Ohmori, N., M. Nakazato, N. Harata, K. Sasaki and K. Nishii

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Activity diary surveys using GPS mobile phones and PDA
Nobuaki Ohmori*
Department of Urban Engineering, School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
Tel.: +81-3-5841-6232
Fax: +81-3-5841-8527
E-mail: nobuaki@ut.t.u-tokyo.ac.jp
Morimichi Nakazato
Institute of Environmental Studies, Graduate School of Frontier Sciences, The University ofTokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
Tel.: +81-3-5841-8391
Fax: +81-3-5841-8527
E-mail: nakazato@ut.t.u-tokyo.ac.jp
Noboru Harata
Department of Urban Engineering, School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
Tel.: +81-3-5841-6233
Fax: +81-3-5841-8527
E-mail: nhara@ut.t.u-tokyo.ac.jp
Kuniaki Sasaki
Institute of Materials and Environmental Technology, University of Yamanashi
4-3-11 Takeda, Kofu, Yamanashi, 400-8511, Japan
Tel.: +81-55-220-8671
Fax: +81-55-220-8671
E-mail: sasaki@yamanashi.ac.jp
Kazuo Nishii
Institute of Materials and Environmental Technology, University of Yamanashi
4-3-11 Takeda, Kofu, Yamanashi, 400-8511, Japan
Tel.: +81-55-220-8533
Fax: +81-55-220-8533
E-mail: knishii@yamanashi.ac.jp*Corresponding author
Word count: 5,498 words, 4 tables, 4 figures, total 7,498 words
Submitted on August 1, 2005
Revised on November 15, 2005

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Abstract: Activity diary is necessary information for investigating the relationships between
individual travel behavior and activity engagement. A GPS mobile-phone-based activity diarysurvey system and a GPS-equipped PDA-based activity diary survey system are developed inthis study. The software programmed in Java works on mobile phone devices for entering
information on activity diaries. Positional data are automatically collected at regular intervals by
GPS-equipped mobile phones. Two pilot surveys were conducted for a total of 49 participants to
examine the advantages of the survey system. By comparing activity data collected by thesoftware with data collected by the conventional paper-based activity diary survey, it was foundthat the system was useful for reducing a “time lag” in data entry and mitigating spatialconstraints for data entry. However, the respondent’s burden depends on the characteristics of the
respondents. The software for the GPS-equipped PDA-based activity diary survey isprogrammed in HTML. Two pilot surveys were conducted and activity data collected by the
PDA were compared with paper-based survey data. Both the number of activities and total
activity time recorded were longer in the paper-based survey, especially in in-home activities. It
could be difficult for the respondents to record parallel activities because of the pre-programmed
check system in the PDA software.

