Sean T. Doherty

A COMPUTERIZED HOUSEHOLD ACTIVITY SCHEDULING SURVEY

Household activity scheduling is widely regarded as the underlying mechanism through which people respond to emerging travel demand management policies. Despite this, very little fundamental research has been conducted into the underlying scheduling process to improve our understanding and ability forecast travel. The experimental survey approach presented in this paper attempts to fill this gap. At the core of the survey is a Computerized Household Activity Scheduling (CHASE) software program. The program is unique in that it runs for a week long period during which time all adult household members login daily to record their scheduling decisions as they occur over time. An up-front interview is used to define a households activity agenda and mode availability. A sample of 41 households (66 adults and 14 children) was used to assess the performance of the survey. Analysis focuses on times to completion, daily scheduling steps, activity-travel patterns, and scheduling time horizons. Overall, the results show that the computer-based survey design was successful in gathering an array of information on the underlying process, while minimizing the burden on respondents. The survey was also capable of tracing traditionally observed activity-travel outcomes over a multi-day period with minimal fatigue effects. The paper concludes with a detailed discussion on future survey design, including issues of instrument bias, use of the Internet, and improved tracing of spatial behaviour. Future use of the survey methodology to enhance activity-travel diary surveys and stated responses experiments is also discussed.

A conceptual model of the weekly household activity/travel scheduling process

This chapter examines the ways in which various activity and travel scheduling decisions or choices are interrelated over time. Major subject headings include: 1. Introduction, 2. Data Collection Methodology, 3. Conceptual Model Development, 4. Random Event Simulator, 5. Conclusions.

COMPUTERIZED HOUSEHOLD ACTIVITY-SCHEDULING SURVEY FOR TORONTO, CANADA, AREA: DESIGN AND ASSESSMENT

Traditional activity-travel diary surveys have for some time served as the primary source of data for understanding and modeling travel behavior. Recent changes in policy and forecasting needs have led to the development of an emerging class of activity-scheduling process surveys that focus on the underlying behavioral mechanisms that give rise to travel and condition future change. Many of these surveys involve the use of computers for data entry over multiday periods. These changes pose new challenges and opportunities for quality assessment. At this early stage it is more important than ever to document closely the quantity and quality of data provided by such surveys as well as the associated burden and experience of respondents. This study reviews existing quality standards and seeks to develop several new data-quality measures suitable to this emerging class of surveys. Data are used from a recent household activity-scheduling survey of 271 households in Toronto, Ontario, Canada. A detailed description of the survey instrument is provided, along with an in-depth examination of key results that shed light on data quality. Included are results from a separate survey of 31 respondents concerning their experiences and perceptions of the survey. Overall, although the survey was generally successful in tracking both observed patterns and underlying decision processes over a multiday period within a household, it did come at a price in terms of respondent burden. On the basis of these results several new data-quality guidelines are suggested that incorporate use of activity-trip rates, scheduling-step rates, planning-time horizons, and log-in durations. Further specific suggestions for reducing respondent burden are suggested.

How far in advance are activities planned? : Measurement challenges and analysis

The development of simulation models of activity-scheduling behavior has gained momentum over the past decade as a means to forecast travel demands. Of fundamental concern in these models is the process or timing of scheduling decisions–-or planning time horizon. Conceptually, it is understood that activities are planned over varying time horizons, but little empirical evidence exists. One way to explore these issues is to ask people to self-report when they planned their activities. However, this is a difficult question for researchers to formulate and for people to comprehend and recall, because people often plan (and replan) activity attributes over an extended period of time, some without much conscious thought. The objective of this paper is to describe the development of a planning time horizon query that was part of a larger activity scheduling process survey and to provide one of the first empirical analyses based on a random sample of 373 respondents. Included is a detailed examination of activity addition, modification, and trip-planning time horizons as well as analysis of “routine” and “unrecalled” decisions. Results indicate that people have the ability to recall a high level of detail on a planning time horizon, ranging from decisions made long ago that establish an initial skeleton schedule to continued preplanning in the days leading up to the event day and impulsive decisions made the day of the event. The implications of these results for future survey design and development of an activity-scheduling process simulation model are discussed.

The development of a unified modeling framework for the household activity-travel scheduling process

The goal of this paper is to propose a new approach to activity-travel schedule modeling that provides a unifying framework for past research in different areas. This approach is based on empirical evidence gathered using a Computerized Household Activity SchEduling (CHASE) survey. The survey provided a means to examine the underlying scheduling behavior of household over a one week period as it occurs in reality. Results show that a clear distinction can be made between routine scheduling decisions that are pre-planned before the week commences, and the more short-term, impulsive, opportunistic decisions made as the schedule is executed during the week. This distinction allows one to conceptualize the modeling task as a multi-stage process, wherein routine planning is approached with existing optimization models (assuming that routine activities are the result of a long-term thought and experimentation process) followed by a more sub-optimal rule-based simulation model to replicate the decisions process during the week within the constructs of the optimal routine plan. Such a model is proposed in this paper as a long term development, and would rely on the type of data provided by new data collection techniques such as CHASE. Operationalization of the model as an event-oriented simulation is proposed. Various components of the model are explored in detail, and discussed within context of existing models.

