Super-Poissonian Statistics In Traffic Flow
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F20%3A00347538" target="_blank" >RIV/68407700:21340/20:00347538 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082391021&partnerID=40&md5=03a9ad5cd9e27e95ab7bd668b0effc23" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082391021&partnerID=40&md5=03a9ad5cd9e27e95ab7bd668b0effc23</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Super-Poissonian Statistics In Traffic Flow
Original language description
We utilize number variance, a statistical tool originating from Random Matrix Theory, to investigate the nature and level of correlation among vehicles in real road two-lane traffic data. We show that while for both fast and slow lane the number variance is non-Poissonian, indicating a strong correlation between vehicles, the nature of the correlation itself differs lane by lane considerably. For the slow lane, the number variance exhibits a sub-Poissonian behaviour, similar to a short-ranged Dyson gas, and follows the predictions of Random Matrix Theory. For the fast lane, however, the number variance enters for certain densities a super-Poissonian regime, indicating that the system can’t be described by a short-ranged repulsive interaction only. We further show that the systems behaviour can be explained by a so called “vehicle bunching” effect, which is a result of lane-change behaviour originating in the slow lane, and which has remarkable similarities to an effect observed in thermal light photon counting experiments in quantum optics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
19th Conference on Applied Mathematics Aplimat 2020 proceedings
ISBN
978-80-227-4983-1
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
930-941
Publisher name
Slovak University of Technology
Place of publication
Bratislava
Event location
Bratislava
Event date
Feb 4, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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