THE EFFECTIVENESS OF SOCIAL
EXPERIMENTS ON VERIFICATION OF
PRE-ESTIMATED ROUTE CHOICE MODEL
Yalcin Alver, Kumamoto University, Graduate School of
Science and Technology
Shoshi Mizokami, Kumamoto University, Civil andEnvironmental Engineering
Conference paper
WS.2.1The Expanding Sphere of Travel Behaviour
Research
11th International Conference on Travel Behaviour Research
Kyoto, 16-20, August 2006

THE EFFECTIVENESS OF SOCIAL EXPERIMENTS ON
VERIFICATION OF PRE-ESTIMATED ROUTE CHOICE
MODEL
Author 1: Yalcin Alver
Department: Graduate School of Science and Technology
Organization: Kumamoto University
Country: JapanPhone: 081-96-342-3541
Fax:
081-96-342-3507
E-mail: yalcinalver@yahoo.com
Author 2
Department
Organization
Country: Shoshi Mizokami: Kumamoto University: Civil and Environmental Engineering: JapanAbstract
In this study, a route choice model was investigated with the information of discounted
expressway toll in Kumamoto, Japan. To convert some of the truck traffic from ordinary roads
to expressway one pre-survey and two experiments were conducted. After the pre-survey amodeling effort was done. In this modeling effort, both Revealed Preference (RP) and Stated
Preference (SP) data were combined and a combined RP/SP model were proposed for theestimation on route choice decision of freight and production companies. Modeling was donein four steps and finally a combined RP/SP model was estimated. Afterwards two social
experiments were conducted in Kumamoto Prefecture considering discount on expressway
toll. These experiments were conducted to identify the effects of toll discount by applying
50% discounted toll to expressway. The effects of the experiments were identified bydiscussing the surveys and traffic counts, which were done before and during the experiments.
The ability of proposed model to estimate the actual route choice decisions of considered
companies were tested. Results showed that proposed model could estimate the actual route
choice decisions of companies under toll discounts 75% in average. The estimation results forthe second experiment were better, which covers longer part of the expressway than the firstone. Transferability of the proposed model with pre-surveys’ data were tested to pooled data
which includes both actual conditions and pre-survey conditions.

Keywords
Route choice model, Transferability, Social Experiment.

1. Introduction
Increasing motorization and limited space for transportation networks cause congestion
problems in Japan. Traffic problems occur in Kumamoto City, Japan. In the city, ordinary
roads are not wide enough and truck traffic usually passes trough the city center. On the other
hand, Kyushu expressway is passing through the city center and easily accessible with several
Interchanges (IC). The main objective of this study is to convert some of the truck traffic fromcity (ordinary roads) to expressway with discounted expressway toll. For this purpose, Local
Government of Kumamoto Prefecture conducted a pre-survey and two experiments to identify
the effects of discounted expressway toll.
First, a pre-survey was conducted to clarify the actual conditions. Survey had two main parts,
first one is traffic survey to identify the traffic condition both on expressway and ordinary
road at the city center. Second, a mailed route choice survey was conducted. The target
respondents in this study are mainly freight and production companies within Kumamoto
Prefecture. These company vehicles are usually trucks and cause more traffic problems thanthe private cars. However, they do not use expressway because of budget constrains.
Afterwards, two social experiments were conducted to clarify the effects of discounted toll.
Both experiments have same specifications except for the covered interchanges. In the firstexperiment five ICs (37.8 km) and in the second one six ICs (56.2 km) were covered. 50%
discount was applied to the trips between covered ICs. During the experiments, traffic surveys
were conducted to identify the variation in traffic volume. Questionnaire surveys wereconducted to freight and production companies, bus drivers, commuters and people living
along the ordinary roads.
After the pre-survey a modeling effort spent to estimate a route choice model withinformation of discounted expressway toll. In this study, two data types were considered andcombined in the final model; Revealed Preference (RP) and Stated Preference (SP). RP data
are based on choices made under real situations. For example, actual route choice decision ofdriver between origin and destination with information of attributes of each alternative routecan be considered as RP data. Another type of data used in route choice analysis is SP data.
Different from RP, SP data are used to improve alternative set by creating hypotheticalscenarios. SP data are collected when alternatives are not yet present. The model was
estimated in four steps. Finally, a nested logit type structure is established to estimate the
combined RP/SP model. Model has three roots; ordinary road (RP), expressway (RP), andexpressway (SP).
Verification of the proposed model was done by using the data collected from social
experiments. First, the pre-estimated model was used to estimate the actual route choicedecision of the companies, which mailed questionnaire surveys were delivered during theexperiments. Estimated results for these companies with the help of proposed model werecompared with the actual choices of these companies. The estimation accuracy of the
proposed model was investigated.
Finally, the effectiveness of three pooled data was tested. Data used in the pre-estimation anddata collected during the route choice experiments from freight and production companies
1were combined in three different ways. First, collected data during the pre-survey was
combined with data collected during social experiment 1. In the second pooled data,pre-surveys data was combined data from social experiment 2. Finally, all three data;pre-survey and both social experiments were combined. By using nested likelihood ratio test,
transferability of the model estimated before the experiments to pooled data (actual
conditions) was tested. Pooled data were prepared to create new data sets, which combined SP
related data collected during the pre-survey and actual data collected during the experiments.
The objectives of the study are:
- To test the effectiveness of the route choice experiments,- To create an effective data set by combining data from pre-survey and social experiments,- To verify the estimation accuracy of the pre-estimated model.

