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dc.contributor.author
Makridis, Michail
dc.contributor.author
Leclercq, Ludovic
dc.contributor.author
Ciuffo, Biagio
dc.contributor.author
Fontaras, Georgios
dc.contributor.author
Mattas, Konstantinos
dc.date.accessioned
2020-09-28T12:06:38Z
dc.date.available
2020-09-27T02:47:25Z
dc.date.available
2020-09-28T12:06:38Z
dc.date.issued
2020-11
dc.identifier.issn
0968-090X
dc.identifier.other
10.1016/j.trc.2020.102803
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/442895
dc.description.abstract
Road traffic congestion is the result of various phenomena often of random nature and not directly observable with empirical experiments. This makes it difficult to clearly understand the empirically observed traffic instabilities. The vehicles’ acceleration/deceleration patterns are known to trigger instabilities in the traffic flow under congestion. It has been empirically observed that free-flow pockets or voids may arise when there is a difference in the speeds and the spacing between the follower and the leader increases. During these moments, the trajectory is dictated mainly by the characteristics of the vehicle and the behaviour of the driver and not by the interactions with the leader. Voids have been identified as triggers for instabilities in both macro and micro level, which influence traffic externalities such as fuel consumption and emissions. In the literature, such behaviour is usually reproduced by injecting noise to the results of car-following models in order to create fluctuations in the instantaneous vehicles’ acceleration. This paper proposes a novel car-following approach that takes as input the driver and the vehicle characteristics and explicitly reproduces the impact of the vehicle dynamics and the driver’s behaviour by adopting the Microsimulation Free-flow aCceleration (MFC) model. The congested part of the model corresponds to the Lagrangian discretization of the LWR model and guarantees a full consistency at the macroscopic scale with congested waves propagating accordingly to the first-order traffic flow theory. By introducing naturalistic variation in the driving styles (timid and aggressive drivers) and the vehicle characteristics (specification from different vehicle models), the proposed model can reproduce realistic traffic flow oscillations, similar to those observed empirically. An advantage of the proposed model is that it does not require the injection of any noise in the instantaneous vehicle accelerations. The proposed methodology has been tested by studying a) the traffic flow oscillations produced by the model in a one-lane road uphill simulation scenario, b) the ability of the model to reproduce car-following instabilities observed in three car-following trajectory datasets and c) the ability of the model to produce realistic fuel consumption estimates. The results prove the robustness of the proposed model and the ability to describe traffic flow oscillations as a consequence of the combination of driving style and vehicle’s technical specifications. © 2020 Elsevier Ltd.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
Traffic flow
en_US
dc.subject
Oscillations
en_US
dc.subject
Driver behaviour
en_US
dc.subject
Vehicle dynamics
en_US
dc.subject
Fuel consumption
en_US
dc.subject
Microsimulation
en_US
dc.title
Formalizing the heterogeneity of the vehicle-driver system to reproduce traffic oscillations
en_US
dc.type
Journal Article
dc.date.published
2020-09-22
ethz.journal.title
Transportation Research Part C: Emerging Technologies
ethz.journal.volume
120
en_US
ethz.journal.abbreviated
Transp. res., Part C Emerg. technol.
ethz.pages.start
102803
en_US
ethz.size
20 p.
en_US
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2020-09-27T02:47:35Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-28T12:06:49Z
ethz.rosetta.lastUpdated
2020-09-28T12:06:49Z
ethz.rosetta.versionExported
true
ethz.COinS
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