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Diagnosis of alternative patterns

Internet GIS-Based Activity-Travel Simulator for
Investigating Alternative Activity-Travel
Patterns
Morimichi Nakazato, The University of Tokyo
Nobuaki Ohmori, The University of Tokyo
Sadayasu Aono, The University of Tokyo
Takuya Maruyama, Japan Society for the Promotion of
Science
Noboru Harata, The University of Tokyo
Conference paper
Session 2.4 Simulating behaviour
The Expanding Sphere of Travel Behaviour
Research
11th International Conference on Travel Behaviour Research
Kyoto, 16-20, August 2006

Internet GIS-Based Activity-Travel Simulator for Investigating
Alternative Activity-Travel Patterns
Morimichi Nakazato
Institute of Environmental Studies, The University of Tokyo, Japan
Nobuaki Ohmori
Department of Urban Engineering, The University of Tokyo, Japan
Phone: +81-3-5841-6232
Fax:+81-3-5841-8527
E-mail: nobuaki@ut.t.u-tokyo.ac.jp
Sadayasu Aono
Department of Urban Engineering, The University of Tokyo, Japan
Takuya Maruyama
Japan Society for the Promotion of Science, Japan
Noboru Harata
Department of Urban Engineering, The University of Tokyo, Japan

Abstract
This paper reports the development of an integrated system for data collection, analysis,
representation and evaluation of individual activity-travel patterns, using GPS mobile phones
and Web GIS technologies, and its application to travel feedback programs. A GPS
mobile-phone-based survey system was developed to collect information on travel diaries andtravel routes, which were used as an input to the Internet GIS-based activity-travel simulator.
The simulator provided information on diagnostic indices and spatial movement of the current
travel pattern and alternative travel patterns of different travel modes. Participants were able
to compare the current travel pattern with alternative ones on the Web browser, investigating
diagnostic indices and spatial movements on a map. The system was applied to the travel
feedback program for the employees working in the Osaka Prefectural Government. The
system, as a new communication tool of the travel feedback program, contributed to
improving the participants’ attitudes and to changing travel behavior towards decreasing
car-use.

Keywords
Internet GIS, Activity-Travel Simulator, GPS mobile phone, Travel Feedback Program

Preferred Citation
Nakazato, M., N. Ohmori, S. Aono, T. Maruyama and N. Harata (2006) Internet GIS-based
activity-travel simulator for investigating alternative activity-travel patterns, paper presented
at the 11th International Conference on Travel Behaviour Research, Kyoto, August 2006.

1. Introduction
For sustainable cities, reducing car-use has been a main target in transportation policy.
Transportation demand management (TDM) measures such as Park & Ride and carpooling
have been introduced for the last two decades. However, these measures do not work
effectively unless travelers themselves identify their car-use has brought about a lot of
problems against sustainable cities. In this context, encouraging travelers to become involvedin environmentally friendly travel patterns is one of the effective and promising policy
measures to reduce car-use. Jones (2003) called such approaches soft measures in mobility
management. The effectiveness of the approaches has been demonstrated by previous
research, e.g., Individualized Marketing (Brög, 1998), Travel Smart (Department of Transport,
Western Australia, 2000), Travel Blending (Rose and Ampt, 2001) and the Travel Feedback
Program (TFP) (Taniguchi et al., 2003). These behavior modification programs are referred toas travel feedback programs (Fujii and Taniguchi, 2005). In these programs, the first step isobtaining information on travel diaries from participants to diagnose their travel patterns.
Next, the programs provide the participants with information on the CO2 emissions they
produced, and on public transport as an alternative mode, and/or advise how to reduce car-use
based on their current travel patterns. Some programs ask the participants to make behavioral
plans (Fujii and Taniguchi, 2005). The existent research in western countries reports that
aggregate car-use of the participants reduced by about 10-20% after participation in the
programs. Also in Japan, an interest in these programs has rapidly been increasing. In
particular, the Travel Feedback Program has been implemented in a lot of cities (Japan
Society of Civil Engineers, 2005).
However, the programs spend many human and financial resources at each stage as collecting
participants’ travel diaries using paper-based questionnaire sheets, analyzing them andadvising the participants to use car more environmentally friendly. Data accuracy of travel
diaries collected using paper-based questionnaire sheets has been a problem. It takes muchtime and money to generate individualized alternative activity-travel patterns of moreenvironmentally friendly for each participant. Daito et al. (2005) developed the Travel
Feedback Program system using Web technologies (WEB TFP), which collects travel diaries
from participants on the Web browser. This system alleviates spatial constraints in
implementing the program. It has been applied especially to the workplace-based travel
feedback program. For example, more than 700 employees in a company working at 13
offices located in several parts of Japan participated in the WEB TFP (Ozawa et al., 2006).
However, the WEB TFP system does not collect spatial information on travel patterns and notprovide the participants with it on the Web browser. Not only temporal information of travel
patterns but also spatial information of them is very useful for individuals to understand andinvestigate their current and alternative travel patterns in urban space (e.g., Jones 1982; Joneset al., 1983; Ohmori et al., 2005). To collect more accurate and detailed information on
individual travel patterns, positioning technologies such as Global Positioning System (GPS)and Global System for Mobile Communications (GSM) can be applied (e.g., Murakami and
Wagner, 1999; Ohmori et al., 2000; Asakura and Hato, 2004). In addition, Geographic
Information System (GIS) is a very effective tool for the management, analysis andrepresentation of spatial elements of the transportation network and individual travel patterns.
There has been some research to explore the possibility of developing integrated models ofactivity-travel patterns and GIS (e.g., Golledge et al., 1994; Kwan, 1997).
1

