23rd ITS World Congress, Melbourne, Australia, 10–14 October 2016

Paper number AP-TP0440

An Application of the Mesh-wised Traffic Information Systemusing Floating Car Data for Nationwide Road NetworkHisatomo Hanabusar1*, Morihisa Iijima2, Tadashi Komiya2, Ryota Horiguchi2
1. i-Transportlab. Co., Ltd., Japan, Shin-Surugadai BLDG 9F, 3-10, Kanda-Ogawamachi, Chiyoda-ku,Tokyo, 101-0052, Japan, Tel:+81-3-5283-8527, E-mail:hanabusa@i-transportlab.jp
2. i-Transportlab. Co., Ltd., JapanAbstract
This study describes an application of the real time mesh-wised traffic information “TrafficScope” for nationwide road network. Traffic Scope calculates mainly two indicators of thefluidity and the singularity of road traffic based on Macroscopic Fundamental Diagram using
floating car data. The on-line demonstration of Traffic Scope for the area of 23 wards ofTokyo has been operated for several years. For the next step, we are developing the newsystem to provide Traffic Scope of nationwide road network in Japan. However, sometechnical issues to be tackled for large scale area are found from the analysis of floating cardata. In this paper, we introduce the concept of Traffic Scope and describe the issues to apply
nationwide floating car data to Traffic Scope, showing some examples of anomaly detecting
in road traffic such as the analysis result on the day of heavy snow and the day of several
events.
Keywords: Traffic Information, Floating Car Data, Macroscopic Fundamental Diagram
Introduction
The purpose of this paper is to introduce the application examples of the real time mesh-wised
traffic information “Traffic Scope” for a large area and describe the issues to be tackled forthe development of the nationwide service of Traffic Scope. We first explain the model
concept of Traffic Scope, and show the system structure and the data process of Traffic Scopesystem. After the explanation, we show the example of Traffic Scope for wide area andconsider the applicability and the issues before the discussion for further steps in theconclusion.
In recent years, the huge amount of floating car data is collected as one of the type of big databy car navigation, smartphone and other devices to collect vehicle information. On the otherhand, the services and the technologies using floating car data have been rapidly because theseveral potentials of floating car data are recognized. In addition, it is said that the target areas

An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road Networkfor the services about road traffic information can be expanded with the increasing of floating
car data. In our study, we have come to the conclusion that “Traffic Scope” has a potential toexpand to nationwide using floating car data in Japan. The two major purposes of Traffic
Scope are to provide the current traffic situation at first glance and to encourage the users toconsider their behaviours in transportation. Traffic Scope is one of the new traffic information
services to assist the movement of people to avoid congestion and some troubles in daily
traffic.
Model Concept
Traffic Scope is the mesh-wised traffic information with two indicators of the fluidity and thesingularity of road traffic which are calculated in real time. This methodology which isdeveloped by Horiguchi et al.[1][2][3][4] is used the idea of Macroscopic Fundamental
Diagram (MFD). MFD is formulated by Daganzo[5]. In recent years, many researches using
MFD to understand the traffic situations or to use for traffic management can be found by
several approaches such as Geroliminis[6]. Basically, MFD is a statistical approach forarea-wide traffic which is calculated using floating cat data or detector data. Traffic Scope
employs the idea of integration of real time data and statistical analysis to understand thedifference between usual traffic situation and unusual traffic situation. On the other hand, it isalso important that the visualisation of traffic situation should be designed to provide as theeasy-to-understand traffic information. Traffic Scope is designed to understand the fluidity
and the singularity of road traffic at first glance for broadcasting system such as TV.
Figure1 shows the concept of Traffic Scope. The input data is basically floating car data withtime and GPS position. The point on MFD can be calculated by the product of average flow
and network length (Q) and the product of density and network length (K). Thus Traffic Scope
can also calculate by aggregated data such as traffic volume and average travel time for eachlink. The procedure of the indicators of Traffic Scope is below.
i.

ii.
iii.
iv.

Analyse the statistical QK pattern on MFD using the floating car data in the last 1month (maximum 3 months). Now the time resolution of aggregating QK point is 15minutes.
Estimate the approximate curve from the QK pattern on MFD. The curve is the basic
line that expresses the normal traffic situation.
Calculate the present point of QK on MFD from real time floating car data andanalyse the difference between the present situation and the approximate curve.
Make the indicators (the fluidity and the singularity) of Traffic Scope from theanalysis result (the present QK point and the difference from the normal situation).