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INTRODUCTION
Travel is considered a demand, derived from the desire to engage in activities at certain locations.
Hence, activity diary data are necessary information to analyze individual activity-travel patterns
and to investigate the relationships between individual travel behavior and activity engagement.
Recently, the importance and effectiveness of activity diary data have been recognized forevaluating the effects of policy options on individual quality of life in urban space and time. The
most common survey method of collecting activity diary data has been a paper-and-pencil
interviewing (PAPI). Respondents are asked to fill in paper-based activity diary questionnaire
sheets for a day or over a period of time (two days, one week, etc.). However, there are several
problems with this traditional survey method. First, because of the great amount of time it takes
for respondents to fill in the activity diary sheet, the respondents’ burden is considerably large torecord all of the activities in the questionnaire survey sheet. Since most respondents tend torecord the activities engaged in for the survey day after coming back home at night, data
accuracy about the activity type, start/end time and location, depends mostly on their memory
retention. As for the surveyors, it takes considerable time and money for distributing andcollecting survey materials and for editing and inputting collected data. For the innovation ofsurvey methods for activity data collection, a lot of researchers are trying to reinvestigate theexisting technologies and to develop new survey methods (1).
In recent years, people can make decisions on activity scheduling and travel behavior
more dynamically than before, by acquiring both pre-trip and en-route information on transportsystems and activity opportunities from various media. Consequently, not only revealed
activity-travel patterns but also activity scheduling processes have been of interest totransportation researchers. Some researchers have been doing research on the development ofcomputer software for collecting data on activity patterns and scheduling processes, e.g. CHASE(2) and React! (3). CHASE and React! are computer-assisted self-interviewing (CASI) systems
working on a PC. Personal digital assistants (PDA) and mobile phones can also be used as adevice for data collection (4−5). On the other hand, the use of telecommunications such as
mobile phones, e-mail and the Internet, affects individual travel behavior. To analyze interaction
between telecommunications and activity-travel scheduling/patterns, information on both activity
diaries and the use of telecommunications are required. However, methods applied to collecting
effectively such data remain uninvestigated. Recently, in the field of activity-travel surveys,
positioning technologies such as global positioning system (GPS) and global system for mobile
communications (GSM) have been widely applied to collecting detailed information on travel
trajectory. The technologies make it possible to automatically collect information about position(longitude and latitude) and time (and speed for GPS) at a specific interval. To collect positional
data using GPS and GSM, respondents are required only to carry the device. There has been a lotof research on travel data collection using GPS and GSM (e.g., 6−10). GPS can be attached to
PDA and recently is installed inside the mobile phone device (see 11). PDA and mobile phones
have also been used for data collection as CASI in a wide variety of survey fields. Especially,
most of the younger people are routinely using mobile phones for voice and e-mailcommunications, and they have less difficulty in operating the devices than elder people.
Investigating possibilities of the survey system combined positioning technologies and mobile
devices for activity diary data collection could be important in terms of mitigating the problems
in activity diary surveys.
The objectives of this study are to develop a GPS mobile-phone-based activity diary

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4survey system and a GPS-equipped PDA-based activity diary survey system, and to examine
their advantages and disadvantages over conventional paper-based activity diary surveys.
DEVELOPMENT OF A GPS MOBILE PHONE AND PDA-BASED ACTIVITY DIARYSURVEY SYSTEMS
Selection of the System Platform for Data Collection
The requirements of the survey system in this study are as follows:- to directly collect electronic data on activity diaries and to transmit the data through awireless network (GSM network and the Internet);- to use a mobile device which people can easily carry in their daily lives, so that they canenter information on activity diary into the device at anytime and anyplace without spatial
and temporal constraints;- to automatically collect positional data at a regular time interval to specify activity locations
and travel routes; and- to reduce the survey cost of time and money both for distribution and collection of survey
materials, and for transmitting, editing and inputting the collected data.
Table 1 summarizes comparison among system development platforms. Mobile phones,
PDA and laptop PC are possible options of mobile electronic devices for data collection. The
monetary cost for data transmission from the device to the surveyor (or a dedicated server) is
cheaper for a laptop PC with Internet access than mobile phones and PDA with a mobile
connection. The laptop PC is the best for respondents to enter activity information in terms of thesize of monitor display. However, it would be less convenient for respondents both to carry andto enter activity information at anytime and anyplace. Mobile phone and PDA are smaller
devices and easier to be carried. The mobile phone has a smaller monitor and less flexibility forthe design of data entry form than PDA, but the number of mobile phone users is much larger
than that of PDA users in Japan – the number of subscribers is about 90 million for mobile
phones, but the number of PDA users would be less than 10 million. From the above reasons, weapplied mobile phones and PDA for the platform of system development.
TABLE 1 Comparison among Devices for Activity Diary Data Collection
Mobile phone
PDA
Laptop PC
Monetary cost for data
dependent onHigh
Lowtransmission
attached media
Size of monitor display
Small
MediumLarge
Easiness to be carried
Easy
MediumDifficultSpatial constraints for data
Low
Low
High
entering
Flexibility for the design of
Low
MediumHighdata entry form
The dissemination in people
High
Low
High
Development of GPS Mobile-Phone-Based Data Collection System
There are four mobile phone carriers in Japan; NTT DoCoMo, Inc., KDDI Corporation, TU-KA