Analysis of Factors Affecting the Frequency and Type of Activity Schedule Modification

There is growing interest among the travel behavior community in activity scheduling and rescheduling behavior. This paper reports an analysis of activity modification behavior using extensive data for activity scheduling and rescheduling collected from a recent survey. Models that are developed describe the frequency and type of schedule modification. The analysis indicates that activity location and coscheduling with peers were much less frequently modified than activity timing and duration and that the degree of spatial flexibility of an activity plays an important role. The implications of these findings both for the modeling of scheduling and rescheduling behavior and for the development of scheduling support tools are discussed.

Mixed Logit Model of Activity-Scheduling Time Horizon Incorporating Spatial–Temporal Flexibility Variables

Observed travel patterns are the result of an underlying activity-scheduling process. Understanding how individuals plan and sequence their activities and trips over time will offer promise, as researchers are interested in developing models that can predict the sequences in which activities are added to the schedule during a continuous process of schedule construction. In practice, a fixed order by activity type is often assumed, but it ignores the strong interdependencies in activity and travel choices. This study presents the process of developing a mixed logit discrete choice model to predict the choice of the activity-scheduling time horizon. The model classifies activities according to the order in which they were planned (weeks or months ago, same week, same day, or impulsive). A variety of explanatory variables were used to provide a good model fit. Overall, the model demonstrates that activity planning is influenced by a wide variety of explanatory variables, including observable activity types a...

Household Activity Rescheduling in Response to Automobile Reduction Scenarios

Forecasting the enduring and wider implications of emerging travel demand management and automobile reduction policies has proved to be a challenging task. Travel behavior researchers point to the need for more in-depth research into the underlying activity-travel scheduling processes as a means to improve the ability to do so. The objective of this research is to explore the household rescheduling and adaptation process to vehicle reduction scenarios. Descriptive results from two, small-sample, in-depth experiments are presented. The first experiment focused on households’ response to a fuel prices increase, whereas the second focused on the response of two-vehicle households to long-term removal of one vehicle from the household. Results indicate that households are aware of a broad range of possible adaptation strategies, including not only mode changes but also a wide variety of changes in activities, planning, and longer-term lifestyle changes. When people were asked to actually implement such stated strategies under realistic conditions, a much more elaborate behavioral response was elicited. This included multiple rescheduling decisions involving several activities and household members over the course of a day or even several days. Thus, even relatively straightforward stated response strategies often lead to interconnected primary and secondary effects on observed activities and travel, realized through a sequence of rescheduling decisions over time and space and across household members. These results suggest that an explicit accounting of rescheduling decision sequences in forecasting models would enhance their behavioral validity and accuracy.

Digital Sketch-Map Drawing as an Instrument to Collect Data about Spatial Cognition

The formative years of cognitive mapping research focused on theoretical understanding, with less emphasis on developing innovative methodologies to extract cognitive maps. By the 1990s, new cross-disciplinary exchanges with computer science and information technology had renewed interest in the field. This article describes a method for collecting, mapping, and exploring the sequence of sketch-map creation, including integration of the resulting sketch maps into a geographic information system (GIS) for visualization and potential geometric analyses. The method involves the use of a tablet computer that allowed subjects to draw their sketch maps directly onscreen while computer software simultaneously records the drawing process in audio and video format. Results from a pilot study with 45 participants demonstrate that the method preserves the quality of drawn sketch maps but adds several new data elements and insights. In particular, the audio data were used to add labels and other attributes to drawn s...

Examining the Nature and Extent of the Activity-Travel Preplanning Decision Process

This paper presents results from an in-depth survey method for capturing the content and attributes of peoples’ preplanned schedules. The focus is on preplanned daily activity and travel events, their typically observable attributes (event type, start and end time, location, and involved person), and the extent to which these attributes are specified and elaborated on. The survey started with an interviewer simply asking subjects to write down or discuss their schedule for the next 2 days in as much or as little detail as they knew. The interviewer subsequently probed for further details as needed. This method elicited considerable detail on decision hierarchies in the subjects’ own words. Overall, it was found that activity type is the most often preplanned activity attribute, followed by location, start time, involved persons, and end time. For trips, the mode type and start time are most often planned, followed by involved persons and end time. Additional analysis further confirms that the preplanning is an ongoing decision process, wherein tentative decisions on each attribute are often made and then revisited at some point closer to execution. The implications of these findings for model development and future survey design are discussed. In particular, the results imply that activity scheduling models should adopt a nested or continuous planning loop, wherein certain activity attribute decisions are made first but are followed by subsequent stages of refinement and elaboration.