2. Conducted Surveys and experiments
For the aim of this study, a questionnaire survey was conducted. This survey will be called
pre-survey. After the pre-survey two social experiments were conducted to identify the effects
of discounted expressway toll on different individual groups from different perspectives.
These experiments will be named as Route Choice Experiments (RCE) in this paper, because
main objective of the experiments is to identify the route choice behaviour of drivers between
expressway and ordinary roads under discounted expressway toll.

13.9 km
RCE 1

5.2 km
6.7 km

RCE 2
12 km

18.4 kmFigure 1 Study Area: Covered ICs and Distances Between Them2

2.1. Pre-survey
First survey was conducted with the help of Local Government of Kumamoto Prefecture.
Pre-survey was conducted between 25 November to 5 December 2003. The aim of the
pre-survey is to collect data for the future toll policy’s decisions to convert traffic fromordinary road to expressway. In the survey, route choice decisions and conversion
characteristics of freight and production companies were investigated under different
discounted toll levels. In addition, traffic counts and surveys were conducted to clarify theactual traffic conditions both on the expressway and on the ordinary roads at the city center. A
total of 150 questionnaires were delivered, 50 to production and 100 to freight companies.
Finally, 32 of them from production and 39 from freight companies were collected.
Pre-survey was conducted to identify the route choice decision of freight and production
companies under different discount rates. Questionnaires was made of three main parts;socioeconomic characteristics and general attitudes of the company, actual route choicedecision and travel attributes of these trips as RP data, and hypothetical discount scenarios forexpressway toll as SP data.
In the first part general information as number of employees, number and types of vehicles
were asked. In addition, companies were asked some questions about their actual route choicedecisions and factors that effect those decisions.
EXPRESSWAY TOLL QUESTIONS
From Ueki Interchange to Matsubase Interchange
Ordinary Road

Off-peak

About 1.0 hour

Peak

About 1.5 hours

If the toll will be decreased 30 percent, will you convert to using expressway? (¥1150 ¥800)
How about if the toll will be decreased 20

How about if the toll will be decreased 50

percent,

percent, will you convert to using expressway?

will you convert to using expressway? (¥1150 -(¥1150 - ¥900)¥600)
What is the reason why you don’t want to convert to expressway?
1.

The cost should be reduced as much as possible

2.

Time savings benefits is very minimal

3.

