The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004

DATA FUSION OF VICS AND PROBE TO
REDUCE UNCERTAINTY OF TRAVELTIME INFORMATION
Ryota Horiguchi
i-Transport Lab. Co., Ltd.,
Address: 2-12-404 Ageba-cho, Shinjuku-ku, Tokyo 162-0824, JAPAN
Phone/Fax: +81-3-5261-3077, E-mail: poepoe@nishi.iis.u-tokyo.ac.jp
Hirokazu Akahane
Professor, Chiba Institute of Technology,
Address: 2-17-1 Tsudanuma, Narashino, Chiba
Phone: +81-47-478-0444, Fax: +81-47-478-0474, E-mail: akahane@ce.it-chiba.ac.jp
Katsuaki Koide
Bs., Chiba Institute of Technology,
Address: 2-17-1 Tsudanuma, Narashino, Chiba
Phone: +81-47-478-0444, Fax: +81-47-478-0474

ABSTRACTThis research aims to present the effect of data fusion of probe and VICS travel time information.
VICS, which is so-called Advanced Travel Information System in Japan, collects link travel time
based on loop or ultra-sonic detector speed, and updates travel time information every 5 minutes via
on-board navigation system. However, it provides travel time information only for highways andmajor arterial roads on which detectors are installed, and assumes constant travel times for othermiscellaneous links. When the major roads are jammed by heavy traffic, it can be happen that VICS
navigation system will mislead a driver to the route consisting of minor roads of which the traffic
conditions are uncertain and can be severe as well as the major roads. On the other hand, probe or
floating car data collection system attracts considerable attention to survey the travel times of links
widely over a city. At this moment, even though the frequency of data updating for link travel times
with probe system would not be so high, we can utilize the probe data to spatially complement VICS
data, in order to reduce the uncertainty of travel time information. In this paper, the methodology ofdata fusion proposed here will be explained at first. In the second part, the practice using real VICS
and probe data collected in Nagoya-city will be presented to demonstrate the effect of data fusion.

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The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004

INTRODUCTION
This research aims to present the effect of data fusion of probe and VICS travel time information.
VICS, which came into operation from 1996, is so-called Advanced Travel Information System inJapan. VICS collects link travel time based on loop or ultra-sonic detector speed, and updates travel
time information every 5 minutes via on-board navigation system.
However, a couple of shortcomings are pointed out to VICS. At first, it covers only highways andmajor arterial roads (VICS links) on which detectors are installed. As shown in Figure 1, VICS links
sparsely cover the network, comparing with full links in Nagoya-city area. If someone starts his/hertrip to destination, he/she will use not only major roads but also minor roads for access and egress,
which sometimes may be in severe traffic conditions. A demand for the informative service
including those minor roads seems to be large.

Figure 1. Full links (left) and the VICS links (right) in Nagoya-city area.
At second, it has to estimate link section travel time from detector speed at one point. Some models,such as simple queuing model, will be required for the estimation, but it is difficult and costly tocalibrate those models well in long term. Moreover, detector speed can not distinguish vehicles'
turning movements. Therefore, VICS only provides link travel time by assuming straight throughdirection.
Considering these shortcomings, we may regard even a driver using VICS is facing uncertainty oftravel time information. It can be happen that VICS misleads a driver to worse situation than thedriver without VICS information when the minor roads out of VICS links are severely congested,because most of on-board navigation system assume constant and moderate travel speed for thoseminor roads.
In order to provide much reliable travel time information, it is expect to merge prove information into
VICS. Against to VICS, probe data can be collected on every roads that vehicles may run. It
directly measures section travel time along the path of a probe vehicle by including the delay atleft/right turn. Still we can not expect high frequency of updating travel time with probe at present,
we may utilize stored probe data and extract statistical information among them.
In the following chapter, we will report the practical study for the data fusion of VICS and probe travel
times. The concept and the methodology of data fusion will be explained at first. In the second part,2

The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004

the practice using real VICS and probe data collected in Nagoya-city will be presented to demonstrate
the effect of data fusion.

CONCEPT OF DATA FUSION OF VICS AND PROBE DATA
The methodologies of data fusion proposed here take two ways, correction of VICS link travel times
and spatial complement to VICS links with stored probe data. The concepts of these twomethodologies are described in the subsequent sections.

Correction of VICS Link Travel Times with Probe Data
The popular way to estimate the travel time of a VICS link is so-called 'sandglass' method, whichcounts the number of vehicles at the upstream of the link as the traffic demand. By assuming theparameter of a reasonable flow rate at the downstream section of the link, the method calculates theaverage travel time with simple queuing theory.
It is obvious that the accuracy of the traffic counts and the flow rate will strongly affect on thereliability of the estimated travel times. In practice, however, it is the case that the assumed flow rateis different from the actual value or that the measured traffic counts include errors by some reasons
from maintenance works. Since it will be very costly to seek the perfection to maintain the sensors
and the parameter values, we may permit some errors in VICS travel time information whatever themagnitude of errors are not acceptable.
In order to correct the errors in VICS link travel time, VICS data is to be compared with stored probe
data that is reasonably cleansed to measure link travel times (Sarvi, et. al, 2002), as shown in Figure 2.
Each plot in the figure represents VICS link travel time at the same time when a probe vehicle passes
through the subject VICS link.
Median line for rightturn travel times

300

Median line for straighttravel times

VICS link travel times [sec.]

