Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inferring Passenger Type from Commuter Eigentravel Matrices   A sufficient knowledge of the demographics of a commuting public is essential
in formulating and implementing more targeted transportation policies, as
commuters exhibit different ways of traveling. With the advent of the Automated
Fare Collection system (AFC), probing the travel patterns of commuters has
become less invasive and more accessible. Consequently, numerous transport
studies related to human mobility have shown that these observed patterns allow
one to pair individuals with locations and/or activities at certain times of
the day. However, classifying commuters using their travel signatures is yet to
be thoroughly examined.
  Here, we contribute to the literature by demonstrating a procedure to
characterize passenger types (Adult, Child/Student, and Senior Citizen) based
on their three-month travel patterns taken from a smart fare card system. We
first establish a method to construct distinct commuter matrices, which we
refer to as eigentravel matrices, that capture the characteristic travel
routines of individuals. From the eigentravel matrices, we build classification
models that predict the type of passengers traveling. Among the models
explored, the gradient boosting method (GBM) gives the best prediction accuracy
at 76%, which is 84% better than the minimum model accuracy (41%) required
vis-\`a-vis the proportional chance criterion. In addition, we find that travel
features generated during weekdays have greater predictive power than those on
weekends. This work should not only be useful for transport planners, but for
market researchers as well. With the awareness of which commuter types are
traveling, ads, service announcements, and surveys, among others, can be made
more targeted spatiotemporally. Finally, our framework should be effective in
creating synthetic populations for use in real-world simulations that involve a
metropolitan's public transport system.

12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
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The categories of this paper are: bayes-an
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The categories of this paper are: solv-int
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ex
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The categories of this paper are: astro-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
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The categories of this paper are: math-ph
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The categories of this paper are: q-bio