Others, specify ()

At what toll level will you convert to use expressway?
1. () % discount

2. Toll freeFigure 2 A Sample Scenario for SP questions
Second part of the questionnaire aimed to collect RP data. RP data are based on decisions
3

made under actual situations as the travel attributes of each alternative between origin anddestination. In the second part, first, a background page was shown which includes a map ofKumamoto area with zones same as in Figure 1. Then, companies were asked to draw actualroutes taken for various destination routes. Each company was asked to indicate on the map
three routes, which was chosen and shown depending on the company’s location. . As an
example, a company located at Yatsushiro area was asked to indicate the routes whentraveling to clients in Tamana/Arao, Yamaga/Kikuchi and Ozu/Aso areas. Travel time,
distance and travel cost were considered as RP data for actual route choices of companies
from collected questionnaires.
Third part consists of hypothetical discount questions. These questions were asked todetermine at what discount rate the respondent will convert to expressway from ordinary road.
For each route indicated in the map and asked as an RP data, an SP scenario was added
afterwards. As shown in Figure 2, first, the travel time of ordinary road and alternative
expressway was shown to the respondent. Then, a bidding of discount rate that will attract the
respondent to convert follows. Due to the answer for the first question follow up bids wereasked. This part aimed to identify the acceptable discount rate for expressway toll to convert
to use expressway. Details about the pre-survey were discussed deeply in Alver et al., 2005.

2.2. Route Choice Experiments
Route choice experiments are used to clarify the effects of discounted toll on route choicedecision of drivers. There are two alternative routes for drivers: First one is ordinary roadwithout any fee but unreliable travel time and congestion. Second one is expressway, withexpressway toll depends on the distance, reliable travel time and free flow traffic.
One of the main reasons, which effect the route choice decision of drivers, is travel cost. In
these RCEs, expressway toll is discounted 50% to identify the effect of expressway toll on theroute choice decision. In these RCEs, 50%-discounted toll was applied to all kinds of vehicles
for 24 hours a day. Both experiments were lasted approximately for one month. The covered
interchanges and distances between them are shown in Figure 1.
Before the experiments, details of the experiments were advertised with the help of written
and visual media. When the drivers who use expressway during the experiments were asked ifthey had heard about the social experiment, “Yes” response for the question was only 96% for
the first experiment and 98% for second one.
First, route choice experiments was conducted from November 1st to December 25th 2004,
approximately one year after the pre-survey. Fifty percent discount rate was applied to thetrips between five ICs; Ueki, Kumamoto, Mashiki, Mifune, and Mastubase. Totally, 37.8 kmof the Kyushu expressway was covered for this experiment. Second route choice experiment
was conducted from February 7th to March 4th 2005. In this experiment, Yatsuhiro IC was
added to the covered area and covered interchanges became six. Fifty percent discount rate
was applied to 56.2 km of Kyushu Expressway from Ueki IC to Yatsushiro IC.
These RCEs include many questionnaire surveys and traffic counts; before, during and after
the experiments. Traffic surveys were done on the expressway and on the alternative ordinary
roads to identify the traffic volume before and during the experiments. Traffic volume4

increased on the expressway and decreased on the alternative ordinary roads during theexperiments. Figure 3 shows the average traffic volumes on the expressway on different
time-periods. These traffic volumes also include the transit users, which did not use thediscounted section. For each route choice experiments, three traffic volumes are indicated in
the figure; average traffic volumes; one year before the experiments, one month before theexperiments and during the experiments. Parallel with the increase of expressway usage,traffic volume decreased on the alternative ordinary roads in average 10%.
35,000vehicle/day

