1,941
Views
2
CrossRef citations to date
0
Altmetric
Articles

Automatic Trip Detection with the Dutch Mobile Mobility Panel: Towards Reliable Multiple-Week Trip Registration for Large Samples

Bibliography

  • F. Biljecki, H. Ledoux, and P. van Oosterom, “Transportation Mode-Based Segmentation and Classification of Movement Trajectories,” International Journal of Geographical Information Science 27: 2 (2013) 385–407. doi: 10.1080/13658816.2012.692791
  • A. Blom, M. Bosnjak, A. Cornilleau, A.-S. Cousteaux, M. Das, S. Douhou, and U. Krieger, “A Comparison of Four Probability-Based Online and Mixed-Mode Panels in Europe,” Social Science Computer Review 34: 1 (2015) 8–25. doi: 10.1177/0894439315574825
  • W. Bohte and K. Maat, “Deriving and Validating Trip Purposes and Travel Modes for Multi-Day GPS-Based Travel Surveys: A Large-Scale Application in the Netherlands,” Transportation Research Part C 17: 3 (2009) 285–297. doi: 10.1016/j.trc.2008.11.004
  • S. Bricka, S. Sen, R. Paleti, and C. Bhat, “An Analysis of the Factors Influencing Differences in Survey-Reported and GPS-Recorded Trips,” Transportation Research Part C 21 (2012) 67–88. doi: 10.1016/j.trc.2011.09.005
  • C. Cottrill, F. Pereira, F. Zhao, I. Dias, H. Lim, M. Ben-Akiva, and P. Zegras, “Future Mobility Survey. Experience in Developing a Smartphone-Based Travel Survey in Singapore,” Transportation Research Record 2354 (2013) 59–67. doi: 10.3141/2354-07
  • T. Feng and H. Timmermans, “Transportation Mode Recognition Using GPS and Accelerometer Data,” Transportation Research Part C 37 (2013) 118–130. doi: 10.1016/j.trc.2013.09.014
  • S. Ferrer and T. Ruiz, “Travel Behavior Characterization Using Raw Accelerometer Data Collected From Smartphones,” Procedia: Social and Behavioral Sciences 160 (2014) 140–149.
  • H. Gong, C. Chen, E. Bialostozky, and C. Lawson, “A GPS/GIS Method for Travel Mode Detection in New York City,” Computers, Environment and Urban Systems 36 (2012) 131–139. doi: 10.1016/j.compenvurbsys.2011.05.003
  • K. Geurs, T. Thomas, M. Bijlsma, and S. Douhou, “Automatic Trip and Mode Detection with MoveSmarter: First Results from the Dutch Mobile Mobility Panel,” Transportation Research Procedia 11 (2015) 247–262. doi: 10.1016/j.trpro.2015.12.022
  • S. Hoogendoorn-Lanser, N. Schaap, and M.-J. Olde Kalter, “The Netherlands Mobility Panel: An Innovative Design Approach for Web-Based Longitudinal Travel Data Collection,” paper presented at the 10th International Conference on Transport Survey Methods (Leura Australia, 16–21 November 2014).
  • D. Houston, T. Luong, and M. Boarnet, “Tracking Daily Travel; Assessing Discrepancies Between GPS-Derived and Self-Reported Travel Patterns,” Transportation Research Part C 48 (2014) 97–108. doi: 10.1016/j.trc.2014.08.013
  • P. Kelly, A. Doherty, A. Mizdrak, S. Marshall, J. Kerr, and A. Legge, “High Group Level Validity But High Random Error of A Self-Report Travel Diary, As Assessed by Wearable Cameras,” Journal of Transport & Health 1: 3 (2014) 190–201. doi: 10.1016/j.jth.2014.04.003
  • J. Liu, H. Zhenga, T. Feng, S. Yuan, and H. Lu, “Post-Processing Procedures for Passive GPS Based Travel Survey,” paper presented at the 13th COTA International Conference of Transportation Professionals (CICTP 2013).
  • P. Nitsche, P. Widhalm, S. Breuss, and P. Maurer, “A Strategy on How to Utilize Smartphones for Automatically Reconstructing Trips in Travel Surveys,” Procedia: Social and Behavioral Sciences 48 (2012) 1033–1046.
  • P. Nitsche, P. Widhalm, S. Breuss, N. Brändle, P. Maurer, “Supporting Large-Scale Travel Surveys with Smartphones: A Practical Approach,” Transportation Research Part C 43 (2014) 212–221. doi: 10.1016/j.trc.2013.11.005
  • A. Prelipcean, G. Gidófalvi, and Y. Susilo, “Mobility Collector,” Journal of Location Based Services 8: 4 (2014) 229–255. doi: 10.1080/17489725.2014.973917