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Cellular Inc. and Vodaphone K. K. At the time this research was launched into, the only carrierthat provided mobile phone devices with GPS installed was “au” by KDDI Corporation. The“au” employs “gpsOne” which is called the Assisted GPS (see 12). It calculates the current
position using not only GPS but also information on received signals from multiple base stations
to which the mobile phone device is connected. Therefore, positional data can be collected even
if GPS was not available because of obstructed views of GPS satellites (e.g. inside buildings, atunderground stations, etc.) or carried in a coat or jacket pocket. Furthermore, end users candevelop original Java applications working on the “au” mobile phone device and distribute it
without getting permission from KDDI Corporation. Therefore, we employed the “au” mobile
phone system among the four carriers.
We developed software in the Java language so that respondents can download thesoftware via the Web and install it on their own mobile phones. This freed the surveyor fromhaving to contact the respondents to distribute the software. Also the respondents did not need tocarry two mobile phone devices; one for the survey and another for their own use. When starting
the software, information on position specified by GPS and ID number is transmitted
automatically to a dedicated server at regular time intervals and stored. The time interval can be
set in the JAVA program source file arbitrarily. For entering information on an activity diary(activity type, start/end time, location, travel mode and accompanied persons) and telephone-use
diary (time, media, partner, send/receive and the contents for communications), a data entry form
was programmed as shown in Figure 1.
Respondents enter start/end time directly by pushing dial buttons (see Figure 1).
Information on the activity type, location, travel mode and accompanied persons is selected fromthe predefined list. If an appropriate alternative does not exist in the predefined list, respondents
directly enter their response in the blank cell. As soon as the respondent finishes entering
information on an activity, the time is also automatically recorded to analyze the “time lag”
between activity implementation and activity recording. The end time of the previous activity is
automatically set as the start time of the next activity. Error checking functions test the validity ofthe start/end time (e.g. whether the characters are number and between 3:00 to 27:00 (3:00 a.m.
on the following day), whether the start time is earlier than the end time). When the enteredinformation is not correct, it displays a warning message. Respondents can confirm the enteredinformation at anytime, and they can modify the data if they found some mistakes. The diarydata is temporarily stored in the mobile phone. When the capacity of the mobile phone’s built-in
memory becomes full, by pushing two buttons, the data is transmitted via e-mail to thesurveyor’s e-mail address. The surveyor can identify the data by accessing the server computer
through the Internet in real time.
Since positional data are transmitted only while the software is running, respondents must
always keep the software running during the survey period. When the respondents use their own
mobile phone for the survey, they can receive phone calls and e-mails while the software is
running. However, they need to end the software to make phone calls and send e-mails, andrestart the software after finishing it. When the battery level goes below a specific level, thesoftware automatically exits. This function can avoid data deletion stored in the mobile phonedevice if power suddenly runs out.
The 1st survey was conducted using this software as described in the next chapter. Afterthe 1st survey, we improved the software for some functions. The 1st version of the software
required respondents to select one activity type from 16 alternatives (sleep, personal care, meals,
work, study, housework, school/classes, research, TV watching, the Internet, hobbies, sports,

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6social activities, shopping, resting, and travel) or enter the name of activity only when select“others”, whereas in the 2nd version, the name of a concrete activity type was entered directlyfrom dial buttons. Activity data were transmitted by HTTP in the 2nd version, so respondents’operation to send data became easier (pushing one button). In the 1st version, the surveyor
needed to manually combine the activity data of each respondent sent by e-mail, because therespondent must send the data two or three times a day. Whereas, in the 2nd version, transmitted
data are automatically added to one data file in the server computer.