The authors have been developing GIS-based activity-travel simulators, which can generatealternative activity-travel patterns and represent them on GIS (Ohmori et al., 2005). There ispossibility to apply this system to travel feedback programs as a communication tool forinteractive diagnosis of individual/household activity-travel patterns. This paper reports thedevelopment of an integrated system for data collection, analysis, representation andevaluation of individual activity-travel patterns, using GPS mobile phones and Web-GIS
technologies, which is named iSMAP (Internet-based Simulation Model for Activity
Planning), and its application to the travel feedback programs. The system developed in thisstudy does not recommend which travel pattern is better for environment or individual health,but the participants themselves can investigate alternative activity-travel patterns on the Webbrowser.

2. Development of the System
2.1. GPS Mobile-Phone-Based Travel Diary Survey System
Usually in the travel feedback programs, paper-based questionnaire sheets or Web-basedquestionnaires have been used to collect participants’ travel diaries. In this study, a GPS
mobile-phone-based travel diary survey system was developed to collect information on
individual travel patterns, based on the authors’ previous study (Ohmori et al., 2005). The
advantages of this system are considered as follows:- to directly collect electronic data on travel diaries and to transmit the data through awireless network (GSM network and the Internet);- to automatically collect positional data at a regular time interval to specify
origins/destinations and travel routes; and- to reduce the survey costs of time and money both for distribution and collection ofsurvey materials, and for transmitting, editing and inputting the collected data.
The software programmed in Java language works on the mobile phone devices with GPS
installed of “au” by KDDI Corporation, for entering information on travel diaries. The “au”
employs “gpsOne”, which is called the Assisted GPS (see KDDI website). It calculates thecurrent 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 becollected even if GPS is not available or it is carried in a coat or jacket pocket. The software isdownloaded via the wireless network and installed in the mobile phone. Positional data
(longitude and latitude) are automatically collected at regular time intervals. Travel diaries
and GPS tracking data are transmitted to a server computer. Participants just carry the GPS
mobile phone, and push some buttons whenever they leave origins and arrive at destinations.
They can enter information on trip purposes (commute, business, going home, private,
shopping/eating out, escort, and other) and (main and access/egress) travel modes into the
GPS mobile-phone-based survey system. The data collection system was designed to impose
the minimum respondent burden on the participants.