30,00029,81530,30432,27532,482
29,10730,64927,36925,00020,00015,00010,0005,000
0
one yaerone
beforemonth
beforeduring one yaer
one
beforemonth
beforeRCE 1during

after

RCE 2

Figure 3 Comparison of Expressway Traffic Volumes for RCE 1 and 2
Questionnaires were delivered to expressway users at the egress ICs. Questionnaires were not
only delivered to expressway users but also some other individual groups; people living along
the alternative ordinary roads, freight companies, production companies, bus drivers, andcommuters. The aim of these questionnaires was to investigate how people react to theexperiment and if their route choice decision has changed during the experiment. In this study,
we had focused on the route choice decisions of freight and production companies. Thus, only
questionnaires delivered to freight and production companies were considered. In addition,questionnaires delivered to expressway users were discussed by aggregating the data into
freight and production companies with a basic classification.
2.2.1. Questionnaires delivered to freight and production companies
In this part, questionnaires delivered to freight and production companies during theexpressway toll discounts were considered. Some of the respondent are same companies
answered the questions in the pre-survey. Questionnaires were delivered and collected by
mail.
The questionnaires delivered to freight and production companies have some similar parts
with the questionnaires conducted to same type companies during the pre-survey.
Questionnaires conducted to freight and production companies are almost same except somesmall details. In the first part, three routes were asked depending on the company location.
Thus, six different questionnaires were prepared for different six zones as indicated in Figure
1. For each direction, route choice decision and travel time were asked in two steps; before
5the experiment and during the experiment. Then, if the companies do not use expressway they
were asked to choose the reason from listed ones. The questions about the effects of theexperiment followed and finally, the opinions and suggestions were asked in two open-ended
questions.
In Table 1, delivered and collected questionnaires were indicated. Each company was asked
for three routes and some of them did not filled all routes. Routes were indicated inside theparenthesis.
Table 1

Details about the questionnaires delivered to expressway users

Questionnaires delivered to All companies
Freight companies
Production companies
Questionnaires collected from All companies
Freight companies
Production companies

RCE 1

RCE 2

69(204)38(114)31(90)

69(204)38(114)40(76)
25(51)
15(25)

31(90)
46(53)
23(33)
24(20)

2.2.2. Questionnaires delivered to expressway users
During the experiments postcard shaped questionnaires were delivered to the drivers at thecovered ICs when drivers are leaving the expressway. Drivers could join to the survey byfilling and sending back the paid postcards. In the questionnaires trip purpose and vehicle
type were asked to the respondents with other questions. From these answers, we hadclassified the freight and production companies. Details about the collected questionnaires areindicated in Table 2.
Table 2

Details About the Questionnaires Delivered to Expressway Users

Total number of respondents
Expressway users before
Ordinary road users before
Freight companies
Expressway users before
Ordinary road users before
Production companies
Expressway users before
Ordinary road users before

RCE 1

RCE 2

1503
593
910
147
18
129
330
297
33

1137
460
677
61
8
53
342
61
282

As seen from Table 2, most of the respondent were ordinary road users before the experimentand converted to expressway because of discounted toll. Among the considered companies;
freight and production, approximately 83% of them were using ordinary road before the6experiment. In the second experiment, this rate is around 89%.

3. Modelling Approach
In this study, the route choice modeling consists of four steps; segmentation model, RP route
choice model, SP conversion model and finally combined RP/SP model. This modeling effort
was done before the route choice experiments by using data collected from pre-survey. The
flow chart of the modeling approach is indicated in Figure 4. In this paper, the main objectiveis the verification of the proposed combined model structure with the RCEs. Thus, only final
model will be introduced in this paper, all modeling approach was discussed in previous paper(Alver et al., 2006).

Captive

Expressway

Ordinary

SP Convert Model

ChoiceRP Route Choice Model(102)

Segmentation Model

DATA

Combined RP/SP Model

ConvertNot convert

Figure 4 Flowchart for the Modelling Approach
Segmentation model is estimated as the first step of the modeling methodology. This model
was established to divide the respondents into two groups; ordinary road captive and choicegroups. Ordinary road captive group includes the users who do not want to use expressway
even if there is no toll. Choice group covers the users who are using expressway at the
moment and ordinary road users who want to convert under discounted toll. After thesegmentation step, a route choice model was estimated by using choice group. Route choicemodel depend on the RP data only. A conversion model was decided for ordinary road users
after the route choice model as the third step. The aim of the conversion model is to identify
the conversion characteristics of ordinary road users under discounted toll. As discussed an SPsurvey was conducted in the pre-survey to identify the willingness to pay of ordinary road
users to convert to expressway. Finally, both RP and SP data are combined in a route choicemodel.