  • A. Prelipcean, G. Gidófalvi, and Y. Susilo, “Transportation Mode Detection: An In-Depth Review of Applicability and Reliability,” Transport Reviews 37: 4 (2017) 442–464. doi: 10.1080/01441647.2016.1246489
  • T. Rasmussen, J. Ingvardson, K. Halldórsdóttir, and O. Nielsen, “Improved Methods to Deduct Trip Legs and Mode From Travel Surveys Using Wearable GPS Devices: A Case Study From the Greater Copenhagen Area,” Computers, Environment and Urban Systems 54 (2015) 301–313. doi: 10.1016/j.compenvurbsys.2015.04.001
  • A. Raza, L. Knapen, K. Declercq, T. Bellemans, D. Janssens, and G. Wets, “Diary Survey Quality Assessment Using GPS Traces,” Procedia Computer Science 52 (2015) 600–605. doi: 10.1016/j.procs.2015.05.045
  • S. Reddy, M. Mun, J. Burke, D. Estrin, M. Hansen, and M. Srivastava, “Using Mobile Phones to Determine Transportation Modes,” ACM Transactions on Sensor Networks 6: 2 (2010) Article 13. doi: 10.1145/1689239.1689243
  • K. Reinau, H. Harder, and M. Weber, “The SMS–GPS-Trip Method: A New Method for Collecting Trip Information in Travel Behavior Research,” Telecommunications Policy 39 (2015) 363–373. doi: 10.1016/j.telpol.2014.05.006
  • N. Rieser-Schüssler and K. Axhausen, “Self-Tracing and Reporting: State of the Art in the Capture of Revealed Behaviour,” in S. Hess and A. Daly, eds, Handbook of Choice Modelling (Cheltenham: Edward Elgar, 2014).
  • M. Ribeiro, A. Larrañaga, J. Arellana, and H. Cybis, “Influence of GPS and Self-Reported Data in Travel Demand Models,” Procedia - Social and Behavioral Sciences 162 (2014) 467–476. doi: 10.1016/j.sbspro.2014.12.228
  • H. Safi, B. Assemi, M. Mesbah, and L. Ferreira, “Trip Detection with Smartphone-Assisted Collection of Travel Data,” Transportation Research Record 2594 (2016) 18–26. doi: 10.3141/2594-03
  • A. Scherpenzeel and M. Das, “True Longitudinal and Probability-Based Internet Panels: Evidence from the Netherlands,” in M. Ester and L. Kaczmirek, eds, Social and Behavioral Research and the Internet: Advances in Applied Methods and Research Strategies (Boca Raton: Taylor & Francis, 2010).
  • S. Schönfelder and K. Axhausen, Urban Rhythms and Travel Behavior: Spatial and Temporal Phenomena of Daily Travel (London: Routledge, 2010)
  • I. Semanjski, “Potential of Big Data in Forecasting Travel Times,” Traffic & Transportation 27: 6 (2015) 515–528.
  • I. Semanjski and S. Gautama, “Smart City Mobility Application: Gradient Boosting Trees for Mobility Prediction and Analysis Based on Crowdsourced Data,” Sensors 15: 7 (2015) 15974–15987. doi: 10.3390/s150715974
  • L. Shen and P. Stopher, “Review of GPS Travel Survey and GPS Data-Processing Methods,” Transport Reviews 34: 3 (2014) 316–334. doi: 10.1080/01441647.2014.903530
  • D. Shin, D. Aliaga, B. Tunçer, S. Arisona, S. Kim, D. Zünd, and G. Schmitt, “Urban Sensing: Using Smartphones for Transportation Mode Classification,” Computers, Environment and Urban Systems 53 (2015) 76–86. doi: 10.1016/j.compenvurbsys.2014.07.011
  • Statistics Netherlands, Onderzoek Verplaatsingen in Nederland, 2014 (2014 National Travel Survey).
  • J. Toole, S. Colak, B. Sturt, L. Alexander, A. Evsukoff, and M. González, “The Path Most Traveled: Travel Demand Estimation Using Big Data Resources,” Transportation Research Part C 58 (2015) 162–177. doi: 10.1016/j.trc.2015.04.022
  • F. Witlox, “Evaluating the Reliability of Reported Distance Data in Urban Travel Behaviour Analysis,” Journal of Transport Geography 15: 3 (2007) 172–183. doi: 10.1016/j.jtrangeo.2006.02.012
  • G. Xiao, Z. Juan, and C. Zhang, “Travel Mode Detection Based on GPS Track Data and Bayesian Networks,” Computers, Environment and Urban Systems 54 (2015) 14–22. doi: 10.1016/j.compenvurbsys.2015.05.005
  • F. Zhao, F. Câmara Pereira, R. Ball, Y. Kim, Y. Han, C. Zegras, and M. Ben-Akiva, “Exploratory Analysis of a Smartphone-Based Travel Survey in Singapore,” Transportation Research Record 2494 (2015) 45–56. doi: 10.3141/2494-06