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Titel:

Spatio-Temporal Prediction of Freeway Congestion Patterns using Discrete Choice Methods

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Poster
Autor(en):
Metzger, Barbara; Loder, Allister; Kessler, Lisa; Bogenberger, Klaus
Abstract:
Predicting freeway traffic states is, so far, based on predicting speeds or traffic volumes with various methodological approaches ranging from statistical modeling to deep learning. Traffic on freeways, however, follows patterns in space-time like stop-and-go waves or mega jams. These patterns by itself are informative because they propagate in space-time in different ways, e.g., stop-and-go waves exhibit a typical that can range far ahead in time. When these patterns and their propagation beco...     »
Stichworte:
traffic state prediction, mixed logit, congestion patterns, freeway
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Kongress- / Buchtitel:
Transportation Research Board Annual Meeting
Kongress / Zusatzinformationen:
Transportation Research Board Annual Meeting
Ausrichter der Konferenz:
Transportation Research Board Annual Meeting
Datum der Konferenz:
Januar 2022
Publikationsdatum:
17.01.2022
Jahr:
2022
Quartal:
1. Quartal
Monat:
Jan
Seiten:
20
Erscheinungsform:
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