2

An Application of the Mesh-wised Traffic Information System using Floating Car Data forNationwide Road Network

Figure1 – Concept of Traffic Scope
System structure of Traffic Scope
Figure 2 shows the system image of Traffic Scope System. Traffic Scope Server is receives
the aggregated floating car data with link travel time and sample number. And Traffic Scope
Server analyse floating car data and calculate the Traffic Scope data (the fluidity index and thesingularity index). Traffic Information Server receives the Traffic Scope data and makes theimage data to deliver some services. When the aggregated data with link information is used,the network data (link id, link length, etc.) should be shared between Floating car data serverand Traffic Scope Server.

Figure2 – System image of Traffic Scope system
3

An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road Network

Figure 3 shows the data process in Traffic Scope Server. Traffic Scope Server consists of 4processes. The data collection process is the front-end process to collect floating car data andto divide the collected data into target mesh-areas every 15min. or 5min. QK data making
process calculates the QK plot on MFD and dispose floating car data for the data security
policy. The statistical process is the important process to estimate the normal traffic situation(the basic QK pattern) from QK pattern for each mesh area and decide the parameter of thebasic QK pattern curve. The Traffic Scope information making process calculate the fluidity
index and the singularity index based on the current QK plot and the basic QK pattern onMFD for each mesh area. The calculated results are accumulated the Traffic Scope Databasefor the several service.

Figure3 – Data process in Traffic Scope ServerTokyo Traffic Scope
Traffic Scope system is operating for the area of Tokyo 23 wards called “Tokyo TrafficScope”. Figure 2 shows the online demonstration website of Tokyo Traffic Scope [7]. Thissystem uses the floating car data from SPATIOWL[8] data base in Japan. The target area isonly Tokyo 23 wards area but the collection rate of floating car data is reliable and stable. We
have been operated Tokyo Traffic Scope as a real time demonstration for several years and thetransition of gridlock of road traffic was detected in the day of the Great East Japan
4An Application of the Mesh-wised Traffic Information System using Floating Car Data forNationwide Road NetworkEarthquake. Tokyo Traffic Scope is updated each 15 minutes. The process time isapproximately 3minuts from the collection process to the delivery of the image data of Tokyo
Traffic Scope.

Figure4 – Online demo of Tokyo Traffic Scope
Applications for large area
For the application to nationwide area, we made the prototype of Traffic Scope system
updated some functions to process nationwide floating car data in real time. The prototype
was implemented the new data processes by parallel computing techniques based on theframework in Figure 2 and Figure 3. By using the new prototype, all meshed areas in Japan
can be calculated by the new Traffic Scope System.
Figure 4 and Figure 5 show the analysis results of the singularity index and the speed
difference in the day of heavy snow. The floating car data we use basically covers all areas inJapan, and is aggregated into the format consisting of traffic volume (number of samples) andaverage travel time for each link. The red mesh area in Figure 4 shows the unusual situation
highlighted by the singularity index. And the red mesh areas in Figure 5 are the highlighted
areas which the speed is rapidly declined. We can be fairly certain that Traffic Scope candetect unusual traffic situations and indicate the areas for large area.
5

An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road Network

Figure4 – Singularity of Traffic Scope on the heavy snow day

Figure5 –Speed difference of Traffic Scope on the heavy snow day
Figure 6 shows the enlarged area of the result in Figure5. The unusual traffic situation on thisday was detected especially on mountain corridors. It is likely that the stopped vehicles or thetroubled vehicles by the snow-filled road existed in this area. In addition, some mesh shows
the cross mark areas which had no data or very few data. These areas express that the roads inthe area might be closed by some reasons such as heavy snow. Thus the cross mark area
should be focused and the system may alert as the area to take precautions for the rescue or
the road regulation. On the other hand, the singularity index and the difference speed in Tokyo6

An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road Network

area have relatively less impacts. One of the reasons is said that the many people in Tokyo andthe around areas are no need to use vehicles and they have many choices of transportations totheir destination such as train and bus. The other reason is also said that the snow depth inTokyo is low related to the mountain areas.

