VALIDATION SCHEME FOR TRAFFIC SIMULATION TO
ESTIMATE ENVIRONMENTAL IMPACTS IN'ENERGY-ITS PROJECT'Ryota HORIGUCHI, Hisatomo HANABUSA
i-Transport Lab. Co., Ltd., Phone: +81-3-5283-8527, Fax: +81-3-5283-8528,
E-mail: {rhoriguchi|hanabusa}@i-transportlab.jp
Masao KUWAHARA, Shinji Tanaka
Institute of Industrial Science, University of Tokyo,
E-mail: {kuwahara|stanaka}@iis.u-tokyo.ac.jp
Takashi OGUCHI, Hiroyuki ONEYAMATokyo Metropolitan University,
E-mail: {oguchi|oneyama}@tmu.ac.jp
Hiroshi HIRAI, Seiji HAYASHIJapan Automobile Research Institute,
E-mail: {hhirai|shayashi}@jari.or.jp

ABSTRACTThis paper introduces the validation scheme for traffic simulation to estimate the CO2 emission fromautomobiles. In the paper, rational association of traffic simulation and CO2 emission model is discussed atfirst. Following to the discussion on the reference models of CO2 reduction measurement, the verificationand the validation procedures focusing on individual vehicle trajectories will be summarized. Those
activities are part of the project ‘Development of Energy-saving ITS Technology’ which is organized byNEDO (New Energy and technology Development Organization) in Japan.

INTRODUCTION
From FY2008, 'Development of Energy-saving ITS Technology’ Project organized by NEDO Japan waslaunched. One of the major research topics for which the authors are responsible in Energy ITS Project is toestablish the rational procedure to estimate the CO2 emission from automobiles.
Figure 1 shows the six research directories consisting of our activities to establish the estimation method
for CO2 emission. Developing traffic simulation and CO2 emission models are the most significant
technical issues.

1Hybrid traffic simulation
To improve reliability of traffic
flow estimation, developingtechnology that combines macroand microscopic traffic phenomena.

CO2 emission model

Monitoring with probe cars

Development of technique for
estimating CO2 emission fromvehicle in high accuracy

Development of technology thatestimates real-time CO2 emission
by using probe information.

Fuel consumption test
Microscopic traffic flow simulation

CO2 map

Velocity(km/h)

600
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20000200400-200Time(s)NOx emission(g/s)

Enginespeed(rpm)running resistance, acceleration resistance,
T/M efficiency, gear shift logic, etc.

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CO2 emission

2.00E-01
1.50E-01
1.00E-01
5.00E-02
0.00E+00

100200400 Time(s) 600

8001000

International Traffic Database

International cooperation

Development of technology thatenables to use and to search ofscattered data
Probe
data
weather
Populationdata
Traffic
data
Traffic
Land
statisticuse
ETC

Information exchange such as holding a
regular meeting with experts fromvarious nations to form mutual agreementof the criterion of evaluation method

Model verification & validation
Development of technology thatverifies the accuracy of the estimate
result of the simulation by an actual
on-the-street survey etc.

U.S.

E.U.

effect of root choiceRoad 1NEARCTIS
New EU project

Asia
PacificNEDOproject

Road 2Figure 1: Research directories to establish the estimation method in Energy-ITS projectIn this paper, rational association of traffic simulation (TS) and CO2 emission model (EM) is discussed at
first. Following to the discussion on the reference models of CO2 reduction measurement, the verificationand the validation procedures focusing on individual vehicle trajectories will be summarized.

THE RATIONAL ASSOCIATION OF TS AND EM
Sort of the Granularity of Vehicle Trajectory in TS
There are dozens of TS which are now used in practical study. Since the energy-saving measurement varies
from the microscopic one that works on instantaneous driver’s behavior, such as ‘eco-driving’, to themacroscopic one over the driver’s trip behavior, such as ‘eco-route guidance’ or ‘inter-modal shift’, TS has
to deal with individual vehicle movement in the city size or the region size area, if we are going to consider
those measurement at once. Let us here classify those traffic simulation models in terms of the granularityof vehicle trajectory as shown in Figure 2.
As for 'Link-wised linear', a vehicle runs at the average travel speed which depends on the flow-density
relationship of the current link. The position of the vehicle is identical only at each end of the link.
'State-wised linear' means that a vehicle stops and runs at the constant speed determined by speed-density
relationship of the current link. The position of the vehicle is approximately identical at each position onthe link. 'Fine grained' shows the most precise vehicle movement. A vehicle stops and runs according tosome car following model which updates the acceleration of the vehicle with sufficiently short interval. The
position of the vehicle is identical at each position on the link. The first two types are called piecewise
linear (PWL) trajectories and the last one can be regarded as ‘continuum’ trajectory.

