Nowcast Simulation Predicting Network
Traffic Conditions by Assimilating Floating
Car Data
Ryota Horiguchi1, Hisatomo Hanabusa1, Masato Kobayashi1, Katsuaki Koide1,Takashi Oguchi2,
1 i‐Transport Lab. Co., Ltd.
2 Institute of Industrial Science, the University of Tokyo

1 Introduction
In recent years, real time traffic data collected by floating car data (FCD) can be used formany traffic information services. There are many advantages of real time traffic data.
For example, the accuracy of the travel time information for car navigation systems isimproved by using FCD. However, it must be noted that FCD is observed temporally andspatially as only a part of the traffic situation. In this case, one of the solutions is toestimate the traffic conditions between FCDs using some traffic models or algorithms.
An online traffic simulation system should be provided as an example of a framework toestimate all traffic conditions in an area. ‘Online traffic simulation systems’ is one of theimportant research topics in the traffic engineering field. Some systems are developed
and applied to real road networks for new traffic information services. It is said that thereproducibility and the accuracy of the estimated traffic situation are one of thechallenges for practical use. However, online traffic simulation can be a breakthrough forthe upgrading of traffic information services and road administration. In past studies,
Ishibashi et al. [Ish09] described the method of an online traffic simulation system andthe validation results, such as travel times on the Hanshin Expressway in Japan.
Munakata et al. [Mun09] described validation results on the Metropolitan Expressway
using the online traffic simulation system developed by Shiraishi et al [Shi05].
DYNASMART‐X[Dsx04], DynaMIT [Dym98] and Aimsun Online [Aim08] were also
developed and applied as online traffic simulation systems to predict traffic situations
using real time traffic data. These studies and examples are developed for application toroad networks in which traffic volumes and speeds are obtained by traffic sensors.
However, it is possible that there may be few sensors, or even no sensors, in regular road
networks compared to arterial roads and highways. In addition, the locations of origin
and destination of vehicles are difficult to determine. We can be fairly certain that thesolution in the case of insufficient sensors has not been studied enough. Althoughapplications of FCD, such as travel time prediction, have been the object of study inrecent years, no studies have ever tried application according to the characteristics ofFCD (e.g. traffic volume cannot be estimated from FCD). Therefore, we developed aframework of an online traffic simulation system which can estimate the traffic
conditions of an entire road network using FCD in the case of insufficient traffic volumedata.

2 Concept
The purpose of this study is to develop the Nowcast Traffic Simulation System (simplynoted as ‘Nowcast’) to estimate the road traffic conditions in urban areas in real time.
Figure 1 shows the image of the Nowcast.

Figure 1: Concept of the Nowcast.
“Nowcasting” is the meaning to predict some sort of present situation such as weather.
Thus the Nowcast forecasts the present traffic situation using real time traffic data. The
Nowcast can be applied to several kinds of traffic monitoring systems for city‐wide roadnetworks. The purpose of the monitoring is to measure not only traffic flow and travel
time but also environmental impacts such as CO2 emission and traffic noise. TheNowcast complements the entire present traffic situation by a traffic simulation modelusing FCD. In this case, the Nowcast calibrates the parameters of traffic simulation to fit
the traffic situation given by the traffic simulation model to the traffic situation from theobserved data in real time. In this study, the traffic simulation model SOUND is used andthe parameters for the calibration are below.
• OD traffic volume• Bottleneck capacity (saturation flow rate)2

Figure 2 shows the image of the parameter calibration of the Nowcast. The Nowcast
calibrates these two types of parameters estimating the variation in the average traffic
situation (the base case).

Figure 2: Image of Parameter calibration of NTSS.
In the full paper, the methodology of floating car data assimilation in the Nowcast will be
detailed followed by the validation study using field operation test data.
Corresponding author: Ryota Horiguchi, i‐Transport Lab. Co., Ltd., Shin‐Surugadai DLDG
9F, 3‐10, Kanda‐Ogawamachi, Chiyoda‐ku, Tokyo, 101‐0052, Japan, phone: +81 3‐5283‐
8527, e‐mail: rhoriguchi@i‐transportlab.jp

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