Benjamin N. Passow[benpassow@ieee.org]De Montfort University

Leicester, UK

The Power of Computational IntelligenceCase study: iTRAQ

Benjamin N. Passow, David Elizondo,Eric Goodyer and Simon Witheridge

De Montfort UniversityLeicester, UK

Fuzzy Logic

Artificial Neural

Networks

Evolutionary Computation

Computing with words

Decision Making

Learning

Adaptation

Efficient Searchand Optimisation

Artificial ImmuneSystems

ComputationalIntelligence

Swarm Intelligence

&

Overview

Chrono. data

Traffic data (in-situ)

Met. data

In-situAir Quality

Air quality model

City Plan& O/D

Computational Intelligence Module

Traffic Simulator

feedback for iterative optimisation process

EO AQ data(OMI,GOME-2)

MACCmodelled AQ

Optimised Traffic Management

StrategyGNSS Floating

Car Data

Actual Forecast ResultsTr

affic

Flow

(veh

/hr)

Air Q

ualit

y N

O2

(ugm

-3)

Flow % Delay %

Hour of day Hour of day

Strong increase in traffic flow Substantial decrease in delay While simultaneously managing air quality

7 8 9 10 11 12 13 14 15 16 17

-6.00

-5.00

-4.00

-3.00

-2.00

-1.00

0.00

7 8 9 10 11 12 13 14 15 16 170.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

Results

Initial Study Conclusions

I. iTRAQ is operationally feasible

II. The system demonstrated:• increase in traffic flow 89% of the time (avg +0.6%)• reduction of delay every time (avg -3%)• (using only two neighbouring junctions)

III. iTRAQ provides additional information:• forecasts• suggest enhanced strategies

IV. The iTRAQ system can• inform and support operator decision-making• have autonomous control over both objectives (when fully tested)

Conclusions

Initial Study Conclusions

What can Computational Intelligence do for you?