Learning from user behavior: A survey-assist algorithm for longitudinal mobility data collection

Author:

Lu Hannah,Rischpater Katie,Shankari K.

Publisher

Elsevier BV

Reference14 articles.

1. Akcicek, C., Aemmer, Z., Shankari, K., Duvall, A. Freewheeling: What Six Locations, 61,000 Trips, and 242,000 Miles in Colorado Reveal About How E-Bikes Improve Mobility Options.

2. Travel to common destinations: an exploration using multiday GPS data;Dill;Transp. Res. Record,2014

3. Detecting activity type from GPS traces using spatial and temporal information;Feng;Eur. J. Transport Infrastruct. Res.,2015

4. Gong, L., Morikawa, T., Yamamoto, T., Sato, H., 2014. Deriving personal trip data from GPS data: a literature review on the existing methodologies. In: Procedia – Social and Behavioral Sciences, vol. 138. pp. 557–565, the 9th International Conference on Traffic and Transportation Studies (ICTTS 2014).

5. Testing the Reliability of a Smartphone-Based Travel Survey: An Experiment in Seoul;Lee;J. Korea Inst. Intell. Transport Syst.,2016

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