2013 - EU - Modelling Infrastructure Influence on RoAd Vehicle Energy Consumption
MIRAVEC Report D5.3. The objective of MIRAVEC was to build on existing knowledge and models in order to achieve a more holistic view considering a broad variety of effects. The project results are compiled in this final report of MIRAVEC project. The first part of this final report is a short summary on the findings and outputs of all Work Packages (WP), while the second part is a summary of all recommendations to National Road Administrations (NRAs) on how to implement the findings, models and tools in pavement and asset management systems. The main findings and recommendations of the project can be summarised as follows: Five major groups of parameters influencing road vehicle energy and fuel consumption were identified, of which a subset was selected based on impact, potential for influence by National Roads Administrations and integration into existing fuel consumption models. Further analysis showed that while currently monitored parameters can be used for modelling several effects of the infrastructure influence, knowledge gaps remain with respect to other parameters and the correct modelling of associated effects. There is no current model which takes all infrastructure-related effects into account. Most models for fuel consumption and CO2 emission of road vehicles focus on vehicle and traffic flow characteristics and tend to neglect details of the infrastructure. The Swedish VETO model is one of the most advanced models in this respect and was the basis of many analyses. As the knowledge about the infrastructure influence increases, these models offer the possibility to integrate this knowledge into decision making. The spreadsheet tool developed in WP3 allows the comparison of the effects of different infrastructure-related measures on fuel consumption and CO2 emission. It requires data about the most widely available pavement and road layout parameters and uses information about traffic flow and vehicles as background information. While the tool can be applied even with limited data, the strong influence of these background data found in the analysis may supersede the infrastructure effects in some cases. The investigation of the current situation with regard to the occurrence of this topic in pavement and asset management found a growing awareness of its importance with road managers, but so far very limited implementation in the actual systems. While future models based on the more commonly monitored infrastructure parameters will make the integration of vehicle CO2 emission feasible, acceptance and weight in decision making in the view of limited financial resources for maintenance still remain to be achieved.
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