Start time
End time
Activity type

Scroll button

Dial buttons
FIGURE 1 Snapshot of Data Entry Screen in the 1st Version of the GPS
mobile-phone-based System
Activity Diary Survey Using the GPS Mobile Phone Device
To examine the advantages and disadvantages of the GPS mobile-phone-based activity diarysurvey over the conventional paper-based activity diary survey, two pilot surveys were conductedin January and April 2004 with a total of 49 participants living in Tokyo.
As the 1st survey, in January 2004, two-day activity diaries were collected. The number ofthe respondents of the survey was 36. Thirty three of them were 20’s years old and 3 of themwere 30’s. Thirty one respondents were males. All the respondents were daily using a mobile
phone. The average length of time of mobile phone use was 4.9 years. The respondents wereasked to start the software when they woke up and to exit it when they went to sleep in order tosave GPS tracking costs. They were asked to record activity diaries both in the mobile phone
software and in the conventional paper-based questionnaire sheet on the same day. For thepaper-based survey sheet, they were also required to record the date and time when they recorded
activities in the survey sheet. This information was used for an analysis of the “time lag”
between the activity end time and the data entry time. A total of 6 respondents were daily using

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an “au” mobile phone on which the survey software was able to work (type A5xxx or W1x).
They were asked to use their own mobile phone and to download the survey software from thesurvey website (“au-users” in this study). Then, a survey manual and a paper-based questionnaire
sheet were mailed to them. The “au-users” were not contacted by the surveyor face-to-face. On
the other hand, the “au” mobile phone (type A5402) with pre-installed survey software wasprovided to the respondents who were not using “au” mobile phones (“non-au-users”). The“non-au-users” were asked to carry it in addition to the mobile phone they were personally using.
They were instructed by the surveyor how to use the device face-to-face. On the 1st day, therespondents were asked to record their activity diary, whereas on the 2nd day, they were asked torecord not only their activity diary but also their telephone use diary.
The 2nd survey was conducted using the 2nd version of the system in April 2004 for 13
participants who were all graduate students in The University of Tokyo. This survey was also a
trial to collect activity diary data by mobile phones as an input to a GIS-based activity-travel
simulator, SMAP-E (13). All the 13 respondents were “non-au-users,” so the “au” mobile phonewhich the surveyor prepared was provided to them during the survey period. The respondents
were asked to record activity diaries in the mobile phone for three days and in the paper-basedquestionnaire sheet for the remaining four days. Telephone use diaries were not recorded in the
2nd survey.
The time interval of GPS tracking was set at 10 minutes. Batteries can keep the mobile
phone working for 5 to 6 hours in this setting. It took about 900 yen for one day data collection
for one respondent, including costs for both transmitting the data and GPS tracking. After thediary survey, the respondents were asked to answer some questions regarding comparison
between the mobile phone-based survey and the paper-based survey.
Comparison of Diary Data between Mobile Phone Survey and Paper-Based Survey
Data Handling Time of the Surveyor
Data handling time to complete an electronic database was much less in the mobile phone survey
than in the paper-based survey. In the 1st survey, it took about 3 minutes at minimum for thesurveyor to input two-day activity diary data of one respondent, from the paper-based survey
sheet into a Microsoft Excel sheet. Whereas, it took only 30 seconds to combine two-day activity
diary data sent by e-mail from the mobile phone device and to make an Excel sheet for one
respondent. It was found that time required for editing and inputting the data was considerably
reduced in the mobile phone survey, comparing with the conventional paper-based activity diarysurvey. In the 2nd survey, the respondents themselves input four-day activity diaries from thepaper-based survey sheet into an Excel sheet. The instructor of the graduate course managed thedata handling of three-day activity diary data collected by the mobile phone system and sent thedata to the respondents.
Characteristics of the recorded data
In the 1st survey, the average number of the recorded activities in the mobile phone was 15.0/day
and that of trips was 2.8/day. There was not a significant difference in the number of recorded
activities and trips between the mobile phone and the paper-based diary. However, there weresome problems in the data collected by the mobile phone such as:- two consecutive activities overlapped in timing;- existence of blank time period; andTRB 2006 Annual Meeting CD-ROM

