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Estimating flexible route choice models using sparse data

Fadaei, Masoud (author)
KTH,Transport- och lokaliseringsanalys,Centrum för transportstudier, CTS
Sundberg, Marcus (author)
KTH,Transport- och lokaliseringsanalys,Centrum för transportstudier, CTS
Karlström, Anders (author)
KTH,Transport- och lokaliseringsanalys,Centrum för transportstudier, CTS
 (creator_code:org_t)
IEEE conference proceedings, 2012
2012
English.
In: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on. - : IEEE conference proceedings. - 9781467330640 ; , s. 1215-1220
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • GPS and nomad devices are increasingly used to provide data from individuals in urban traffic networks. In many different applications, it is important to predict the continuation of an observed path, and also, given sparse data, predict where the individual (or vehicle) has been. Estimating the perceived cost functions is a difficult statistical estimation problem, for different reasons. First, the choice set is typically very large. Second, it may be important to take into account the correlation between the (generalized) costs of different routes, and thus allow for realistic substitution patterns. Third, due to technical or privacy considerations, the data may be temporally and spatially sparse, with only partially observed paths. Finally, the position of vehicles may have measurement errors. We address all these problems using a indirect inference approach. We demonstrate the feasibility of the proposed estimator in a model with random link costs, allowing for a natural correlation structure across paths, where the full choice set is considered.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

Keyword

Correlation structure
Flexible routes
Indirect inference
Random links
Sparse data
Statistical estimation
Substitution patterns
Urban traffic networks

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