1. Harry Timmermans Eindhoven University of technology
Using Intelligent GPS Devices and Learning Algorithms for Collecting Multi-Week Activity-Travel Diary Data: Experiences in a Dutch Context
Harry Timmermans
Eindhoven University of technology

2. Introduction
Increasingly more complex models set higher demand for travel survey data
Activity-based models are gradually moving from static, single-day models to dynamic, multi-week models
Conventional activity-travel diaries are insufficient

3. Basic idea
1. use GPS-device to record information about activity-travel patterns
2. use automated intelligent algorithms to translate GPS traces into activity-travel diaries
3. use web-based prompted recall for validation
4. Use learning algorithms to improve accuracy of imputation over time so that respondent burden will reduce over time and they may be willing to carry GPS device a longer period of time

4. Evidence

5. Evidence

6. Conclusions Findings Future research More difficult study areas
Interrupted series due to holidays, day trips etc.
Learning algorithm seems successful
Imputation results are promising (in this study area)
Future research
More difficult study areas
More difficult segments of the population
Using larger set of imputation rules