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Long-distance mode ...
Long-distance mode choice model estimation using mobile phone network data
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- Andersson, Angelica (författare)
- Statens väg- och transportforskningsinstitut,Linköpings universitet,Kommunikations- och transportsystem,Tekniska fakulteten,VTI Swedish National Road and Transport Research Institute, Sweden,Trafikanalys och logistik, TAL,Linköping University, Sweden
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- Engelson, Leonid, 1955- (författare)
- Linköpings universitet,Kommunikations- och transportsystem,Tekniska fakulteten,Linköping University, Sweden
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- Börjesson, Maria, 1974- (författare)
- Statens väg- och transportforskningsinstitut,Linköpings universitet,Nationalekonomi,Filosofiska fakulteten,VTI Swedish National Road and Transport Research Institute, Sweden,Transportekonomi, TEK,Linköping University, Sweden
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- Daly, Andrew (författare)
- ITS, University of Leeds, United Kingdom
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- Kristoffersson, Ida, 1980- (författare)
- Statens väg- och transportforskningsinstitut,Trafikanalys och logistik, TAL,VTI Swedish National Road and Transport Research Institute, Sweden
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(creator_code:org_t)
- Elsevier, 2022
- 2022
- Engelska.
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Ingår i: Journal of Choice Modelling. - : Elsevier. - 1755-5345. ; 42
- Relaterad länk:
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https://doi.org/10.1...
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https://liu.diva-por... (primary) (Raw object)
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- In this paper we develop two methods for the use of mobile phone data to support the estimation of long-distance mode choice models. Both methods are based on logit formulations in which we define likelihood functions and use maximum likelihood estimation. Mobile phone data consists of information about a sequence of antennae that have detected each phone, so the mode choice is not actually observed. In the first trip-based method, the mode of each trip is inferred by a separate procedure, and the estimation process is then straightforward. However, since it is not always possible to determine the mode choice with certainty (although it is possible in the majority of cases), this method might give biased results. In our second antenna-based method we therefore base the likelihood function on the sequences of antennae that have detected the phones. The estimation aims at finding a parameter vector in the mode choice model that would explain the observed sequences best. The main challenge with the antenna-based method is the need for detailed resolution of the available data. In this paper we show the derivation of the two methods, that they coincide in case of certainty about the chosen mode and discuss the validity of assumptions and their advantages and disadvantages. Furthermore, we apply the first trip-based method to empirical data and compare the results of two different ways of implementing it.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
Nyckelord
- Demand model
- Mode choice
- Mobile phone network data
- Travel behaviour
- Long-distance travel
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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