Figure6 – Traffic Scope near Tokyo area on the heavy snow day (February 14, 2014)
We also estimated a Traffic Scope example on another day which some events were held. See
Figure 7 for the Traffic Scope on the day of firework festivals in three areas. These festivals
began after 6:00 p.m. and finished at 8:30 p.m. Generally, fireworks viewers might go home
all together and the around area could be congested by the people by walk and vehicles.
Traffic Scope shows the unusual congested area in three areas at the finish time of thefestivals. Therefore, this example turned out that the singularity index and fluidity index of
Traffic Scope can detect unusual situation area not only weather but also special event forlarge area.
On the other hand, some issues to apply to nationwide area are described through thecalculation examples. One is the process when a mesh area does not have enough floating car
data for the calculation of Traffic Scope. Basically the floating car data is collected in the past
1 hour to calculate Traffic Scope for a time slot (15 minutes). The current system of Traffic
Scope and the prototype cannot adjust the calculation in response to the amount of floating
7

An Application of the Mesh-wised Traffic Information System using Floating Car Data forNationwide Road Network

car data. Thus the result of Traffic Scope could be misunderstood with small amount of datain 1 hour, especially in suburbs. It is said that the function of parameter adjustment of should
be developed. And the other one is the believability of Traffic Scope. Traffic Scope can detect
the unusual situation but there is no supplement to know the reason of the situation. Open data
related to public transport and social networking service is one of the solutions to estimate thebelievability. It is the important issue to overlay with several types of data on Traffic Scopeand develop the framework to know the traffic situation from various perspectives.

Figure7 – Traffic Scope on the day of firework festivals
Conclusions and Future works
In this paper, we describe the system structure and the data process of Traffic Scope, and theapplication result for large area. The following results from our activities were obtained:

The Traffic Scope system was extended to process the nationwide data of floating car.
Traffic Scope can detect the unusual situation for large area in the heavy snow day andin the day with several events.
However, it is said that the calculation of QK analysis in an area with small amount ofdata is needed to adjust the statistical process for real time.
8An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road NetworkOn the other hand, there is room for further consideration of the believability of thedetected unusual situation by Traffic Scope comparing to other traffic information
sources.

Judging from the above, much can be said on the following tasks for the application to thenationwide service of Traffic Scope.
Develop an approach of Traffic Scope to solve the issue of the QK analysis with small
amount of data.
Combine Traffic Scope with several types of data such as weather information.
Find and visualize the reason of the detected area in unusual situation, analysing the datafrom social networking services.
Develop the risk index of unusual traffic congestion to avoid an additional disruption oftraffic in advance.

Acknowledgement
This paper owes much to the thoughtful and helpful comments of Professor Shibasaki, Dr.
Sekimoto, Dr. Seto, Dr. Kanasugi from the Center for Spatial Information Science & Instituteof Industrial Science, the University of Tokyo. And special thanks are due to Honda MotorCo., Ltd. for providing us their floating car data.
References
1. R.Horiguchi, M. Iijima and H. Hanabusa:Traffic Information Provision Suitablefor TV Broadcasting Based on Macroscopic Fundamental Diagram from
Floating Car Data, Proceedings of 13th International IEEE Conference onIntelligent Transportation Systems, Madeira Isrand, Portugal, 19-22
September 2010.
2. R. Horiguchi, M. Iijima, M. Kobayashi and H. Hanabusa: Incident detection forthe surface street network with the mesh ‐ wised traffic indices on themacroscopic fundamental diagramLATSIS 2012 - 1st European Symposium on
Quantitative Methods in Transportation Systems, Lausanne, 4-7 September,
2012.
3. R. Horiguchi, M. Iijima, M. Kobayashi and H. Hanabusa:Traffic anomaly
detection for surface street networks with the mesh-wised traffic indices onmacroscopic fundamental diagram, OPTIMUM2013 - International Symposium
on Recent Advances in Transport Modelling, Kingscliff, NSW, Australia, 21-23April, 2013.

9

An Application of the Mesh-wised Traffic Information System using Floating Car Data for
Nationwide Road Network

4. An analytical approximation for the macroscopic fundamental diagram ofurban traffic, Transportation Research Part B: Methodological, Volume 42,Issue 9, November 2008, Pages 771–781
5. Daganzo, C. (2007). Urban gridlock: macroscopic modeling and mitigation approaches.
Transportation Research B 41 (pp. 49-62).
6. Geroliminis, N., & Daganzo, C. (2007). Existence of urban-scale macroscopic
fundamental diagrams:some experimental findings. Working paper, Volvo Center of
Excellence on Future Urban Transport, Univ. of California, Berkeley.
7. http://www.i-transportlab.jp/en/
8. FUJITSU Intelligent Society Solution SPATIOWL, http://www.fujitsu.com/jp/solutions/business-technology/intelligent-data-services/convergence/spatiowl/function/tra
fficinfo/mesh-demo/index.html

10