250

200

150

100

50

Correction
for straightstraight
right turn

Correction
for right turn

00

50

100

150

200

250

300

Individual probe link travel times [sec.]

Figure 2. Correction of VICS link travel times with stored individual probe data.
Even though the variation of 'individual' probe travel times is larger than VICS travel times, we may3

The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004

derive some relationships from the comparison to be used for the correction of VICS data. In Figure
2, we derived two liner regression lines to the 'median' plots which provide median values of prove
travel times for every 30 second range of VICS travel times. Since the turning movement at thedownstream intersection is given to each probe travel time, we may obtain the correction line not only
for straight but also right or left turn. When a certain value of link travel time is provided by VICS,
different travel times will be provided according to the turning movement at the intersection by using
this method.

Spatial Complement to VICS Links with Probe DataAs shown in the right picture of Figure 1, most of the minor roads are not designated as VICS links.
However, considerable number of VICS links are not given travel time information because of thereason that they have no traffic detector on themselves and so on. Table 1 shows the total length oflinks in terms of information provision types in Nagoya-city. It is found that only 4% out of wholelinks are provided travel time information, and we have to estimate the travel times for the rest of 76%
links by not using VICS.
Table 1. Total length of links for each information provision type (Nagoya-city).
Description

TypeTotal length%

1VICS link with travel time information

400 km4%

2

VICS link without travel time information

2,150 km22%

3

Non-VICS link

7,000 km74%

Average of probe travel times for every 15 minutes. [sec.]

In this research, timetables of expected travel times are derived from the historical probe data for thelinks without VICS information. Figure 3 illustrates an example that contains the expected link
travel times of certain non-VICS link for every 15 minutes. Even though the derived timetable isstatic and cannot consider the daily traffic condition, it still reveals that the profile of the travel time
has two peaks in the morning and the evening. This timetable helps to make the travel time
information be reliable, rather than by assuming constant speed.

3530252015105004812Time of day [hr]162024

Figure 3. Timetable of expected travel times for a non-VICS link.

4The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004PRACTICE OF DATA FUSION USING REAL VICS AND PROBE DATA
In order to demonstrate the effect of data fusion, two sample path as shown in Figure 4, which startfrom Nagoya-city and goal to Ichinomiya-IC, is selected. The distance from start to goal isapproximately 13 km. VICS link travel time is provided to the section of 2.4 km along Path-1, while
no VICS link travel time is provided to Path-2.
Ichinomiya ICPath-1
Path-2

2.5km
Nagoya Sta.

Figure 4. Sample path to demonstrate the effect of data fusion.
Figure 5 compares the travel times of the two paths for every 15 minutes on a certain day. The left
picture shows the travel times using only VICS information. As we assume constant travel times fornon-VICS links and VICS links without information, the travel times of Path-2 are always the same.
Although the change in the travel time of Path-1 is moderate, the graph says Path-1 always faster thanPath-2.

2500
Travel Time of the path [sec.]

Travel Time of the path [sec.]

2500
2000
1500
1000
50002000
1500
1000
500
004812Time of Day

16202404812Time of Day

162024Figure 5. Comparison of path travel times (left: only VICS data, right: data fusion)
On the other hand, the right picture shows the travel times calculated by the data fusion method
proposed in this paper. The changes in the travel times now become more conspicuous than the leftpicture. The difference of travel times between Path-1 and Path-2 gets larger during the off-peak, andare almost equal to each other at the peak period. The result of data fusion seems to be more realistic
than the result with only VICS data.
5The 2nd International Symposium on Transportation Network Reliability, Christchurch, 2004

CONCLUSION
In this paper, we described the concepts and the processes of data fusion with VICS and probe link
travel time data. Imagine a driver who provided the path travel times based on the left graph inFigure 5 at peak period, he/she will tend to choose Path-1 that looks faster than Path-2. However,provided the data fusion travel times in the peak period, he/she may aware both Path-1 and Path-2 arecongested as much as each other, and the result of path choice behavior will never be the same as theprevious case. Indeed, let us conclude that the data fusion can reduce the uncertainty of travel times
and increase the reliability of the network.

REFERENCES
Sarvi, M. et. al (2002). A Methodology for Data Cleansing and Trip End Identification of Probe
Vehicles, In the proceedings of the JSCE Conference of Infrastructure Planning, Vol.26.
Chung, E. et al (2003). Cleansing of Probe Car Data to Determine Trip OD, Presented at 21st ARRB
Conference in Cairns, Austraria.

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