Individual activity data collection based on mobile positioning infrastructure in Beijing

Collecting individual activity data is increasingly more challenging for researchers because of low response rate and high respondent burden. In this paper, we combine two mobile positioning technologies with a Remind Recall approach for individual activity data collection in a large city. When the users are outdoor, the phone´s GPS receivers will automatically track the users´ trajectories while when the users are indoor, it will automatically switch to mobile positioning and continues recording. In order to achieve the purpose of prompted recall and reduce user burden, a trajectory segmentation algorithm is proposed to generate a brief sketch which improves the responder´s possibility to recall information about activities. We have implemented a data collection system and carried out an activity survey project about 500 people in Beijing. The good performance of our system in Beijing survey and the enthusiastically residents´ responses give a sufficient proof of our expectation.