Clustering di tracce di mobilità per l’identificazione di stili di guida

Petraro, Alessandro (2017) Clustering di tracce di mobilità per l’identificazione di stili di guida. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria informatica [LM-DM270]
Documenti full-text disponibili:
[img] Documento PDF (Thesis)
Disponibile con Licenza: Creative Commons: Attribuzione - Non commerciale - Condividi allo stesso modo 3.0 (CC BY-NC-SA 3.0)

Download (9MB)


Traffic simulators are effective tools to support decisions in urban planning systems, to identify criticalities, to observe emerging behaviours in road networks and to configure road infrastructures, such as road side units and traffic lights. Clearly the more realistic the simulator the more precise the insight provided to decision makers. This paper provides a first step toward the design and calibration of traffic micro-simulator to produce realistic behaviour. The long term idea is to collect and analyse real traffic traces collecting vehicular information, to cluster them in groups representing similar driving behaviours and then to extract from these clusters relevant parameters to tune the microsimulator. In this paper we have run controlled experiments where traffic traces have been synthetized to obtain different driving styles, so that the effectiveness of the clustering algorithm could be checked on known labels. We describe the overall methodology and the results already achieved on the controlled experiment, showing the clusters obtained and reporting guidelines for future experiments.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Petraro, Alessandro
Relatore della tesi
Correlatore della tesi
Corso di studio
Ordinamento Cds
Parole chiave
Agent-based modelling,Traffic Micro Simulators,Clustering Algorithms,SUMO
Data di discussione della Tesi
14 Marzo 2017

Altri metadati

Statistica sui download

Gestione del documento: Visualizza il documento