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Digital
Library of the European Council for Modelling and Simulation |
Title: |
Driving Behaviour
Clustering For Realistic Traffic Micro-Simulators |
Authors: |
Alessandro
Petraro, Federico Caselli,
Michela Milano, Marco Lippi |
Published in: |
(2017).ECMS 2017 Proceedings
Edited by: Zita Zoltay
Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi:10.7148/2017 ISBN:
978-0-9932440-4-9/ ISBN:
978-0-9932440-5-6 (CD) 31st European Conference on Modelling and Simulation, Budapest, Hungary, May 23rd
– May 26th, 2017 |
Citation
format: |
Alessandro
Petraro, Federico Caselli,
Michela Milano, Marco Lippi (2017). Driving Behaviour Clustering For Realistic Traffic
Micro-Simulators, ECMS 2017 Proceedings Edited by: Zita
Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi: 10.7148/2017-0018 |
DOI: |
https://doi.org/10.7148/2017-0018 |
Abstract: |
Traffic
simulators are effective tools to support decisions in urban planning
systems, to identify criticalities, to observe emerging behaviours
in road networks and to configure road infrastructures, such as road side units and traffic lights. Clearly the more
realistic the simulator the more precise the insight provided to decisions
makers. This paper provides a first step toward the design and calibration of
traffic micro-simulator to produce realistic behavior. The long-term idea is
to collect and analyse real traffic traces
collecting vehicular information, to cluster them in groups representing
similar driving behaviours and then to extract from
these clusters relevant parameters to tune the micro-simulator. In this paper,
we have run controlled experiments where traffic traces have been synthetized to obtain different driving styles, so that
the effectiveness of the clustering algorithm could be checked on known
labels. We describe the overall methodology and the results already achieved
on the controlled experiment, showing the clusters obtained and reporting
guidelines for future experiments. |
Full
text: |