01129818

Component

https://doi.org/10.3141/2105-04

http://scholar.google.com...usen&publication_year=2009

Since the first Global Positioning System (GPS) studies in the mid-1990s, this method of surveying individual travel behavior has gained attention in transport research. Compared with classic travel survey methods, GPS studies offer researchers benefits of more accurate and reliable information. At the same time, the participants’ burden is reduced substantially if the GPS data collection does not involve time-consuming questions. However, without additional information, such as modes and trip purposes, extensive postprocessing is required to derive data that can be used for analysis and model estimation. The corresponding procedures are an ongoing research issue. This paper describes a postprocessing procedure needing no input other than the most basic GPS raw data: three-dimensional positions and the corresponding time stamps. First, the data are thoroughly cleaned and smoothed. Second, trips and activities are determined. Third, the trips are segmented into single-mode stages, and the transport mode for each of the stages is identified. The procedure is applied to GPS records collected in the Swiss cities of Zurich, Winterthur, and Geneva. A total of 4,882 participants carried an on-person GPS receiver for an average of 6.65 days. The results are compared with the Swiss Microcensus 2005 to demonstrate that derived data are ready for further applications, such as discrete choice model estimations.

01141653

09-1830

English

pp 28-36

2009

Transportation Research Record: Journal of the Transportation Research Board

9780309126205

Print

Figures (5) ; References (35) ; Tables (2)

Data collection; Data quality; Fuzzy logic; Global Positioning System; Information processing; Travel behavior; Travel surveys

Data filtering; Data smoothing; Postprocessing

Geneva (Switzerland); Winterthur (Switzerland); Zurich (Switzerland)

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 30 2009 6:05PM

• A Semidirective Interview Method to Analyze Behavioral Changes: A Focus on Two Case Studies
• Bayesian Training and Committees of State-Space Neural Networks for Online Travel Time Prediction
• Development of Geolocation Data Compression for Transportation Target Identification
• Distributed Approach for Estimation of Dynamic Origin–Destination Demand
• Driver-Assisted Bus Interview: Passive Transit Travel Survey with Smart Card Automatic Fare Collection System and Applications
• Efficiency and Effectiveness of Cell Phone Samples in Transportation Surveys
• Forecasting Network Data: Spatial Interpolation of Traffic Counts from Texas Data
• Generating Internationally Comparable Figures on Long-Distance Travel for Europe
• Household Travel Surveys with GPS: An Experiment
• Improving the Usability of a Complex Household Travel Survey: An Evaluation of User Requirements
• Kinematic Terrestrial Light-Detection and Ranging System for Scanning
• Measuring and Estimating Suppressed Travel with Enhanced Activity–Travel Diaries
• Model-Based Synthesis of Household Travel Survey Data in Small and Midsize Metropolitan Areas
• Participatory Geographic Information Systems and Active Transportation: Collecting Data and Creating Change
• Transport and Surveillance Aspects of Location-Based Services
• Vehicle Detection from Satellite Images: Intensity-, Chromaticity-, and Lane-Based Method