Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model. (December 2018)

• Record Type: Journal Article
• Authors: Samaras, Christos; Tsokolis, Dimitris; Toffolo, Silvana; Magra, Giorgio; Ntziachristos, Leonidas; Samaras, Zissis
• Is Part Of: Transportation research. Volume 65(2018)
• Page Start: 772
• Page End: 783
• Publication Date: 2018-12
• Subjects: Vehicle emissions -- Congestion -- Micro modelling -- Urban traffic control -- Intelligent transport systems; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2017.10.016
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Novel micro-simulator of coupled traffic and vehicle emission modelling proposed. Approach suitable to use in several traffic cases and powertrain configurations. 47% range in mean diesel car consumption in urban corridor depending on congestion. 6.0–11.9% positive impact of start stop under normal and congested conditions. 4.5% (congested) and 8.1% (normal) mean fleet CO2 decrease by urban traffic control. Abstract: Τhis study demonstrates the combination of a microscopic traffic simulator (AIMSUN) with an instantaneous emissions model (AVL CRUISE) to investigate the impact of traffic congestion on fuel consumption on an urban arterial road. The micro traffic model was enhanced by an improved car-following law according to Morello et al. (2014) and was calibrated to replicate measured driving patterns over an urban corridor in Turin, Italy, operating under adaptive urban traffic control (UTC). The method was implemented to study the impact of congestion on fuel consumption for the category of Euro 5 diesel <1.4 l passenger cars. Free flow and congested conditions led to respective consumption differences of −25.8% and 20.9% over normal traffic. COPERT 5 rather well predicted the impact of congestion but resulted to a much lower relative reduction in free flow conditions. Start and stop system was estimated to reduce consumption by 6% and 11.9% under normal and congested conditions, respectively. Using the same modelling approach, UTC was found to have a positive impact on CO2 emissions of 8.1% and 4.5% for normal and congested conditions, respectively, considering the Turin vehicle fleet mix for the year 2013. Overall, the study demonstrates that the combination of detailed and validated micro traffic and emissions models offers a powerful combination to study traffic and powertrain impacts on greenhouse gas and fuel consumption of on road vehicles over a city network.