Talks and Poster Presentations (with Proceedings-Entry):
C. Schneider, C. Rudloff, D. Bauer, M. Gonzalez:
"Daily travel behaviour: lessons from a week-long survey for the extraction of human mobility motifs related information";
Talk: UrbComp'13: The 2nd ACM SIGKDD International Workshop on Urban Computing Proceedings,
08-11-2013; in: "Proceedings of the UrbComp'13: The 2nd ACM SIGKDD International Workshop on Urban Computing Proceedings",
ACM Digital Library (ed.);
Paper ID 8.
Multi-agent models for simulating the mobility behavior of
the urban population are gaining momentum due to increasing
computing power. Such models pose high demands in
terms of input data in order to be reliably able to match real
world behavior. To run the models a synthetic population
mirroring typical mobility demand needs to be generated
based on real world observations. Traditionally this is done
using travel diary surveys, which are costly (and hence have
relatively low sample size) and focus mainly on trip choice
rather than on activities for an entire day. Thus in this
setting the generation of synthetic populations either relies
on resampling identical activity chains or on imposing independence
of various trips occurring during the day. Both
Acknowledgments: This research was partially funded
by the EMPORA project ( nanced by the Austrian KLIEN).
Travel survey data has been made available from Verband
Region Stuttgart which is gratefully acknowledged.
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assumptions are not realistic.
Using Call Detail Records (CDRs) it has been found that individual
daily movement uses only a small number of movement
patterns. These patterns, termed motifs, appear stably
in many di erent cities, as has been shown for both CDR
data as well as travel diaries.
In this paper the relation between these motifs and other
mobility related quantities like the distribution of travel distances
and times as well as mode choice is investigated.
Additionally transition probabilities both for motifs (relevant
for multi-day simulations) and mode transitions are
discussed. The main nding is that while some of the characteristics
seem to be unrelated to motifs, others such as mode choice
exhibit strong correlations which could improve the provision
of synthetic populations for multi-agent models.
Thus the results in this paper are seen as one step further
towards the creation of realistic (with respect to mobility
behavior) synthetic populations for multi-agent models in
order to analyze the performance of multi-modal transportation
systems or disease spreading in urban areas.
Keywords: human mobility; multi-agent models; mobility
demand modeling; motifs.
ACM Classi cation Codes:
I.6.5: SIMULATION AND MODELING: Model Development
J.2: Computer Applications: PHYSICAL SCIENCES AND
Created from the Publication Database of the AIT Austrian Institute of Technology.