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Modelling Eco-Driving Support System for Microscopic Traffic Simulation
Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.ORCID iD: 0000-0002-0336-6943
Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.ORCID iD: 0000-0003-0767-5169
University of Leeds.
TNO.
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2019 (English)In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2019, article id 2162568Article in journal (Refereed) Published
Abstract [en]

Microscopic traffic simulation is an ideal tool for investigating the network level impacts of eco-driving in different networks and traffic conditions, under varying penetration rates and driver compliance rates. The reliability of the traffic simulation results however rely on the accurate representation of the simulation of the driver support system and the response of the driver to the eco-driving advice, as well as on a realistic modelling and calibration of the driver's behaviour. The state-of-the-art microscopic traffic simulation models however exclude detailed modelling of the driver response to eco-driver support systems. This paper fills in this research gap by presenting a framework for extending state-of-the-art traffic simulation models with sub models for drivers' compliance to advice from an advisory eco-driving support systems. The developed simulation framework includes among others a model of driver's compliance with the advice given by the system, a gear shifting model and a simplified model for estimating vehicles maximum possible acceleration. Data from field operational tests with a full advisory eco-driving system developed within the ecoDriver project was used to calibrate the developed compliance models. A set of verification simulations used to illustrate the effect of the combination of the ecoDriver system and drivers' compliance to the advices are also presented.

Place, publisher, year, edition, pages
WILEY-HINDAWI , 2019. Vol. 2019, article id 2162568
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:vti:diva-14812DOI: 10.1155/2019/2162568ISI: 000505993700004Scopus ID: 2-s2.0-85077677663OAI: oai:DiVA.org:vti-14812DiVA, id: diva2:1387972
Available from: 2020-01-23 Created: 2020-01-23 Last updated: 2020-01-23Bibliographically approved

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Olstam, JohanBernhardsson, Viktor

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