3.1. Combined RP/SP Model
RP and SP data have their own advantages and disadvantages. The point is some of thedisadvantages of RP data are the advantages of SP data. Some researchers in different fields
recognized this idea and they tried to combine these two data types. In transportation studies,some studies were conducted to combine two data types to estimate more efficient models(Ben Akiva, Morikawa, 1990; Swait and Louviere, 1993; Bradley and Daly, 1997). In
transportation literature, the typical application is to the choice of transportation modes. The
RP data is the current choice and the SP data involves a future choice among current and newtransportation alternatives. The combination of RP and SP data seeks to exploit the contrasting7

strengths of the various approaches while minimizing their weakness. This was described in
the study of Louviere (2000) as “data enrichment” paradigm.
Discrete choice models are the main modeling methodology in combining the RP and SP data.
This study is focused on the estimation of models with discrete choice models. In recent
transportation related studies, combined RP/SP approach is an attraction for the researchers
because of the advantages of using both data types. As an example, Ortuzar and Iacobelli,(1998) used combined estimation method for the mode choice between coach and train,
Cherchi and Ortuzar 2002 study is the impact of new train service, which was investigatedbefore the service improvement. Combining both data can help to the researcher to estimate
better models. However, combining RP and SP data has some difficulties. The main problem
in combining the RP and SP data is the different nature of their errors. The variance of the RP
and SP error terms are different from each other. Still it is not stated that the variance of which
error terms are bigger, it depends on the empirical context.
Ben-Akiva and Morikawa (1990) developed a framework for combining the two types of dataconsidering differences in nature of errors. Two types of data are considered in the approach;first data type provides direct information about the main parameters to be modeled andsecond data type provides additional information about these parameters (indirect
information). Differences in the errors of RP and SP data can be denoted as a function of their
22variance ( σ RP
,σ SP
).
2
2
σ RP
= μ 2σ SP(1)

Many model structures were proposed and tested. The most significant and logical structureused in the estimation is indicated in Figure 5. In the estimated models three roots are
considered; ordinary road (RP), expressway (RP), and expressway (SP). Note that for SP
alternatives, it does not emerge directly from the root or branch, but from a particular nest
with scale parameter μ . Nest parameter ( 1 / λ ) is introduced because of the correlation
between expressway RP and expressway SP, since both utilities use same time variables
Expressway (RP) represents the expressway users who actually use expressway before thediscount. Ordinary road (RP) users are the ordinary road users who do not want to use
expressway after the discount. Expressway (SP) users are the ones who wanted to use
expressway under discounted toll, only this data depends on the SP choices.

1/ λOrdinary Road (RP)

Expressway (RP)μExpressway (SP)Figure 5 Proposed Model Structure
Among the considered models most significant models is the estimated combined RP/SP
8

model. The estimation details and results were discussed in Alver et al. (2006). In this paper
we have tested the estimation accuracy of the proposed model with the conducted RCEs.

4. Transferability of the Proposed Model
4.1. Pooled Data
Conducted RCEs provide valuable data sets to test the pre-estimated model. We haveproposed that if the data of pre-survey is combined with the data, which is collected during
the RCEs from freight and production companies, the data set will be improved. Thus, theapplicability of pre-estimated model was tested with these data sets, which contains the actualroute choice decisions of companies under discounted toll. In the first step, pre-surveys’ datais combined with the data from RCE 1 and 2, separately. In addition, in the final step, all data
sets; pre-surveys’ data and data from both RCEs are combined. The combined RP/SP model
structure was used in the estimation same as the one that we considered in the verification.
The estimation results of the proposed combined RP/SP model and pooled models are shownin Table 3.
In the pooled data, pre-surveys’ data and data from RCEs are combined. Data from RCEs
were enlarged by using their route choice decision before the experiments. For the enlarged
data, discount rate was not considered for the route that was used before the experiment byconsidered companies. Proposed combined RP/SP model and pooled data were estimatedseparately and results are not so different from each other. The transferability of thepre-estimated model was tested to the pooled data, which considers application conditions.
Table 3

