Open Access
Explanation of Complex Dynamics of Congested Traffic in NGSIM Data with Three-Phase Traffic Theory
Boris S. Kerner,Sergey L. Klenov +1 more
TLDR
In this article, an explanation of congested traffic in NGSIM-data in the context of the three-phase traffic theory is presented, which is explained by the nucleation-interruption effect occurring in metastable synchronized flow.Abstract:
An explanation of congested traffic in NGSIM-data in the context of the three-phase traffic theory is presented. Complex spatiotemporal dynamics of moving jams observed in NGSIM-data is explained in three-phase traffic theory by the nucleation-interruption effect occurring in metastable synchronized flow. The nucleation-interruption effect in metastable synchronized flow is associated with the dual role of lane changing in the synchronized flow as well as with the vehicle merging from on-ramps onto the main road and from the main road to off-ramps. The dual role of lane changing is as follows: lane changing can lead either to the occurrence of a growing moving jam or to the jam dissolution in metastable synchronized flow.read more
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Three phase classification of an uninterrupted traffic flow: a $k$-means clustering study
TL;DR: In this article, the authors investigated the speed time series of the vehicles recorded by a camera at a section of a highway in the city of Isfahan, Iran Using $k$-means clustering algorithm, they find that the natural number of clustering for this set of data is $3$ This is in agreement with the three-phase theory of uninterrupted traffic flows.
Journal ArticleDOI
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Journal Article
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TL;DR: An innovative method for identifying the traffic phases has been proposed based on the existing traffic stream models along with the new findings of the authors’ empirical data analysis and successfully applied in the case study for evaluating the new length-based vehicle classification models with dual-loop data.
Proceedings ArticleDOI
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TL;DR: A hybrid method that incorporates level of service and K-means clustering methods for identifying traffic phases from dual-loop data and applies the "phase representative variables" to represent traffic characteristics in the traffic flow phase identification algorithm is presented.