SAMO: A Sequential Pattern Mining Model for Evaluating Road Criticality in Urban Traffic Networks

Bachir, Nourhan; Zaki, Chamseddine; Harb, Hassan; Billen, Roland

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SAMO: A Sequential Pattern Mining Model for Evaluating Road Criticality in Urban Traffic Networks

Bachir, Nourhan; Zaki, Chamseddine; Harb, Hassan et al.

2024 • 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)

Editorial reviewed

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https://hdl.handle.net/2268/325236

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Disciplines :

Computer science

DOI :

10.1109/VTC2024-Fall63153.2024.10757675

Author, co-author :

Bachir, Nourhan ; Université de Liège - ULiège > Sphères

Zaki, Chamseddine; American University of Middle East

Harb, Hassan; American University of Middle East

Billen, Roland ; Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)

Language :

English

Title :

SAMO: A Sequential Pattern Mining Model for Evaluating Road Criticality in Urban Traffic Networks

Original title :

[en] VeTraSPM: Novel Vehicle Trajectory Data Sequential Pattern Mining Algorithm for Link Criticality Analysis

Publication date :

28 November 2024

Event name :

2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)

Event place :

United States

Event date :

7 October, 2024

Audience :

International

Peer reviewed :

Editorial reviewed

Source :

IEEE Xplore

Additional URL :

https://ieeexplore.ieee.org/document/10757675

Available on ORBi :

since 10 December 2024

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