Abstract This paper presents a methodology to extract a series of passenger indicators from anonymized mobile phone records, with the aim of improving the available knowledge on passenger needs, behaviors and characteristics. The methodology is validated against the information provided by passenger surveys at the Madrid-Barajas Airport. The research shows the potential of anonymized mobile phone records to complement and enrich the information provided by passenger surveys regarding airport catchment areas, intermodality and passenger behavior. This methodology is then applied to the study of air travel demand in Madrid-Barajas Airport in July 2020, two weeks after the COVID-19 lockdown period in Spain. Finally, we discuss how the information extracted from the fusion of mobile phone records and passenger surveys can be leveraged for the modelling and evaluation of novel intermodal solutions.
Highlights We develop a methodology for exploiting mobile phone records in combination with surveys to characterize passenger behaviour. •The use of open source cell network data enabled the reconstruction of door-to-door international trips. •The characterization of the catchment area and access modes offers similar results to passenger surveys. •Surveys can be exploited to calibrate passenger purpose models to be applied to the mobile phone records datasets. •The methodology was successfully applied to a study period after COVID-19 outbreak, when there was limited opportunity for surveying passengers.
A methodology for understanding passenger flows combining mobile phone records and airport surveys: Application to Madrid-Barajas Airport after the COVID-19 outbreak
2021-11-11
Article (Journal)
Electronic Resource
English
Focus on Spain - Madrid Barajas Airport
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