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8- several in-home activities not recorded.
A total of 69 activities recorded in the paper-based diary were not recorded in the mobile phone.
Twenty-seven of them were “sleep” activities. For the remaining 42 activities, 24 of them werein-home activities and 21 of them were activities engaged at midnight. On the other hand, a totalof 35 activities recorded in the mobile phone were not recorded in the paper-based diary. Most of
the activities were relatively short-time activities. In the 2nd survey, the average number of therecorded activities in the mobile phone was 12.1/day and that of trips was 3.7/day.
Frequency of Data Entry
Frequencies that the respondents entered information on activities were compared between themobile phone and the paper-based diary. In the 1st survey, the average number for thepaper-based diary was 2.1/day and that for the mobile phone was 8.1/day. There was no
respondent who recorded data more frequently in the paper-based diary than in the mobile phone.
This means the respondents recorded activities more frequently in the mobile phone than in thepaper-based diary. This could be due to the higher flexibility in space and time for recording datain the mobile phone survey. In the 2nd survey, the average number of the frequency of data entry
was 3.7/day for the mobile phone. The respondents were not required to record data entry time
for the paper-based diary in the 2nd survey.
“Time Lag” between Activity Implementation and Data Entry
Figure 2 shows cumulative distribution of a “time lag” from the end time of an activity (activity
implementation) and the time when the activity was recorded. For example, if an activity end
time was 10:00 a.m. and the activity was recorded at 10:30 a.m., the “time lag” is 30 minutes. If
an activity was recorded before the activity end time, the “time lag” becomes a negative value.
As shown in the figure, the “time lag” was shortest in the mobile phone of the 1st survey andlargest in the paper-based diary of the 1st survey. The averages of the mobile phone of the 1st
survey, mobile phone of the 2nd survey and paper-based diary of the 1st survey were 87 minutes,
179 minutes and 445 minutes, respectively. In the mobile phone of the 1st survey, 39.6% of thetotal activities were recorded within 5 minutes of the activity implementation, whereas 26.6% of
the total activities were recorded after 600 minutes (10 hours) in the paper-based diary of the 1st
survey. The higher frequency and shorter “time lag” suggest that respondents can enter activity
information into the mobile phone software at anytime and anyplace, and from clearer memory,
so data accuracy could be higher than the traditional paper-based survey. An intriguing result isthat about 10% of the activities in the mobile phone of the 1st and 2nd surveys were recorded
before the activity was finished. But in terms of inter-personal variability, the average, minimum,
maximum of each respondent’s average “time lag” were 105 minutes, -12 minutes and 895
minutes, respectively, and the standard deviation of all the respondents’ average “time lag” was
153 minutes. Thus, the “time lag” was much dependent on individuals. In the 2nd survey, theaverage, minimum, maximum of each respondent’s average “time lag” were 200 minutes, 13
minutes and 524 minutes, respectively. The difference of “time lag” between the mobile phone
diaries of the 1st and 2nd surveys could be due to the difference in survey method, software andrespondents, but we cannot know the specific reason from this study.

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100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

mobile phone,
1st survey
paper-based,
1st survey

601<

481-600

361-480301-360

241-300

181-240

121-180

91-120

61-90

46-60

31-45

26-30

21-25

16-20

11-15

0-5

6-10

mobile phone,
2nd survey<0% of cumulative number ofrecorded activities

Ohmori, N., M. Nakazato, N. Harata, K. Sasaki and K. Nishii

time lag (min.)

FIGURE 2 Time Lag between Activity Implementation and Data Entry
Locations Where Data Were Recorded
As shown is Figure 3, in terms of locations where activities were recorded, in the paper-based
diary of the 1st survey, 67% of the activities were recorded in their home and 32% were in theirwork or school places. Only 1% of the activities in the paper-based diary were recorded while
traveling. On the other hand, 47% of activities in the mobile phone of the 1st survey wererecorded in their home, 22% were in their work or school place and 11% were in other locations.
About 20% of the activities were recorded while traveling, of which, 10% was traveling by train,
5% was walking and 1.5% was while riding a bicycle. In the mobile phone of the 2nd survey,
35% of the activities were recorded in their home, 35% were in their school place and 20% werein other locations. 35% were recorded while traveling of which 21% were traveling by train,
7.5% were walking and 2% were while riding bicycle. The results show that the mobile phone
makes it possible for the respondents to enter activity diary information without spatial andtemporal constraints.
mobile-phone,
2nd survey

