Assessment of the impact of speed limit reduction and traffic signal coordination on vehicle emissions using an integrated approach

Madireddy, Madhava Rao; Coensel, Bert De; Can, Arnaud; Degraeuwe, Bart; Beusen, Bart; Vlieger, Ina De; Botteldooren, Dick

doi:10.1016/j.trd.2011.06.001

Cited by 138 publications

(59 citation statements)

References 11 publications

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“…approach is a refinement of conventional traffic noise prediction models in which emission calculations are based only on average speeds and intensities [30][31][32]. However, the state-of-the-art vehicle noise emission models [for example those used in the FHWA Traffic Noise Model or the European Imagine model, 33] still consider a single, prototypical emission law for each vehicle category.…”

Section: Introductionmentioning

confidence: 99%

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Coensel¹,

Brown²,

Tomerini³

2016

Applied Acoustics

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Annoyance, sleep disturbance and other health effects of road traffic noise exposure may be related to both level and number of noise events caused by traffic, not just to energy equivalent measures of exposure. Dynamic traffic noise prediction models that include instantaneous vehicle noise emissions can be used to estimate either of these measures. However, current state-of-the-art vehicle noise emission models typically consider a single emission law for each vehicle category, whereas measurements show that the variation in noise emission between vehicles within the same category can be considerable. It is essential that the influence of vehicles that are producing significantly more (or less) noise than the average vehicle are taken into account in modelling in order to correctly predict the levels and frequency of occurrence of road traffic noise events, and in particular to calculate indicators that characterize these noise events. Here, an approach for predicting instantaneous sound levels caused by road traffic is presented, which takes into account measured distributions of sound power levels produced by individual vehicles. For the setting of a receiver adjacent to a dual-lane road carrying free flow traffic, the effect of this approach on estimated percentile levels and sound event indicators is investigated. • The software is freely available as a Python plugin to the Aimsun microscopic traffic simulator.• Simulations show that this refined approach affects estimated percentile sound levels by up to 4 dB.• The influence of the approach on indicators for the number of noise events is illustrated.

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Section: Introductionmentioning

confidence: 99%

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Coensel¹,

Brown²,

Tomerini³

2016

Applied Acoustics

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“…It is considered that transport policies such as speed control, traffic signal coordination, Intelligent Transport System (ITS), public transport improvement, railway construction, and road network planning, will exert a positive influence on traffic volume, modal shift, and GHG emissions [52][53][54][55], but the impacts on other industrial sectors have not been clarified because transport models are rarely appropriately integrated into global CGE models. Our iterative coupling model is a practical tool for investigating how to keep the balance between transport-related GHG emission reduction and economic development.…”

Section: Mitigation Scenariomentioning

confidence: 99%

Contribution of the transport sector to climate change mitigation: Insights from a global passenger transport model coupled with a computable general equilibrium model

et al. 2018

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A passenger transport model, Asia-pacific Integrated Model (AIM)/Transport, incorporating travelers' mode of choice and transport technological details was developed in this study. This AIM/Transport was coupled with the AIM/Computable General Equilibrium (AIM/CGE) to capture interactive mechanisms between the transport sector, energy consumption, greenhouse gas (GHG) emissions, and the macro-economy. This paper presents the model structure and mathematical formulation of AIM/Transport, and explains how it was integrated with the CGE model by an iterative algorithm, taking into consideration the feedback between AIM/Transport and AIM/CGE. A numerical simulation proved that the integration of AIM/CGE and AIM/Transport can achieve a convergence after 13 iterations. A business-as-usual (BaU) scenario and a mitigation scenario were created to test the robustness of the model integration and how the mitigation potential and cost would be modified by coupling AIM/Transport. The key finding was that the carbon price and mitigation cost were modified with the coupled CGE-Transport model.

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“…PTV VISSIM lists ENviVer (based on VERSIT+) as a plug-in for emission and energy modelling (PTV Group, n.d.), but there are also examples of ad-hoc linkages with MOVES (Abou-Senna and Radwan, 2013), PHEM (Hirschmann et al, 2010) and CMEM (Stevanovic et al, 2009). Quadstone Paramics, another commercial microsimulation tool has been used in conjunction with VERSIT+ (Madireddy et al, 2011), MOVES (Xie et al, 2012) and CMEM (Boriboonsomsin and Barth, 2008;Misra et al, 2013). CMEM was also used in a study of Lee et al (2009), while the energy model VT-micro was used with TRANSIMS (Kwak et al, 2012).…”

Section: Energy Modelling In Transportationmentioning

confidence: 99%

Assessing the energy impact of traffic management and vehicle hybridisation

Karbowski¹,

Kim²,

Auld³

et al. 2016

IJCAST

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Abstract:We provide a review of methodologies previously used to evaluate impacts of transportation systems and changes in transportation infrastructure on energy consumption. We present a new framework that allows estimating the energy impacts of managed traffic lanes in the context of vehicle automation. The presented framework relies on two major components, an integrated transportation system simulator and a powertrain simulator. For the transportation system simulator we propose using integrated transportation system simulator POLARIS. For the powertrain simulator we use AUTONOMIE, a tool funded by the US Department of Energy. Both tools are developed at Argonne National Laboratory. We demonstrate our approach by modelling a transportation corridor along a major highway. Two scenarios are considered, unmanaged, when both trucks and cars use all the lanes of the highway and managed, under which one of the highway lanes is a dedicated lane for truck traffic and trucks are forming platoons using adaptive cruise control technology. We provide the numerical results of the experiment at the end of the paper. We also present the impact of vehicle hybridisation combined with automation on the energy consumption.Keywords: travel demand; traffic microsimulation; energy assessment; integrated modelling; powertrain simulation. Namwook Kim is an Assistant Professor at Department of Mechanical Engineering Hanyang University. His research area is in developing, validating, and evaluating simulation models for advanced vehicles. Dynamics, optimisation, and optimal control theory are vigorously used for these studies, and optimal control for hybrid electric vehicles was the theme of his dissertation.

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Assessment of the impact of speed limit reduction and traffic signal coordination on vehicle emissions using an integrated approach

Cited by 138 publications

References 11 publications

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Contribution of the transport sector to climate change mitigation: Insights from a global passenger transport model coupled with a computable general equilibrium model

Assessing the energy impact of traffic management and vehicle hybridisation

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