2.2. Internet GIS-Based Interactive Travel Feedback System
MapInfo MapXtreme software was used for the Internet GIS-based interactive activity-travel
simulator, iSMAP. By using the Web GIS software, it becomes very easy to manage GIS data2

and represent spatial information in the Web environment (see Aono et al., 2004; Aono et al.,2006). Programs of data management and representation on the Web browser were written in
VBScript. When this research was launched into, the authors had thought that it would bebetter for the participants to access to the program website from their home or office once aday. The system consists of the following two parts:- completing the travel diaries and spatial information on travel patterns; and- simulating alternative travel patterns.
2.2.1. Completing Travel Diaries and Spatial Information on Travel Patterns
On the Web browser, one-day travel diary and travel trajectory collected by the GPS
mobile-phone system are represented in spatial and temporal dimensions (see “the current
travel pattern” of Figure 1). GIS raster data of ProAtlas map in Osaka area were used toeasily identify urban space and individual spatial travel patterns. Also several diagnostic
indices about the day’s travel pattern such as travel times, travel distances, travel costs byeach travel mode, the total daily CO2 emissions and the total daily calorie consumptions arecalculated based on the travel data and represented on the Web browser. The participants canreflect their current travel patterns on that day investigating the represented information.
The names of origins and destinations can be directly entered on the Web browser. When theparticipants did not enter information on trip purposes and travel modes or entered incorrect
information into the GPS mobile-phone-based survey system, they can enter or correct the
information on the Web browser. Some trips might be missed or incorrectly represented in thetravel diary, because they forgot to push buttons of the GPS mobile phone when leaving
origins or arriving at destinations. They can modify the travel diary by deleting and adding
trips on the Web browser. Spatial information on origins and destinations can be also easily
modified on the Web GIS.
2.2.2. Simulating Alternative Travel Patterns
Alternative travel patterns of different travel modes are generated on condition that locations
and start times of out-of-home activities engaged in on the day are fixed. The participants canchange travel modes of any trips of the current travel patterns to alternative ones. Alternative
main modes are train, bus, car, taxi, bicycle and walk. A GIS database of railway network in
Osaka area, including 1,419 railway stations in 22 railway companies, was used to calculate
travel times and travel routes by train. Travel time by train between an origin and a
destination is that of the route of the minimum travel time using the nearest railway stations
from the origin/destination. A database of travel fee by train was originally prepared. We did
not prepare bus network data. If the participants choose train or bus as a main mode, they alsochoose access/egress modes. Available access/egress modes to/from the railway stations arebus, car, taxi, bicycle and walk. Travel routes of alternative patterns are represented on the
GIS map. When the alternative mode is train, the travel route is represented by polylines
connected with intermediate stations. Whereas the alternative mode is not the train, the travel
route is the same as the current trip. In “the alternative travel pattern No.1” of Figure 1, achange in travel routes of some trips from car to subway is represented. Information on
alternative travel patterns is added below the current travel pattern successively on the Webbrowser. Participants can compare the current travel pattern with alternative ones,
investigating the spatial movements and diagnostic indices of the travel patterns, and areasked which pattern they prefer. In the last stage, the system asks the participants which
3diagnostic indices such as travel times, travel costs, CO2 emissions and calorie consumptions
affected their preference, and the constraints of their trips.
Travel diary (trip start/end times,
origins and destinations, trip purposes,
travel modes and trip distances)

Diagnostic indices of the travel pattern (travel times, trip
distances and travel costs by each mode, the total daily
CO2 emissions and calorie consumptions)
Origins/destinations (star-shaped points) andtravel trajectory (generated from positional data)

The current
travel pattern

The alternative
travel pattern No.1

Changes are yellow colored. Worse in red.
Better in blue.

Travel route of the alternative
pattern (by subway)
Changes in travel diary are colored byyellow.

Improved indices are colored by red andworsened indices are colored by blue.

