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Data Evaluation for Continuous Monitoring of Urban Travel

Vallée, Jan ORCID iD icon 1; Ecke, Lisa ORCID iD icon 1; Salbach, Nicolas 1; Vortisch, Peter 1
1 Institut für Verkehrswesen (IFV), Karlsruher Institut für Technologie (KIT)

Abstract:

Key Performance Indicators (KPIs), such as modal split or vehicle kilometres travelled (VKT), are essential for assessing mobility trends and informing policy decisions. Traditionally, such indicators rely on travel survey data, which, while comprehensive, are costly and time-consuming to collect. In recent years, alternative data sources, such as mobile phone data, floating car data, and sensor-based measurements, have become increasingly available, offering new opportunities for more frequent and spatially detailed mobility analyses.
This paper examines various data sources that can be used for KPI calculation, highlighting their strengths and weaknesses. We review existing studies that have successfully combined two or more of these data sources to gain a more comprehensive understanding of travel behavior. The key focus is on methodological challenges of data fusion, including spatial and temporal resolution issues, representativeness, and consistency between datasets.
Furthermore, we discuss the role of travel surveys in supporting data integration. While surveys alone cannot provide continuous travel monitoring, they offer valuable microdata on travel behavior, which can help validate and calibrate other data sources. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000194055
Veröffentlicht am 10.06.2026
Originalveröffentlichung
DOI: 10.1016/j.trpro.2026.04.194
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Verkehrswesen (IFV)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 2352-1465
KITopen-ID: 1000194055
Erschienen in Transportation Research Procedia
Verlag Elsevier
Band 97
Seiten 563–572
Vorab online veröffentlicht am 05.06.2026
Schlagwörter Data Fusion, Travel Surveys, Transport Data, Travel Behavior
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