Estimation Results: Pre-estimation, Pooled Data
Combined RP/SP

Combined RP/SP+ RCE1

Combined RP/SP+ RCE2

Combined RP/SP+ RCE1 + RCE2

Estimate(t-stat.)

Estimate(t-stat.)

Estimate(t-stat.)

Estimate(t-stat.)1.3091 (2.27)-0.0305 (-3.28)-0.0014 (-2.97)

0.8426 (4.14)-0.0266 (-3.91)-0.0008 (-4.62)

1.3111 (2.72)-0.0289 (-2.04)-0.0013 (-3.11)

0.4718 (2.30)-0.0146 (-2.37)-0.0004 (-2.50)

1.2605 (2.96)
0.0030 (1.93)
0.0925 (0.50)
0.9339 (14.93)

0.8548 (4.33)
0.0023 (3.03)
0.0788 (1.59)
0.9964 (32.27)

1.1668 (3.42)
0.0006 (1.14)
0.0621 (0.76)
0.9538 (15.91)

0.3993 (2.48)
0.0005 (1.06)
0.0442 (1.13)
0.9538 (30.86)

91
0.37
21.52

169
0.33
31.15

129
0.35
22.23

207
0.32
32.90

Variables
Constant
Travel Time
Cost (Expressway toll)
Company dummy(freight.=1, production.=0)
Number of employeeλμNumber of Samples
ρ2
VOT(JPY/min.)9

4.2. Transferability
Transferability is the application of a pre-estimated model to a context different from which it
was estimated in (Koppelman and Wilmot, 1982). Transfer of a model can be defined as theuse of all or part of a model in another context (time, region etc.) than the one in which it wasestimated.
The transfer of proposed model to a new application context can help the researchers toestimate more efficient model with a small data set. In addition, transferability helps to reducethe model development effort, which takes a lot of time. Thus, especially in transportation
literature several empirical studies have been conducted to measure the effectiveness of modeltransfer from one context to another. Some of these studies have examined model transferfrom one spatial context to another (Atherton and Ben-Akiva, 1976; Galbraith and Hensher,
1982; Koppelman et al., 1985).
A variety of tests and measures has been used to compare the predictive ability of choicemodels. Many of these tests operate at the aggregate level comparing observed and predictedmarket shares or in this case observed and predicted route choice decisions. Measures ofmodel transferability were used to asses the effectiveness of models when they are transferred
for use in an application context that is different from their calibration context. The indicesand t-statistics are all based on log likelihood measure. In this study, two tests are considered;likelihood ratio test and asymptotic t-test.
4.2.1. Likelihood ratio test

Results of this test show the statistical similarity of the estimation and application model
coefficients. In this test, the null hypothesis is that the coefficients of the estimated model do
not deviate significantly from the coefficients estimated from the entire set of application data.
We have combined the pre-estimated data with the actual route choice surveys and examined
whether the proposed model parameters have remained stable over time and most importantly
under the real conditions of discounted toll. Likelihood ratio test ( X 12 ) uses the log likelihood
values to test the transferability of the models as follows:

X 12 = −2[L A+ B (θ A+ B ) − L A (θ A ) − LB (θ B )](2)

Where,
L A+ B (θ A+ B ) : Log likelihood values of the pooled models with the model parameters
estimated from pooled conditions.
L A (θ A ) : Log likelihood value of the pre-estimated model with the model parameters
estimated from pre-survey conditions.
LB (θ B ) : Log likelihood values of the RCEs with the model parameters estimated from RCE
conditions.