Figure 1 Snapshot of the iSMAP (Representation of the Current Travel Pattern of a Day andan Alternative Travel Pattern)

3. Application of the System to the Travel Feedback
Program in Osaka
To investigate how the system can work as a communication tool of the travel feedback
program and to identify problems occurring in its practical use, a pilot study was conducted
for the participants working at the Department of Civil Engineers, in the Osaka Prefectural
Government, in November to December 2005. As a rule, the office prohibits its employees tocommute by car. Figure 2 shows a flowchart of the travel feedback program. The program
was basically implemented using the WEB TFP system (Daito et al., 2005).
In the first stage of the program, a questionnaire survey was conducted for obtaining
information on daily car-use, attitude for transport and environment and habitual intensity,4and for screening the sample. Questions about attitude for transport and environment were to
ask answers of five-point scale for the following five questions: “Do you think car-use is notgood for your health?”, “Do you think car-use is not good for environment?”, “Do you think it
is better to reduce car-use?”, “Do you think reducing your car-use is difficult?” and “Do you
think you will try to reduce your car-use?”. Questions about habitual intensity were to ask
which travel mode they use when traveling for a total of 10 trip purposes, e.g., visiting
friend’s house, business, going to convenience stores, shopping clothes, etc.
The 1st questionnaire survey for obtaining information on daily car-use, attitude for transport andenvironment and habitual intensity, and for screening the sample using the WEB TFP system
The 1st travel diary survey using the GPS
mobile phone system (Nov. 26 – Dec. 4)

The 1st Travel diary survey using the WEB
TFP system (Nov. 24 – Dec. 1)

Diagnosis of the current travel patterns andinvestigation into alternative travel patterns
using the iSMAP system (Dec. 5 – Dec.6)

Diagnosis of the current travel patterns
using the WEB TFP system

Self evaluation of the current travel patterns and making behavioral plans using the WEB TFP
systemThe 2nd travel diary survey using the WEB TFP system (Dec.8 – Dec.14)
The 2nd questionnaire survey for obtaining information on attitude for transport and environmentand habitual intensity, and evaluation of the travel feedback program using the WEB TFP system

Figure 2

Flowchart of the Travel Feedback Program in the Osaka Prefectural Government

As shown in Figure 2, two different systems (the iSMAP and the WEB TFP) were used forcommunication tools in the diagnosis step. The WEB TFP system required participants torecord two-weekend-day travel diaries (trip start/end times, destinations, trip purposes andtravel times by each travel mode) on the Web browser and showed diagnostic indices of thecurrent travel pattern such as total travel time, percentage of car-use, fuel consumptions, CO2
emissions and calorie consumptions. A total of 70 employees, who had a driving license anddaily used a car, were recruited as the participants to the program. Twenty of them
participated in the program using iSMAP and the rest 50 employees participated in the
program using the WEB TFP system. All the participants were males and 30’s to 50’s years
old.
The GPS mobile phones pre-installed with the software for travel diary data collection were
distributed to the participants of the iSMAP group. Ten of them were explained in face-to-faceby the instructor how to use the mobile phone in the 1st travel diary survey. The participants
were asked to carry the mobile phone and record travel diaries on a total of 4 weekend days
during Saturday, November 26 to Sunday, December 4, 2005. They were asked to charge themobile phone while in their home and office. They were asked to power the mobile phone on
and push buttons when they start trips, and enter information on trip purposes and travelmodes if possible. Positional information on longitude and latitude was collected every 2
5minutes. When arriving at destinations, they were asked to push buttons and power it off. This
process saved the battery consumption of the mobile phone.
Immediately after the 1st travel diary survey, on December 5 or 6, the participants of theiSMAP group participated in a face-to-face interview with the instructors using the iSMAP at
the office of the Department of Civil Engineers, in the Osaka Prefectural Government. Two
laptop computers with the Internet access were prepared for the interviewing survey. At the
beginning, the authors had intended to use the system as a self-operating system. However,this was the first trial to apply it to the travel feedback program and problems might possibly
have occurred in self-operating the system. Therefore, we decided that the instructor
supported to operate the system in face-to-face interviewing.
First, the instructor inputted the participant’s ID number and password, and selected a day outof the 4 weekend days. Then the day’s travel diaries and travel route on GIS map appeared.
The participants entered the names of trip start/end locations on the Web browser. As for thetrips of which they did not enter the whole information, the participants were asked to enter
the rest information into the Web browser. Diagnostic indices calculated based on the travel
diary were represented: travel times, travel distances and travel costs by travel mode, and thetotal CO2 emissions as an index of environment and the total calorie consumptions as anindex of health in the day. Next, the interviewer asked the participant, “Could you change
travel modes in any trips?” The system showed information on an alternative travel pattern on
the Web browser below the current pattern, if he changed travel modes. The participant
identified the changes in spatial pattern and difference of diagnostic indices between before
and after the mode change. This process was repeated until the participant considered that hehad no more alternative patterns. Finally, he was asked, “Which travel pattern do you prefer,the current travel pattern or one of the alternative patterns?” and “Which diagnostic indicesaffected your preference?” If he preferred the current travel pattern, he was asked to choose
the reasons why he could not prefer the alternative travel pattern from a list, e.g. problems inaccess/egress, frequency of public transport, luggage, weather, etc. It took about 30 minutes
for a participant to complete the interview.
After the interview, the 2nd travel diary survey was conducted using the WEB TFP system onweekend days on December 8 to December 14. Lastly, the 2nd questionnaire survey was
conducted for obtaining information on attitude for transport and environment, and evaluationof the travel feedback program.