homework orschool placeotherlocationswhile travelingmobile-phone,
1st survey

paper-based,
1st survey
0%

20%

40%

60%

80%

100%

FIGURE 3 Locations Where Data Were Recorded

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Respondents’ Preference in Different Survey Methods
This section presents the analysis of the respondents’ answers to questions about the survey
methods after the activity diary survey was finished.
Impacts of the Mobile Phone Survey on the Respondents’ Behavior
Three respondents in the 1st survey were conscious of being positioned automatically by GPS,for example, they answered that “I didn’t engage in activities which I didn’t want to be known,”
and “I did activity-travel patterns as easy as I can record them.” Fifteen of them answered that
their activity-travel behavior and mobile phone use were at least affected by participating in thesurvey. For example, some respondents took into consideration the battery capacity of the mobile
phone device, so they did not travel further than usual from their home and office or school. For
the participants who used their own mobile phone, since they had to stop the system to make aphone call or to send an e-mail, they communicated less with the mobile phone than normal
usage. Automatic positioning and battery problems could cause a little different activity-travel
behavior from the normal pattern.
Perceived Time to Complete Data Entry
To investigate the respondents’ burden, the respondents were asked which survey method,
mobile phone or paper-based diary, took longer time to complete data entry of the activity diary.
Table 2 shows the result. For the “non-au-users” of the 1st survey, although 30% of the
respondents answered that it took shorter time in the mobile phone to complete data entry, 40%of them felt that it took longer time in the mobile phone survey. It was found that the
respondents’ burden would depend on each respondent’s characteristic and her/his literacy ofmobile phone use. For the 2nd survey which required recording telephone use diaries, more
respondents answered it took longer time in the mobile phone.
TABLE 2 Respondents’ Perceived Time to Complete Data Entry (the Number of the
Respondents)“non-au-users”“au-users”
stnd
st
1 day 2 day 1 day 2nd day
Shorter in the mobile phone
9
7
3
3
Same
10
9
0
0
Longer in the mobile phone
11
14
2
3
N/A
0
0
1
0
Development of GPS-Equipped PDA-Based Activity Diary Survey System
In this chapter, the development of a PDA-based system for collecting data on activity diaries
and positioning data is described. Figure 4 shows the PDA tool used in this study. The PDA is"Linux-ZAURUS" by SHARP Corporation, which is equipped with a VGA-size display and runs
on a Linux operating system with the Japanese language. The GPS receiver is equipped on the
CF (compact flash) slot in the PDA. This system is developed focusing on two points. One is toconstruct a closed survey environment on the PDA to save telecommunication costs.
Telecommunication costs for collecting and storing data are the weak points ofmobile-phone-based survey systems, because the cost becomes more expensive as data quantity

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becomes larger from one respondent. The other point of focus is to construct a flexible survey
system that is easy to expand to other devices such as mobile phones. Considering an application
to a certain size of travel-survey, the costs and management of PDA can be a weak point.
Therefore, the system was developed as a closed survey system with flexibility for expanding. To
ensure these conditions, the questionnaire is developed based on a Web technology. A Web server,
a Web browser and questionnaires were installed on each PDA. The PHP (Hypertext
Preprocessor) script controls the questionnaire and SQL (Structured Query Language) databaselanguage also associates with this system in the data management. The data can be saved in themain memory of PDA at any point of answering questions. Respondents start answering again
from the questions not finished yet. The positioning data from the GPS receiver is also stored in
the main memory of PDA as a CVS type file by self-made data logger.