2LinkLink

Link

Figure 2: ‘Fine grained (left)’, ‘state-wised linear (center)’ and ‘link-wised linear (right)’ trajectories in TSSort of EM
EM can be classified as well in terms of granularity of vehicle movement. The simplest but most popular
EM is a ‘trip motive’ type which uses the average travel speed of a vehicle trip. In this type, themacroscopic function to calculate the exhaust volume per unit distance is provided according to the average
speeds of ‘typical’ observed trips.
Another EM which is popular for mechanical engineers is an ‘instant motive’ type which calculates energy
consumption per short time period with the power and the torque that a engine produces. By combining thepower transmission model, this type of EM provides the microscopic function between the instant CO2emission and the vehicle running speed.
There are medium grained EMs between the macroscopic and the microscopic ones, so-called mesoscopic
type. This type calculates the amount of emission for a short travel, e.g. from one stop to the next stop,
according to the proportion of vehicle traveling mode, such as idling, accelerating, decelerating andcruising.

Association of TS and EM Mediated with Piecewise Linear Trajectory
As we mentioned, the energy-saving ITS measurements would work to improve driving behavior in
microscopic scale, while some others would induce trip behavior changes in macroscopic scale. As for themicroscopic level, people might expect TS to produce fine grained trajectories to feed the microscopic EM
which accumulates instant emission depending vehicle's speed and acceleration. It is however suspicious
from the viewpoint of rational use of TS in regional size network, since many of the microscopic TS do notguarantee the validity of vehicle movement in acceleration level for a wide area. It is recommended that theoutput trajectories from microscopic simulation will be simplified to state-wised or link-wise linear
trajectories to feed CO2 emission models. Table 1 shows the rational association of TS and EM for a wide
area study.

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Table 1: Rational association of traffic simulation and CO2 emission model
Modeling level of CO2 emission model

Granularityof vehicle
trajectoryin traffic
simulation

Macroscopic

Mesoscopic

Microscopic(trip motives)(PWL)(fine grained)

Link-wiselinearState-wiselinearFinegrained???
(pessimistic about theregion wide study)

THE REFERENCE MODELS FOR MODEL DEPLOYMENTIn this project, we will NOT intend to develop or specify models nor software to be used for CO2
evaluation, BUT may employ various models as long as the models and software are well verified andvalidated. In this sense, we have proposed the reference models for the following stages; 1) modeling, 2)
verification & validation, and 3) evaluation. The role of those reference models is to identify the subjects tobe checked and confirmed among the stake holders.

Modeling Stage
The reference model for the modeling stage is proposed for each category of the energy-saving ITS
measurements; i.e. 1) improving driving behavior, 2) traffic control for intersections & highway corridors,3) traffic management in network scale, and 4) TDM & modal shift.
Traffic phenomena

TS modeling

Moderate speed &acceleration of ecodriving vehicles.

Speed suppression offollowing vehicles.

PWL trajectory

EM modeling
Normal acceleration
profile at start-up foreco-driving vehicles.

Designation of the model
parameters for ecodriving vehicles.
-- max acceleration atstart-up, desired runningspeed, etc.

Validation of TS(meso-scale)

Development ofmeso-scale EM

Composition of travelingmode from ‘state-wise linear‘trajectory
Vel

Update of running speedwith car-following model.

Time

Validation of TS(macro-scale)
Extension of start-up
loss increases
congestion.

-- # of stopping and duration-- av. running speed andduration

Reproduction ofdischarging flow rate
reduction by moderate
acceleration.

Emission unit for eachtraveling mode.
-- stopping, start-up,running, etc.

