Assessing the Influence of Residential Location Changes on Travel Behavior
Final Report
Principal Investigator:
Michael G. McNally
Institute of Transportation Studies
University of California, Irvine
Irvine, CA 92697-3600
Tel: (949) 824-8462
Fax: (949) 824-8385
E-m: mmcnally@uci.edu
Funded by a UCTC Year 13 Research Grant
ABSTRACT:
There are certain fundamental transportation problems that have remained problems, in part, due to an inability to effectively collect the data necessary to address the problem. One such problem involves the learning process by which a household re-locating into a new neighborhood evolves new household activity patterns. More specifically, when a household relocates, what are the immediate and longer term impacts on travel behavior of the local activity and transportation systems? How do household travel patterns evolve? While simple logic suggests that new alternatives become available for travel and activity decision-making, what are these choices and how does knowledge of these choices evolve?
This project applied technologies developed in prior UCTC and UC Irvine research projects to facilitate the observation of a small number of households re-locating from within Orange County, CA to selected new home developments in southern Orange County. A in-vehicle GPS-based, wireless communication data logging system, TRACER, was installed in the vehicles of each sampled household to measure vehicle use for a multi-day period prior to moving, immediately after re-locating, and a few weeks after relocating to the new development. Sampled households also used REACT!, a computer-aided self-administered survey research software which was developed in prior UCTC research, to record their household travel and activities during this same period. A critical phase of this project was the integration of REACT! and TRACER. GIS-based data sets depicting the local activity-systems and transport networks serve as base reference maps. Together, this data provided a means to address the changes in travel behavior upon relocation and to assess the evolution of stability in this behavior over time.
Key Words: Travel behavior, residential location, TRACER, REACT!, household travel/activity surveys, activity diaries.
1. OVERVIEW
The fundamental motivation for the
proposed research was to compare household travel behavior patterns before and
after residential relocation. The goal
was to gain fundamental insights into the following areas of residential
location and the associated influence on household travel behavior:
(1) What are the relevant land use and transportation considerations when re-locating a residence;
(2) What is the effect of residential relocation on household travel patterns, in general, and on VMT, mode use, and travel time, in particular;
(3) What learning processes are revealed as households develop new travel patterns;
(4) Over what time frame does stability of travel patterns arise; and
(5) What is the influence of land use type and activity availability on travel behavior.
Prior research suggests that the decision to purchase a new home is in part affected by the location of that new home within a household’s spatial environment. Since the sample design of this research effort restricted all households to be moving into the same residential area, it was not possible to fully assess issues of residential choice. However, if did allow for a more structured assessment of the impacts of this new environment on travel and activity choices.
There are certain fundamental transportation problems that have remained problems, in part, due to an inability to effectively collect the data necessary to address the problem. This project applied technologies developed in prior UCTC and UC Irvine research projects to facilitate the observation of a small number of households re-locating from within Orange County, CA to selected new home developments in southern Orange County. A in-vehicle GPS-based, wireless communication data logging system, TRACER, was installed in the vehicles of each sampled household to measure vehicle use for a multi-day period prior to moving, immediately after re-locating, and a few weeks after relocating to the new development. Sampled households also used REACT!, a computer-aided self-administered survey research software which was developed in prior UCTC research, to record their household travel and activities during this same period. A critical phase of this project was the integration of REACT! and TRACER. GIS-based data sets depicting the local activity-systems and transport networks served as base reference maps. Taken together, this data provided a means to address the changes in travel behavior upon relocation and to assess the evolution of stability in this behavior over time.
1.1 REACT!
A web-based travel/activity survey, REACT! is designed as a Computer Aided Self-administered Interview. REACT! elicits both travel/activity plans as well as revealed travel patterns as a step toward revealing the household scheduling process. REACT! comprises two linked components. The first is the Initial Interview, a self-administered household "interview" which is completed prior to the start of the diary. The second is the Daily Interview, a self-administered survey of the preceding 24 hours of travel and activity.
REACT!'s self-administered initial interview provides a user-friendly interface to collect standard demographic variables (household, person, and vehicle characteristics) as well as information describing "typical" activity types and locations. The initial interview concludes with the
completion of the first pre-travel survey. During this phase, all travel and activity that is planned for the survey period is identified at a level of detail corresponding to the level of planning -- only those attributes actually planned are recorded.
REACT!'s self-administered daily interview comprises to parts. The first is a comprehensive travel and activity diary. Activities that were planned can be moved from the pre-travel plan to the current day's survey, adding any unplanned characteristics and updating as necessary. The second involves a continuation of pre-travel planning for the reminder of the week.
1.2 TRACER
TRACER is a portable, automated in-vehicle data collection system that integrates GPS with wireless communications allowing data to be accessed and the vehicle to be tracked at any time that the vehicle is under power. TRACER incorporates an Extensible Data Collection Unit (EDCU) with a suite of base station processing software for both real-time and post-processing. These self-contained units are based on a power-efficient x586-class, 133 MHz microprocessor running a Linux-based embedded operating system. The unit has 32 Mb of RAM, uses flash-RAM as its primary storage, and controls both a GPS receiver and a cellular digital packet data (CDPD) modem. The operating system runs programs to control the defined EDCU functional applications. A range of applications include: (a) basic multi-day surveys of vehicle trajectories, (b) real-time traffic stream condition reporting via vehicle probes, (c) enhanced multi-day trajectory survey with behavioral logging, and (d) routing behavior under real-time route guidance.
2. RESEARCH METHODOLOGY
2.1. Sample Selection
The sample population consists of 25 Orange County households that were identified based on their purchase of a new home in a new residential development in southern Orange County. These homes were not subject to move in for several months which allowed for a pre-survey interview with the household to explain the study, introduce the survey instruments, and establish the baseline travel and activity patterns for the household in their current environment.