The above equation is Chi-squared distributed with degrees of freedom equal to number ofrestrictions (coefficients in this model). If the calculated value from above formulation issmaller than the critical Chi-squared, the null hypothesis is accepted. As discussed, we have10

created three pooled data, which combines the RCEs and pre-survey. Results of likelihood
ratio test for these models are indicated in Table 4.
Table 4Chi-Squared Values for Pooled Data Sets
Variables

Combined RP/SP+ RCE1

Combined RP/SP+ RCE2

Combined RP/SP+ RCE1 + RCE2

10.66

9.28

11.02

X 12
Note: Critical χ 2 (5,0.05) = 11.07

If we compare the transferability of the pre-survey to pooled conditions, the best results are
estimated with the second pooled data. The other models are also transferable. If weremember the verification of the RCE 1 and 2 with the pre-estimated model, proposed model
estimated the route choice decisions 78% correctly for the freight and production companies
in RCE 2. This result was 72% for the RCE 1. Here, first pooled data is transferable but, X 12
for the first model is little higher than the second pooled data. The area covered in the second
RCE is longer. Thus, covered discounted section is more suitable for the travels inside theprefecture. Remember in the pre-survey, business trips inside the prefecture were investigated.
4.2.2. Asymptotic t-test

Another test is available to compare the estimated variables one by one. An asymptotic t-test
for this purpose is as follows:t=(θ A + θ A+ B )σ A2 + σ A2 + B(3)Where,

θA: Estimate of a parameter in pre-survey conditions
θ A+ B : Estimate of a parameter in pooled conditions

σ A2: Variance of parameter estimate in pre-survey conditions
2
σ A+ B : Variance of parameter in pooled conditions
This asymptotic t-test allows us to find out which variable differs between the transferredmodels. If the likelihood ratio test fails, asymptotic t-test can help to define the variable,
which is not transferable between the pre-survey and pooled conditions. Results of this test
are indicated in Table 5 for three different pooled data sets. In the asymptotic t-test, sevenvariables are considered as estimated in the model. Critical value is t(7,0.05)=1.895 and all
variables in tests for three models are in the limits and transferable. Same as the likelihood
ratio test, pooled data with RCE 2 gives better results rather than first one.
The results support that our model is transferable if we create a pooled data, which includes
actual conditions under discounted toll and pre-surveys’ data. Proposed model is transferable
11

to the actual discounted conditions. Another important finding is second RCE is more
effective, transferability tests are better. The reason RCE 2 has better estimate results than firstone is the distance. First social experiment covers five interchanges and these interchanges are
not enough to cover all trips inside the prefecture. Thus, in the second experiment, one moreinterchange was added and almost all trips are covered inside the prefecture.
Table 5Results of Asymptotic t-test
Variables

Constant
Travel Time
Cost (Expressway toll)
Company dummy(freight.=1, production.=0)
Number of employeeλμCombined RP/SP Combined RP/SP+ RCE1+ RCE2
0.87
0.35
0.53
0.44
0.86
0.07
0.30