GPS receiver

FIGURE 4 Snapshot of Linux PDA and GPS Receiver
The first question of an activity diary is to answer the time of going to bed last night andgetting up this morning. Next, respondents are to answer the attributes of the first activity in theday, such as the start time, end time and the type of activity. The alternatives of activities vary
according to the current location, in-home or out-of-home. If the current location is in-home,meals, housework, family care, leisure, communications, sleep, parallel activities, and others arelisted as the alternatives. If the current location is out-of-home, meals, work/study, daily
shopping,
non-daily
shopping,
medicalcare,familycare,leisure,communications/social-activities sightseeing/recreation, sleep, and others are listed as thealternatives. Sleep, meals, and family care are the mandatory activities. Housework, daily
shopping, and work/study are categorized as the maintenance activities. Leisure,communication/social-activities, non-daily shopping and sightseeing/recreation are categorized
as discretional activities. After finishing of entering the attributes of an activity, the system asks
whether the next activity is travel or not, to update the information of the current location. In thequestion of attributes of travel, several psychological questions are added. For example, in caseof travel by car driving, the reason of choosing car driving, the reason and timing of the route
choice, the possibility of the route change and the alternatives of the mode are asked to the
respondents. After answering the questions associated with the travel, the questions about thereason of location/facility choice and the flexibility/changeability of time allocation are added to

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the ordinary questions of the attributes of activities.
The PDA is equipped with a small keyboard and a touch-display system for data input.
Respondents use properly these devices according to the type of data at data entry of the survey
system. Respondents basically select the answer to the questions from displayed alternatives
using a touch pen. Input from keyboard is necessary in case of no adequate alternatives in the list.
The system also examines the consistency of the answers and requires corrections if there is any
inconsistency in the answers. The collected two types of data, GPS positioning data and activity
diary data, are analyzed in a GIS.
The Validity of the PDA-Based Survey
A pilot survey was conducted using the PDA-based system in January 2004, which was a
one-week survey on two respondents. After the first survey, the alternatives and construction of
the questionnaire were modified based on the suggestions from the respondents. The second
empirical survey was conducted in January 2005, which was also a one-week survey on two
respondents. In the second pilot survey, we administered a paper-based activity diary survey tothe same respondents at the same time to compare the efficiency of the PDA-based survey. The
paper-based activity diary survey was a bar-chart type. The reason for adopting a bar-chart type
diary was based on the result of our preceding research (14).
The result of activity duration for each activity in the second pilot survey is shown in
Table 3. The parallel activities are counted doubly and the start time of sleeping is different
between consecutive two days. Therefore, the sum of activity durations is different and exceeds
occasionally twenty four hours. The figures in parenthesis are the activity duration from thepaper-based survey. The bold figures indicate that the activity duration in the paper-based survey
is longer than that of the PDA-based survey, and figures with an underline indicate the counter
case of the bold figures. The activity durations of mandatory activities were longer in the
PDA-based survey, especially in out-of-home activities. As opposed to that, the activity durationsof in-home discretional activities and travel were longer in the paper-based survey. Thesetendencies kept the same during the survey period. Table 4 shows the number of recorded
activities. Even the number of activities did not accord between the PDA and paper-based survey.
TABLE 3 Activity Duration of Each Activity Type (One Respondent)
Day
1st
2nd
3rd
4th
5th
6th
7th
8th

Mandatory
440 (430)
665 (725)
395 (455)
420 (320)420 (740)
460 (450)
540 (540)
630 (625)

In-home
Maintenance0 ( 0)
410 (390)280 (280)510 (430)
105 (125)
380 (300)
415 (415)
610 (550)

TRB 2006 Annual Meeting CD-ROM

Discretional
150 (130)300 (310)
320 (300)
60 (120)210 (300)
220 (320)
60 ( 60)
20 ( 80)

Mandatory
0 ( 0)
0 ( 0)
80 ( 80)
0 ( 40)0 ( 0)
0 ( 0)
15 ( 15)0 ( 0)

Out-of-home
Maintenance Discretional
440 (430)
185 (190)
115 (115)0 ( 0)
110 (110)230 (225)
350 (310)
0 ( 0)325 (320)0 ( 0)
215 (205)
0 ( 0)
0 ( 0)
285 (280)
170 (165)0 ( 0)

Travel65 ( 90)
10 ( 20)85 (110)40 ( 40)80 ( 85)
25 ( 35)
95 (100)
70 ( 80)

Paper revised from original submittal.

