integrated with average speed-based emission models. A Monte Carlo sampling approach is proposed to propagate the uncertainty in traffic flow inputs to emission predictions. To ensure transferability of findings, this methodology has been tested using multiple real data sets on three motorway road networks, one of which operates under Variable Speed Limits (VSL).

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Modelling instantaneous traffic emission and the influence of traffic speed limits

Cited by 294 publications

References 19 publications

Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway

Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway

Disaggregate Path Flow Estimation in an Iterated Dynamic Traffic Assignment Microsimulation

Uncertainty Propagation from the Cell Transmission Traffic Flow Model to Emission Predictions: A Data-Driven Approach

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