Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
determinations are the use of a travel diary and working in residential land use, while the least important deter- minates are being a male and traveling long distances. ⢠The model results can be used to identify possible approaches to address the underreporting by various groups. Providing a clear definition of what to record may address individuals working in residential land use. Providing travelers with high trip rates with more room to record trips on the forms may help. These individuals should be identified during recruitment. Probing for trips during lunch and stops along the way should be per- formed for unemployed individuals in the same way as for workers. ⢠The model results indicate a need to better engage drivers under the age of 30 in the surveys, as well as indi- viduals with high school educations. More challenging is addressing the underreporting of the proxy- reported travel. Not allowing proxy reporting has significant cost implications and may introduce more bias into the sur- vey data than that introduced by allowing proxy report- ing. Strengthening the telephone interview may help address this issue, as well as those related to unemployed individuals. DYNAMIC ACTIVITY- TRAVEL DIARY DATA COLLECTION USING A GLOBAL POSITIONING SYSTEMâENABLED PERSONAL DIGITAL ASSISTANT Bruno Kochan, Tom Bellemans, Davy Janssens, and Geert Wets Davy Janssens described the use of a GPS- enabled PDA device to improve travel diary data collection efforts with activity- based travel models. He discussed data collec- tion needs with activity- based travel models, available computerized travel survey data collection tools, the advantages and limitations of different approaches, and a new GPS- enabled activity- travel diary data collection tool. Volume 2 contains a paper on this topic.3 The fol- lowing points were covered in his presentation. ⢠The traditional four- step models were developed in the 1950s to predict travel demand for different trans- portation options. Recently, activity- based models have been developed to address some of the limitations asso- ciated with four- step models. Activity- based models pre- dict interdependencies between several facets of activity profiles. These facets include the type of activity, when and where the activity is conducted, the duration of the activity, and the mode of transportation used to travel to and from the activity. The participation of other individ- uals in the activity and travel represents still another facet included in activity- based models. More robust activity- based models also incorporate learning effects and other advanced elements. ⢠Activity- based models require more sophisticated and more detailed data than the traditional travel mod- els. To accommodate the calibration and validation data requirements of dynamic activity- based models, more detailed activity- travel diary information is needed. Travel diaries consist of a sequence of activities and jour- neys completed by each individual in a household. The diaries focus on all the activities and journeys completed by an individual. Completing activity- travel diaries requires a lot of effort on the part of the respondent. Travel diaries take time to fill out and require individu- als to remember and record numerous activities. ⢠A number of methods have been used to collect travel- diary information over the years. The basic paper- and- pencil method is still used in many areas. Advan- tages to this approach are that the diaries can be filled out at any time and place and are relatively easy to com- plete. This method can be prone to errors and inconsis- tencies, however. It can also be complex and tedious for some individuals. ⢠A second approach is using computer- aided self- interviews to record activity- travel scheduling behavior. The Computerized Household Activity Scheduling Elici- tor (CHASE) provides an example of this approach. This method includes a multiday computerized scheduling interface, which allows individuals to record their sched- uling decisions by adding, modifying, and deleting activi- ties to their schedule. Possible advantages to this method include the ability to obtain more detailed information and improved data quality. Potential limitations include the need to access a computer at specific places and times. ⢠A third approach is using Internet- based travel diaries. This method provides greater flexibility for the individual, because the diaries can be completed at dif- ferent locations that have Internet access and at times that are convenient to the participant. A possible limita- tion with this approach is the need for participants to have Internet access. ⢠Building on these efforts, research in Belgium is focusing on the development and application of an inte- grated travel diary approach using GPS in a PDA appli- cation. This approach involves a participant recording their planned activities in a PDA and collecting informa- tion on the participantâs actual activities through the use of GPS. The planned and actual activities can be com- pared and additional information concerning differences can be gathered as needed. ⢠A number of advantages may be realized through the use of a GPS- enabled PDA travel survey. First, trip 36 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 1 3 See Kochan, B., T. Bellemans, D. Janssens, and G. Wets. Dynamic Activity- Travel Diary Data Collection Using a Global Positioning SystemâEnabled Personal Digital Assistant. Volume 2, pp. 94â97.