Ohmori, N., M. Nakazato, N. Harata, K. Sasaki and K. Nishii

13

TABLE 4 Number of Recorded Activities
Day
1st
2nd
3rd
4th
5th
6th
7th
8th

Mandatory
2 (2)
4 (4)
2 (2)
2 (2)
3 (4)
4 (4)
2 (2)
5 (5)

In-home
Maintenance
0 (0)
3 (3)
2 (2)
5 (4)
3 (3)
7 (7)
3 (3)
6 (7)

Discretional
2 (2)
4 (4)
1 (1)
1 (2)
4 (4)
3 (5)
1 (1)
1 (2)

Mandatory
0 (0)
0 (0)
1 (1)
0 (1)
0 (0)
0 (0)
1 (1)
0 (0)

Out-of-home
Maintenance Discretional
2 (2)
1 (1)
1 (1)
0 (0)
1 (1)
2 (2)
2 (3)
0 (0)
2 (2)
0 (0)
2 (2)
0 (0)
0 (0)
4 (4)
3 (2)
0 (0)

Travel
5 (6)
1 (2)
6 (6)
4 (4)
4 (4)
2 (3)
5 (5)
6 (6)

CONCLUSIONSA GPS mobile-phone-based activity diary survey system and a GPS-equipped PDA-based
activity diary survey system were developed as intelligent survey methods for collecting activity
diary data. Pilot studies were conducted to compare data collected by the mobile devices withdata collected by the conventional paper-based questionnaire surveys. From the comparative
analyses, the following results were found for the GPS mobile-phone-based survey system:- Data handling time for the surveyor for data analysis was considerably reduced in the mobile
phone survey compared with the conventional paper-based activity diary survey.
- The frequency of data entry was higher in the mobile phone survey than in the conventional
survey and the “time lag” between activity implementation and data entry was shorter in themobile phone. This could be the advantages from flexibility in space and time for recordingdata.
- Battery consumption in the mobile phone software affected the respondents’ activity-travel
behavior. The use of telecommunications by mobile phone was also affected for own mobile
phone users (“au-users”).
- Respondents’ burden would depend on their characteristics and literacy of mobile phone use
in the mobile phone survey.
In the PDA-based survey, the number of activities collected by the paper-based survey
was generally larger than that collected by the PDA-based survey. The total activity duration of
the paper-based survey, especially of in-home activities and travel, was longer than that collectedby the PDA-based survey. It might have been caused by a pre-programmed check system in the
PDA software, because the survey system required entering parallel activities strictly andprecisely. The respondents might avoid entering data correctly. This is one of the points to be
improved through this survey experiment.
There remains space for improvement in the software developed in this study towards amore user-friendly system and more accurate data collection. Future research concerns
comparison between the GPS mobile-phone-based system and the GPS-equipped PDA-based
system. In the near future, the GPS mobile-phone-based survey or the GPS-equipped PDA-based
survey could be used to complement or substitute the conventional paper-based or PC-based
activity diary survey methods. Complementation means using a mobile device as a memory
jogger for recording out-of-home activities and travels. Substitution means no need of apaper-based questionnaire survey sheet. Geographical presentation of the current position andtravel trajectory on the mobile phone or PDA monitor display using a GIS map could contributeto increasing respondents’ interest, motivation and willingness to participate in the survey.

TRB 2006 Annual Meeting CD-ROM

Paper revised from original submittal.

Ohmori, N., M. Nakazato, N. Harata, K. Sasaki and K. Nishii

14

ACKNOWLEDGEMENTS
The authors gratefully thank to Dr. Yusuke Konishi of Center for Spatial Information Sciences(CSIS) in the University of Tokyo, who developed the original Java program of the automatic
GPS data collection for the “au” mobile phone system. We also express our appreciation to Mr.
Mirai Ohi and Mr. Akira Endo for supporting the development and experiment of PDA-based
survey.
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TRB 2006 Annual Meeting CD-ROM

Paper revised from original submittal.