2.2. Data Collection
Data collection comprised following three phases:
Phase 1: After purchasing a new home and prior to moving into the home.
Phase 2: Within the first two weeks of moving into the new home.
Phase 3: Three months after moving into the new home.
The Phase 1 questionnaire gathered data related to the household and its residential relocation decision process. Each household was also introduced to TRACER. These self-contained GPS units are easy to install in household vehicles (requiring only an auxiliary power port and two small antennas). Further, the GPS tracings of vehicle travel are easily displayed on a web site so that household members can see what data is to be collected once the formal survey starts. This TRACER test period also provides a baseline of household travel, complemented by questions on the interview questionnaire. The GPS units record trip date, start and end time, and vehicle position (latitude and longitude) at 2-10 second intervals.
In subsequent phases, the integrated TRACER and REACT! systems are used to elicit and record household activity planning and execution. TRACER requires no traveler intervention, serving as a silent monitor of vehicular travel and activity. REACT! allows the household respondents (adults only) to select the time that’s best for them to record daily travel and subsequent plans, even in multiple sessions (taking a total of about 20 minutes per adult per day).
2.3. Data Processing
With the integration of REACT! and TRACER, the REACT! database is primarily self-coding with respect to spatial and temporal location. The small sample size allows for a manual review of all data records in the REACT! database as well as a formal comparison to the vehicle trip logs from the TRACER systems independent database.
2.4. Data Analysis
As an exploratory study, only initial hypotheses were developed, as formal research hypotheses were expected to emerge as the data was analyzed. First, it is possible that part of the rationale for re-locating can be directly related to activity availability and access in the new location, indicating some advanced knowledge of the new area. It is more likely that this knowledge will accrue within the household as the household members become accustomed to the new environment. We plan to assess overall activity patterns during all three data collection phases, and also to analyze specific patterns of mode use, activity choices, household interaction, and general measures such as VMT and total travel time.
3. KEY FINDINGS
3.1 Technical Performance of
Survey Instruments
The integrated TRACER and REACT! was pre-tested with a small sample in Irvine, California. The pre-test identified selected improvements needed in question design and also identified the need for revision of help files. Many were too “wordy” while some were too brief. Additional help files were required for the TRACER interface. Although the selection of GPS “trips” for inclusion in the REACT! diary was straightforward, some short trips either do not appear or only partially appear (starting mid-trip when the GPS signal was locked). Respondents were instructed that the tracing was not foolproof. If the tracings correspond to actual travel, a simple “click” moves information on trip times and locations to the diary. Partial information serves, at least, as a memory jogger and can also be moved to the diary followed by editing. Finally, the length of the REACT! session was deemed to long for panel designs, so the initial interview was shortened (and eliminated from subsequent phases) and the detail in pre-travel planning and post-trip recording was reduced. Preliminary analyses validate the program's capability of guiding participants to complete data entry tasks on their own. The pre-test allowed for the reduction instrument bias while allowing for the expansion of program capabilities.
3.2 Behavioral Analyses
Data collected with TRACER and REACT! were used to examine the structure of activity patterns. The term structure refers to the outcome of a set of decisions facing individuals as they conduct their daily activities. At a minimum, structure can be interpreted as the sequence by which various activities enter one's daily activity scheduling process. Structure is complex with multi-day diaries since there is variation over the week, plus variation from one phase to the next.
Initial analyses of household data was consistent with prior TRACER and REACT! applications (both applied independently). Two-way contingency tables again showed that shorter duration activities were more likely to be inserted opportunistically in a schedule already anchored by longer duration counterparts. An analysis of tour structure suggested that many tours were opportunistically formed with the proportion of opportunistic stops increasing with the sequential position of an activity in a tour, but with this proportion decreasing as travel time increased.
3.3 Overall Assessment
The analyses completed suggests two potential directions to improve current travel demand models. First, in terms of data collection, the conventional activity/travel diary approach needs to be augmented. It is found that a certain portion of out-of-home activities actually occurred spontaneously. Thus, taking "snapshots" of the revealed activity patterns for a day or two does not necessarily capture consistent patterns. Asking questions related to an individual's typical activity program is a potential way of addressing this. For example, based on the finding that individuals tend to adjust the timing of events rather than the locations, it may be worthwhile to consider adding questions to conventional travel diaries addressing whether there are frequently visited locations. If the set of alternative activity locations were known, it would improve the chances to deduce the decision strategies that resulted in the revealed patterns. Second, the analyses demonstrated that the behavioral strategy behind everyday activity scheduling is closer to the viewpoint of transactional opportunistic (i.e., the activity-peg theory) than it is to a simultaneous utility-maximization structure. Instead of contemplating the optimal choices before action, individuals are often improvising in an environment with certain spatial and temporal constraints.
4.
JOURNAL PAPERS AND
CONFERENCE PRESENTATIONS
Journal papers are under development as is Elizabeth Geho’s PhD dissertation that summarizes all aspects of the project.
5. INNOVATIONS
TRACER and REACT! are two survey technologies that were developed in prior research. As part of this study of residential location impacts on travel behavior, these two technologies were integrated. It was particularly important to automate the data acquisition process because the anticipated impact of a residential relocation makes it unlikely that a household will participate in simultaneous survey efforts. More importantly, it is the process of learning and evolution that is the focus of interest, and these subtleties are difficult to assess at a point in time. The integrated survey system is believed to be a valid method to collect longitudinal household data over longer time periods, perhaps leading to continuous data collection.
6. ACKNOWLEDGEMENTS
The author acknowledges the research support of the University Transportation Centers program, in general, and the University of California Transportation Center, in particular, for support and encouragement on this and prior studies leading to this research.