Modeling different penetration rates of eco-driving in urban areas: Impacts on traffic flow and emissions

Autor: Cristina Valdes, Andres Monzon, Alvaro Garcia-Castro, Manuel G. Romana
Rok vydání: 2016
Předmět:
Zdroj: International Journal of Sustainable Transportation, ISSN 1556-8318, 2016-11, Vol. 11, No. 4
Archivo Digital UPM
instname
ISSN: 1556-8334
1556-8318
Popis: Climate change and air quality are two main environmental challenges in metropolitan areas. As road transportation is one of the main contributors, public administrations are facing these problems with a number of complementary policy measures: shift to cleaner modes, new fuels and vehicle technologies, demand management, and the use of information and communication technologies (ICT) applied to transportation. Eco-driving is one of the measures that present large fuel savings at individual level. Although these savings are well documented in the literature, few studies focus on how eco-drivers driving patterns affect the surrounding vehicles and the traffic in general, and more particularly what would be the impact when the number of eco-drivers grows. Using a traffic microsimulation tool, four models in urban context have been built, corresponding to the different types of urban roads. Both the base-case and the parameters setting to simulate eco-driving have been calibrated with real data collected through floating vehicles performing the trips with normal and eco behaviors. In total, 72 scenarios were simulated, varying the type of road, traffic demand, and the percentage of eco-drivers. Then, the CO2 and NOx emissions have been estimated through a microscopic emission model. The results show that in scenarios with low or medium demand levels and increasing number of eco-drivers, the effects are positive in terms of emissions. On the other side, with high percentage of eco-drivers and high traffic demand, the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.
Databáze: OpenAIRE