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Titel:

A novel Machine-Learning, Multi-Criteria, Centralized Bicycle Routing Algorithm

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Poster
Autor(en):
Dahmen, Victoria; Loder, Allister; Bogenberger, Klaus
Abstract:
In this paper, we present a novel efficient multicriteria route model for bicycles. Efficiency is particularly relevant for handling large-scale routing requests, as is essential for centralized routing services and traffic assignment problems. The multicriteria aspect is crucial in the context of bicycles, since their route choice is heavily influenced by infrastructural and topological factors. We leverage high-density GPS-based route data to optimize the efficient weighted shortest path algor...     »
Stichworte:
Bicycle route choice model; GPS Tracking Data; Data-Driven Optimization; Adaptive Routing Model; Multicriteria Optimization; Machine Learning; GNI
Dewey-Dezimalklassifikation:
000 Informatik, Wissen, Systeme; 620 Ingenieurwissenschaften
Kongress- / Buchtitel:
Transportation Research Board Annual Meeting
Datum der Konferenz:
January 2025
Jahr:
2025
Jahr / Monat:
2025-01
Monat:
Jan
Reviewed:
ja
Sprache:
en
TUM Einrichtung:
Lehrstuhl für Verkehrstechnik
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