0.01
0.31
0.10
0.16
0.17
1.09
0.21

Combined RP/SP+ RCE1 + RCE2
1.57
1.47
0.88
1.25
1.89
0.25
0.28

5. Verification of Proposed Model
From the estimation results when we compared all the models, we found out that combined
RP/SP model have better estimates to clarify the route choice decision of the freight andproduction companies. Generally, the procedure works in this way and future demand andtraffic volume will be estimated by using the estimated most significant model. However, in
our study, we had a great chance that we could verify our estimation results with the data thatwas collected during two route choice experiments. These experiments represent the actual
behaviors of drivers. Estimated results were compared with the data collected from route
choice experiments.
Verification of the proposed model structure was done by using data collected from freightand production companies during RCEs. These questionnaires are similar to the ones used in
the pre-survey. Most importantly in these data, same kinds of companies and vehicle types are
considered as the pre-survey. Questionnaires include the information about the travel times,
cost as expressway toll, route; before and during the experiment, company type and numberof employee.
In the verification, we have used the pre-estimated combined RP/SP model’s coefficients andwe have calculated the route choice probabilities of all routes for each company. If the actualroute choice decision of the company is same as the estimated bigger route choice probability
for that company by using the actual data and pre-estimated models coefficients, it is accepted
as true and otherwise false. As an example, if the actual route choice is expressway andestimated expressway probability is bigger than ordinary road it is true, otherwise false. The
hit ratios for proposed model are indicated in Table 6 for both RCE.
The verification results show that proposed model (combined RP/SP) estimated the actualroute choice decision of the companies more than 72% correctly. In average, our result could
12estimate the route choice decision on each three companies out of four. Proposed model could
estimate the route choice decisions better for the second experiment, because covered
interchanges are more and it fits better with the aim of the pre-survey.
Table 6Hit Ratios for Freight and Production Companies

Combined RP/SP Model
Average expressway probability
Average ordinary road probability

RCE 1 (%)

RCE 2 (%)

72
62.1
37.9

78
71.7
28.4

As we discussed second experiment covers longer area and fits better with the pre-survey. In
average, proposed model could estimate the route choice decision 75% correctly.

6. Conclusion
The aim of the study was to convert some of the truck traffic from the city center toexpressway, which passes through Kumamoto City. Expressway toll policy was considered toincrease the traffic volume on the expressway. For this aim one pre-survey and two route
choice experiments were conducted. After the pre-survey, a route choice model was estimatedwith information of discounted expressway toll. Estimation was done in four steps, and finallycombined RP/SP model was estimated. Combined RP/SP model was the most significant
model from the viewpoint of t-statistics and ρ2 values.
Route choice experiments are conducted to collect information about decisions of theindividuals and to identify the effects of discounted toll on traffic and its surroundings. These
kinds of surveys are valuable to evaluate the actual conditions and to test the estimation
accuracy of the pre-estimated models. To verify our model, we have to wait the policy
implementation. However, it would be late if our model could not estimate the demand after
the implementation and we have assumed the discount in expressway toll will attract manyusers.
Before the policy implementation on the expressway toll discount, two experiments wereconducted to identify the route choice decisions of users under real conditions. During theseexperiments 50% discounted toll was applied. In the first experiment, five interchanges werecovered and in the second experiment one more interchange was added to the previous range
and six interchanges were covered. These experiments allow us to verify our model and tocompare the estimated results with the actual data, which presents the situation after thepolicy implementation.
Data collected before the RCEs and data collected during the experiment were pooled tocreate an effective data set. Transferability of the proposed combined RP/SP model, with thepre-estimated data was used to test the performance of pooled data. Three pooled data arecreated; first one, combines the pre-estimated data with first experiments data. In the second
one, pre-estimated data was combined with second experiment’s data and finally13pre-estimated data with both experiments’ data were combined.
Transferability tests indicated that model is transferable with the pre-surveys data to thecreated three pooled data sets. Second model has better transferability results parallel with theverification results depending on the covered distance. Almost all expressway trips could becovered by second experiment. If the transferability of all variables were done separately, allvariables would be transferable to pooled conditions.
Finally, the estimated demands during the experiments by using pre-estimated model arecompared with the actual route choice decisions of freight and production companies.
Proposed model could estimate the actual route choice decision of the companies 72%
correctly in the first experiment and 78% in the second experiment. In the second survey, one
more IC was added to the previous one and almost all trips inside the prefecture were covered.
Pre-survey investigated the trips inside the prefecture. Thus, the estimation results for thesecond experiment should be higher. In average, linear model could estimate the actual
behavior 75%. Verification results of the linear model is better and this result supports thatcombined RP/SP model was chosen as the proposed model to estimate the route choicedecisions of considered companies.

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