Multi-modal input interface GPS unit with antenna Multi-modal User-Device Interaction The data collection practice is enhanced from two perspectives: Text-to-speech.

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Multi-modal input interface GPS unit with antenna Multi-modal User-Device Interaction The data collection practice is enhanced from two perspectives: Text-to-speech and speech recognition to enable the machine-human interview process. The survey program actively sense data input patterns and keep the survey respondent aware of any wrong operation through auditory cues or voice message. Voice prompts help the user navigate through survey forms Real-time Tracking of Activity Scheduling/Schedule Execution Within A Unified Data Collection Framework Jianyu (Jack) Zhou and Reginald Golledge University of California, Santa Barbara, California Abstract The goal of this research is to provide a real-time system that incorporates the extraction of activity scheduling and execution information within one unified data collection system. These “revealed” data could be used for explicitly defining the mechanism of how people’s activity schedules dynamically adapt to social- demographic and temporal-spatial constraints and finally leads to the activity- travel patterns detailed by different survey methods. Background: Although a large portion of the activities that people perform daily is unplanned ahead of time, activity scheduling is inevitable when people try to make deliberate choices to accommodate competing activity needs or tasks. The action of scheduling could occur stochastically over time in an unpredictable way and could serve as an effective means for average people to find a path through the spatial-temporal constraints enforced by the human and physical environment. Researchers from various disciplines (e.g. psychology, geography, transportation) are interested in different aspects of activity scheduling problems. One of the major foci is to identify the temporal-spatial decision making structure embedded in activity scheduling and its linkage to actual activity execution. Theoretical advances and technological improvements during the past decades (e.g. cognitive model of planning and computational process models) have made the initial portion of the pursuit clearer and easier as considerable modeling and simulation efforts were spared. But the latter part of the question is yet to be explored explicitly in real life situation with a more powerful data collection means. Survey Methodology and System Implementation Survey Organization The survey program on the Pocket PC is organized into a series of forms. The survey program presents four module components and the wireless data transmission function (Figure 1): 1. Mod 1 serves the role of the up-front interview in traditional activity/travel survey. In the module, personal demographic data and activity/travel-related spatial information are collected before the beginning of the main survey for survey management. 2. Mod 2 allows the survey respondent record preliminary and refined activity schedules. 3. Mod 3 records activity-implementation-related information in real time. 4. Mod 4 functions as an independent survey unit that allows the survey respondent to take the initiative of deciding when to answer questions related to unfulfilled activities. Survey Methodology and System Implementation (cont’) Schedule Capture and Activity/Travel Tracing ( Figure 4): The information to collect with respect to a scheduled activity includes (Figure 3): activity type, day of the week for the activity, planned time slot for the activity, planned activity location, the number of people that co-participate in the activity. Use ARCPAD’s GPS tracking function to capture user’s position during the travel duration (Figure 2). The activity just accomplished is associated with the pre-input schedule as the survey respondent indicated on the “Link to Schedule” Form. For more information, please contact: Jianyu (Jack) Zhou, Department of Geography University of California Santa Barbara, Santa Barbara, CA , USA Telephone: (805) Objectives Capture the dynamic activity scheduling/execution behavior over a long survey period within a unified data collection framework. Monitor the travel data collection process in real time by wireless networking and respond to the possible data errors in a timely way. Conceptual Framework single-server, multiple-clients architecture design with four essential four hardware components: Funding Source: University of California Transportation Center (UCTC) Grant #DTRS99-G Wireless networking card Portable computing device Conclusions The survey methodology opens the opportunity for researchers to gather information on the integral scheduling and activity execution process by means of empirical data collection and to model the relationship between them. The data provided by the system will be used for in-depth analysis of the interaction between scheduling and correlated activity execution in future modeling developments. For the next step of research, we are planning to conduct a pilot data collection study with the system and study the dynamic linkage between activity scheduling and associated execution with a nested logit modeling approach. It would be also interesting to compare instrument bias and survey burden brought by the system with traditional activity/travel data collection methods. Further improvement on duration and reliability of the system potentially endows the activity/travel researchers with a powerful tool to enlarge the data bases for the longitudinal trends of activity/travel pattern changes