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Abstract

The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems). The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome. (C) 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of the Programme Committee of the Transport Research Arena 2012
Procedia - Social and Behavioral Sciences 48 ( 2012 ) 3418 – 3427
1877-0428 © 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of the Programme Committee of the Transport Research
Arena 2012
doi: 10.1016/j.sbspro.2012.06.1306
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Available online at www.sciencedirect.com
© 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of the Programme Committee of the
Transport Research Arena 2012 Open access under CC BY-NC-ND license.
Open access under CC BY-NC-ND license.
3419
Zissis Samaras et al. / Procedia - Social and Behavioral Sciences 48 ( 2012 ) 3418 – 3427
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Zissis Samaras et al. / Procedia - Social and Behavioral Sciences 48 ( 2012 ) 3418 – 3427
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... The link between these two modules could be obtained by adopting different approaches, according to the geographical scale, the temporal horizon, the drivers' behavior and the simplifications decided by the modelers. Samaras et al. (2012) propose a division of the methods into the macro and micro scale. In the next sub-sections, the characteristics of the two approaches are presented for both transport modelling (section 2.1) and for CO2 emission modules (section 2.2). ...
... A full assessment of ICT related impacts is a challenging task, because the mechanisms through which ICT solutions affect CO2 emissions depend on the vehicle fleet and technology, the mean speed and the speed variation. Any evaluation has to take into account the real-world driving patterns of the single vehicles and the drivers' behaviors and decisions, which affect the nature of the transport demand itself, the modal split, the route choice, the trip timing, the quantities and types of vehicles using the overall transport network (Samaras et al., 2012). Klunder et al. (2009) reviewed the models that are suitable to evaluate the impacts of three classes of ICT-related measures (eco-solutions, traffic management, Advanced Driver Assistance Systems, ADAS) on road traffic CO2 emissions. ...
... The ADVANCE model, for instance, was used to evaluate the power train derived from the conversion of a Volkswagen New Beetle into a hybrid vehicle. Samaras et al. (2012) developed an integrated methodology that can be used to quantify the impacts of various ICT solutions for road transport CO 2 emissions at two inter-linked levels, thus combining benefits from both micro and macro modelling. Firstly, it designs and develops some new modules and interfaces to link existing traffic and emission models at the micro-scale (real-world driving pattern and traffic behavior of passenger cars and instantaneous 7 emission models). ...
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To quantify CO2 emissions from road transport, literature suggests the adoption of several alternative methods, based on transport modelling and carbon modules. Some of these methods are labelled as a micro approach and others as a macro approach. Their distinction is made according to the temporal and spatial horizons, the aim of the study and the degree of accuracy required. This paper presents these methods and discusses their appropriateness, whereby special focus is laid on the potential of the micro approach on ICT, based on a literature review of several European projects. We conclude that the adoption of the micro approach, is quite promising – mostly at the urban level, despite the computational efforts required and the technical difficulties to model driver behaviors. Thus, further research is required to overcome the numerous sources of scientific uncertainties.
... Various initiatives have tried to developed different approaches to simulate the effects of ICT measures on emissions, although the estimation of road transport externalities has to consider several uncertainties (Korzhenevych et al., 2014) and the existing emissions calculation methodologies have significant limitations in terms of data availability and reliability (Grote et al., 2016). Moreover, several studies have outlined a number of additional shortfalls of the existing traffic and emission models which are used to predict the impacts of ICT on mobility (Samaras et al., 2012) making each methodology more unreliable. ...
... The ICT-Emissions project proposed a methodology based on the integration of various simulation models (vehicle control model, traffic model and emissions model) in order to estimate the impacts of ICT technologies on carbon dioxide emissions (Monzon et al., 2017). The combination of the different models require several sources of information and also data collection to acquire the necessary input data (Samaras et al., 2012) but in most cases governments and transport authorities lack the resources for modelling and data experiments (Grote et al., 2016). The ICT-Emissions methodology is aiming to simulate with great accuracy the effects of the measures (Monzon et al., 2017), although the use of complex models has greater demand of input data in terms details which is more sensitive in regards of estimation and collection (Grote et al., 2016). ...
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... Air pollution is, therefore, a complex problem that poses multiple challenges in terms of management and mitigation and has been studied several times in the case of air quality, emissions etc. (Brand et. al., 2012), (Samaras et al., 2012). Effective action to reduce the impacts of air pollution requires a good understanding of the sources that cause it, as well as up-to-date knowledge of air quality status and its impact on humans and on ecosystems (European Environmental Agency, 2015). ...
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In recent years, road transport models have developed for better estimation of road traffic emissions with higher and higher temporal and spatial resolution, to be used as a tool in air quality management for the better living. Road transport related emission models are becoming more and more complex. In this paper, the key research question is how the improvement in modelling influences the results? The authors compared three different macro emission modelling system with the dataset of Hungary for 2010. One must notice that more precise model has larger data requirement. Firstly, the consumption-based model was run with 31 needed input data secondly, EURO standard based model was run with 261 needed data and finally, speed dependent model was run with 1060 needed input data. According to the results, it can be stated that a more complex model could cause significant differences in emission compared to simpler one. The differences can be caused by old Hungarian vehicle fleet or differences in estimation error.
... I It was assumed that the distribution of fuel consumption is a normal Gauss distribution with the expected value of 9.5 liter/100 km in case of gasoline and 7.6 liter/100 k m of diesel oil (Kousoulidou et al., 2012;Samaras et al., 2012). II The ratio of diesel vehicles (β=0,25) is considered equal to the national average (Emőd and Török, 2010). ...
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