4. Results of the Application
4.1. Completing Travel Diaries
A total of 30 daily travel diaries of 20 participants were confirmed in the interview. About
20% of the participants did not enter the information on trip purposes and travel modes in the
GPS mobile-phone-based survey system. Some trips were not recorded correctly. In a total of
13 trips, the participants forgot to push buttons of the mobile phone when leaving origins
and/or arriving at destinations. On the contrary, a total of 6 trips were recorded by mistake
when they did not make trips. The mobile phone exhausted the battery during trips in a totalof 11 days. Multiple trips were sometimes consolidated into one trip. In advance of theinterview for investigating travel patterns, the surveyor checked these trips of incomplete
6information. In the face-to-face interview, it took nearly 30 minutes in average to modify thetrip information and to complete two-day travel diaries for one participant. Another reason oftaking much time was that laptop PCs with the Internet access by PHS (Personal Handyphone
System) of which the transmission speed was relatively slow (256kbps and 32kbps) was used.

4.2. Simulation of Alternative Travel Patterns
For 20 participants, alternative travel patterns were investigated for a total of 24 daily travel
patterns of 17 participants. Three participants were not able to use other travel modes than car,because their trip destinations were closer to their home than to any railway stations.
Seventeen of the 24 simulated travel patterns were the changes from car to train. The
alternative travel patterns were preferred to the current pattern in 7 of them. The rest of thesimulated patterns were the changes in travel mode from car to bicycle, car to bicycle and taxi,
bicycle to walk, etc. It took less than 5 minutes to investigate at most two-day travel patterns
for one participant. Figure 3 shows an example that a participant preferred the alternative
pattern with mode change from car to train to the current pattern.
OriginThe current
travel route bycar

The alternative
travel route bytrain
Destination

The current travel pattern: two trips bycar
Total travel time: 230 min.
CO2 emissions: 21.8kg
Calorie consumptions: 389.7kcal

Figure 3

The alternative travel pattern: two trips
by train
Total travel time: 148 min.
CO2 emissions: 2.7kg
Calorie consumptions: 330.4kcal

An Example that a Participant Preferred the Alternative Pattern with Mode Change
from Car to Train to the Current Pattern

4.3. Changes in Attitude and Travel Behavior before and after theTravel Feedback Program
In this section, changes in attitude and travel behavior before and after participating in thetravel feedback program are summarized and compared between the iSMAP group and the
WEB TFP group. The analysis used the data collected in the 1st and 2nd questionnaire surveys
for asking attitude and habitual intensity and the 1st and 2nd travel diary surveys of bothgroups. Complete datasets were obtained from a total of 13 participants in the iSMAP groupand 50 in the WEB TFP group.
74.3.1. Changes in Attitude towards Transport and Environment
As for habitual intensity, the percentage the participants answered to use car for a total of 10
trip purposes decreased at almost the same rate in both groups (about 40% to 30%). In bothgroups, attitudes towards transport and environment were improved, except for the question,“Do you think car-use is not good for environment?”. The reason could be that some of them
did not realize the volume of CO2 emissions. The percentage that they answered “Yes” to thequestion, “Do you think reducing your car-use is difficult?”, especially decreased more in theiSMAP group. This result suggests that the participants were able to identify the changes oftravel patterns more concretely and realistically using iSMAP system.
4.3.2. Changes in Travel Behavior
In the iSMAP group, the numbers of all trips and car trips, in average, did not change between
the 1st and 2nd travel diary surveys, whereas the total travel time by car decreased by 16%.
Besides, the number of walk trips decreased by 78% and the numbers of train and bus trips
increased by 100%. Also the total travel time by train and bus increased by more than 100%.
On the other hand, both the number of all trips and the total travel time decreased by 9% and
22% respectively. This result indicates that the iSMAP system emphasized and promoted
public transport use. Then, we analyzed the relationships between individual characteristics(distance between their home and railway stations, preference in simulating alternative
patterns, etc.) and modal shift to public transport. However, significant relationships were notfound from the analyses. Especially in travel patterns not including shopping trips (without
luggage), car-use reduced more in the iSMAP group than in the WEB TFP group.