Output PWL
veh. trajectory

Figure 3: The reference model for the ‘eco-driving’ model4

The reference models for those ITS measurements are formatted as follows. At first, the traffic phenomena
to be considered are identified. How to model those phenomena in TS is subsequently described. Since weare endorsing the use of PWL trajectory to mediate TS and EM, it is to be described how the ITS
measurement effects on the PWL trajectories output from TS. Finally, some of the traffic phenomena which
are considered not in TS but in EM are described. In order to make a connection to the next ‘verification &validation’ stage, the items which are necessary to be checked in the next stage should be given comments.
Figure 3 is an example for ‘eco-driving’ in the first category of the ITS measurements.

Verification & Validation Stage
TS is often criticized because of its black-box behavior. To overcome that criticism, we are promoting theuse of TS through verification & validation to comprehend the models’ nature. Here, ‘verification’ means
the examination if a model follows rules programmed into a computer as the developer intends. For
instance, we may examine if the number of vehicles generated from an origin is exactly the same as theintended value following the probability distribution specified. The shockwave speed produced by a model
may be checked if the speed matches with the kinematic theory. On the other hand, ‘validation’ is theexamination if a model reasonably reproduces complex real phenomena. In the real world, we face a lot oftraffic phenomena such as merging, diverging, weaving phenomena, etc., which are quite difficult todescribe in a closed form equations. In the validation, we attempt to confirm the reproducibility of realcomplex traffic phenomena.
Figure 4 illustrates our VVD (Verify-Validate and Disclose) policy in so-called 'V-shaped' softwaredevelopment model. Here, let us add the ‘disclosure’ process to the normal V-shaped model. This means forany evaluation model, unless the result of the verification and the validation should be in public, we do not
accept the use of such models.
So far, we have developed the 'Standard Verification Manual' and 'Benchmark Dataset' which have intended
to verify and validate the model nature for the evaluation of ‘delay’ or ‘loss’. In the future scope, we willdisseminate the extended manual to driving behavior level and prepare precise benchmark dataset for thevalidation of CO2 emission model in real world.
V-03:
V-03:Disclosure
Disclosure
Specification
Specification

V-02:
V-02:Validation
Validation

Modeling
Modeling

V-01:
V-01:Verification
Verification

Component
Componentdesign
designComponent
Componenttests
tests

Implementation
Implementation

Figure 4: VVD policy in 'V-shaped' software development model5

Evaluation Stage
The reference models for the evaluation stage depict the ‘proper procedure’ of TS and EM use. For thisstage, we have proposed two types of the evaluation procedure; the integrated approach with total
simulation and the expansion approach with partial simulation. In the former approach, TS may deal withlarge network which covers whole region/nation-wide area and all vehicle trajectories are to be provided toEM. Figure 5 illustrates the procedure of this integrated approach. In the latter approach to the contrary, TS
covers some ‘representative’ small areas in the subject region/nation. The CO2 reduction estimated in therepresentative areas will be expanded to the whole region with proper procedure.

Task number

Calibration
Statistics of thesales data for
petroleum products

E-01-6Functional
component

comparison

Data

E-01-3

Validity checking
data for calibration(aggregated level)
E-01-2
Calibration
Link travel speed

E-01-1
Input (road and transportation
conditions with time-dependent
OD matrix.)

Traffic simulation(has been validated foraggregated traffic conditions)E-01-7

Estimated CO2emission (before)

Link throughput
PWL* trajectories
of individual vehicles

CO2 emission model(meso-scopic)

E-01-8* PWL: Piecewise Linear

E-01-5Traffic simulation +the model of ITS application

PWL* trajectories
of individual vehicles

Macro-scalemeasurements
in Energy ITS
applications

Composition ofvehicle type, age,etc.

CO2 emission model(meso-scopic)+ ITS application

Micro-scalemeasurements
in Energy ITS
applications

Estimated emission
from the neglectedtraffic demand
E-01-4

Estimated CO2emission (after)

CO2 reduction

Figure 5: Evaluation process of the integrated approach with total simulation for region/nation-wide studies

FUTURE DISCUSSION
Our project aims to establish the reliable evaluation method in international context. In this sense, thoseidea presented in this paper are to be discussed and consented in our international collaboration scheme towhich EU and US partners are participating.
We are also working on the development of our TS and EM associating model, which will represent theJapanese models, according to the proposed reference models. However, we will not force to use our model
to EU and US sides. As we mentioned in this paper, we are intending to provide ‘open’ development
scheme on the reference models, if they are approved internationally, anyone can develop the evaluation
model.

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