4.4. Participants’ Evaluation of the System
This section describes the participants’ evaluation of the system based on the analysis of thedata collected in the 2nd questionnaire survey after the feedback program. As for the GPS
mobile-phone-based travel diary survey system, 54% of the participants were imposed (alittle) burden. However, all of the participants answered that operating the mobile phone was(relatively) easy. As for the iSMAP system, more than 70% of the participants answered that itwas easy to understand the spatial elements of their travel patterns on a map. Someparticipants gave opinions such as “The speed of representing spatial travel patterns on a map
was very slow”, “I wanted to change the scale of the map”, “I wanted to do the diagnosis
process on my PC”. Most participants answered that the simulation process (77%) anddiagnostic indices (64%) were easy to understand. However, one of the participants answered,“I wanted to see not only information on environmental issues but also that on economic
issues”, “I wanted to compare travel route, cost and time between the current and alternative
travel patterns”. These answers indicate that he did not correctly understand the informationon the Web browser. It needs improvement of representation in a more understandable way.
Some of them answered, “I need information of alternative routes of less travel time reflecting
congestion.”

5. Conclusion
This paper described the development of an integrated system for data collection, analysis,
representation and evaluation of individual activity-travel patterns; the GPS
mobile-phone-based travel diary survey system and the Web GIS-based activity-travel8simulator, iSMAP. Information on travel diaries was collected using the Java application
working in GPS-mobile phones and could be also modified in the Web browser. The systemgenerated alternative travel patterns with diagnostic indices representing the travel pattern. We
applied it to the travel feedback program for employees working in the Osaka Prefectural
Government as a pilot study. The feedback program with the iSMAP contributed to improving
the participants’ attitudes towards reducing car-use. Travel distances by car decreased more
and public transport use increased more in the iSMAP group than in the WEB TFP group afterparticipating in the travel feedback program. This could be due to the function that theparticipants could interactively investigate individualized alternative travel patterns
considering spatial information and diagnostic indices.
For the future research, the process of completing travel diaries should be improved, because
it took much time to modify and complete the travel diaries collected with the GPS
mobile-phone-based survey system in the pilot study. The iSMAP can be applied to any
participants living in any cities where GIS database of transport network is available. In thisstudy, the system was applied to weekend days’ travel patterns, because the participants wereprohibited from commuting by car. We are planning to apply the system to commuters by car
and to examine the possibilities of behavioral change to environmentally friendly travelmodes. At present, since generated alternative activity-travel patterns are conditioned with
fixed locations and start times of the current activities, only changes in travel modes are
examined. We try to improve the system to generate more flexible alternative travel patterns,
incorporating not only travel modes but also locations, time of day and the sequence of theactivities. Other diagnostic indices such as the volume of environmental exposure to air
pollution such as NOx and PM would be useful for self diagnosis of travel patterns.

Acknowledgement
The authors express our gratitude to Osaka Prefectural Corporation for Agricultural Land andDevelopment and Greenery Environment Promotion, and Mr. Takehiko Daito at
Transportation System Studies Laboratory Co., Ltd. for a great help in managing the Osaka
prefecture travel feedback program. We also thank Professor Takashi Uchida at Osaka City
University for useful advises to the system development.

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