FREEFLOW: New tools for advanced network management ... - UTMC

FREEFLOW: New tools for advanced network 

management 

Prof. John Polak, Imperial College London 

Rob Shepherd, ACIS 

© Copyright 2010 FREEFLOW Consortium

FREEFLOW – Overview 

− Motivation and project overview 

− Data Warehouse 

− Intelligent Decision Support 

− Deployment 

− Conclusions 


FREEFLOW – Background 

− Rapid pace of innovation in: 

− data sources (e.g., pervasive GPS, increasingly extensive CCTV) 

− network modelling tools 

− decision support technologies 

− channels of communication with individual traveller 

− Provides enormous scope for innovation in network 

management and traveller information 

− To meet new challenges in transport policy 

− But existing strategies for network management do not fully 

exploit these capabilities, and remain largely reactive 


FREEFLOW – Vision 

− Develop a platform that integrates latest developments in 

data, models, decision support and dissemination 

technologies 

− Modular, pick-n-mix. Not one size fits all 

− Driven by explicit analysis of user requirements 

− Build on, not duplicate, existing investments e.g., in the UK’s 

UTMC architecture 

− Develop services, tools and approaches that can be used in 

the UK and elsewhere 


FREEFLOW – Project and Partners 

Sponsors 

Demonstrators 

Industrial 

Academia 


FREEFLOW – Key Elements 

− Sensor processing (e.g., enhanced signal processing) 

− Data warehouse (e.g., how do I access all these data), data sharing and 

dissemination using open standard interfaces with real-time capability 

− Sensor data fusion (e.g., combining CCTV, ILD, GPS, ANPR data for 

network performance estimation) 

− Network state estimation and prediction (e.g., where are the 

queues/incidents, are they growing or clearing) 

− Strategy development and selection (e.g., what should we do, what 

worked in the past, what does modelling tell us) 

− Tools for integration, visualisation and decision support (e.g., how do I get 

at and use all this information) 


FREEFLOW – Data Warehouse Context 

Kent and York 

FREEFLOW Data Warehouse 

Other 

Applications 

Existing 

UTMC 

CDB 

Data 

Source 

UTMC CDB 

Import 

Adapter 

Direct Data 

Source 

Adapters 

UTMC Compliant 

Database 

Adapter 

Manager 

UDG XML SIRI UTMC 

IDS 

ODS 


FREEFLOW – Data Warehouse Context TfL 

TDES, (Traffic Signal Timing) 

LDIS, (VMS) 

LTIS, (Traffic Information) 

IRID, (Image Recognition (CCTV)) 

SFM, (Fault/Asset Management) 

SOX-D, (UTC/SCOOT Data) 

Real-time 

Data 

Sources 

LCAP, (ANPR (Journey Time)) 

OUTCAST, (Historic UTC and 

Traffic Signal Data) 

JTE, (Journey Time Estimator – 

GPS and Loop Data) 

Historic 

Data 

Sources 

UTMC CDB (COMET) 


Input 

Adapters 


Output 

Adapters 


Input 

Adapters 

Data 

Warehouse 

UDG XML SIRI UTMC 

Other 

Applications 

ODS 

IDS 


FREEFLOW – Data Warehouse Design 

UTMC CDB 

Import Adapters 

Direct Data 

Source Adapters 

Adapter Manager 

Output Cache 

Database Cache 

Web Server 

Database Manager 

© Copyright 2010 FREEFLOW Consortium 

UTMC Compliant 

Database

FREEFLOW – IDS Overview 

− The ‘intelligence’ in IDS resides in four dimensions: 

− Being able to fully utilise all available data sources 

− Being able to identify and predict potential problems 

− Being able to systematically use past experience to respond 

to problems 

− To view network management and traveller information as 

an integrated activity 


FREEFLOW – IDS Overview 

Data 

Interface 

State 

Estimator 

Rule-based 

Triggers 

IDS 

Rules 

Engine 

Rule-based 

Interventions 

Pattern 

Matcher 

Intervention 

Evaluator (PI) 

Intervention 

Lookup 

Alert + 

Intervention 

Potential Causes 

of Alert 

Events & 

Faults 

Lookup 

Historic Traffic 

Sensor Data 

(CMM) 

Historic 

Traffic Control 

Interventions 

Historic 

Events & 

Faults 


FREEFLOW – IDS Flowchart 

Real World 

Sensors 

IDS 

State Estimator 

State Prediction 

Intervention 

Needed 

Yes 

Strategy Selection 

Intervention 

Knowledgebase 

Historic 

Traffic 

Data 


FREEFLOW – IDS – a simple state estimator 

− Input: Flow and occupancy data from ILDs 

− Output: In its simplest form, categorises the current traffic 

state (flow, occupancy) as congested or uncongested) 


FREEFLOW – IDS - rules engine 

− Pattern matcher determines which of the IDS subcomponents 

to invoke using 

− The output of the state estimator 

− Data from traffic sensors 

− The rules engine chooses one of the following options 

− Recommends pre-selected traffic control interventions for 

known traffic problems 

− Invokes the pattern-matcher for problems not defined in 

the rule-set 


FREEFLOW – IDS - pattern matcher 

− The idea behind pattern-matcher – learn from past 

experience (what has worked and what has not) 

− Objective: find past traffic states with similar spatial pattern 

and severity 

− Successful interventions during similar traffic problems in the 

past are potential solutions to the current problem 


FREEFLOW – IDS – interventions & events 

− Data from similar past problem states can provide successful 

past interventions for similar problems 

− Interventions can be quantitatively ranked using a PI metric 

− Historic data can also reveal potential causes of the problem 

− Traffic incidents. e.g. broken down vehicle 

− Equipment failure. e.g. traffic light faults 

− Makes use of the historic archive of traffic control, incident 

and fault logs available in many cities 


FREEFLOW – Demonstrators 

− York 

− UTMC history and investment to build on 

− Bus service reliability is key priority 

− Demonstrations on multiple radials 

− Kent 

− UTMC history too 

− Motorways around Maidstone impact on network 

− Active management of urban/interurban interface during incidents 

− London 

− Different UTC architecture 

− Very large authority 

− Active management at Hyde Park Corner 

− Data Warehouses exist at all three demonstration sites 


FREEFLOW – Data Warehouse 

− In deploying the Data Warehouse we encountered certain 

challenges: 

− Extracting data from existing in-situ UTMC Common 

Databases using repeated request response cycles is not 

efficient 

− The Databases were never designed to support this 

− Interfaces that are not open standards do impede data 

exchange 


FREEFLOW – Data Warehouse 

− City of York 

− SCOOT data, Car parks, VMS, roadworks, bus Transport 

Link, (bus Transport Route) 

− Holds historical data back to August 2009 

− Car Park Dynamic – 438,000 records 

− Kent County Council 

− TL ANPR, VMS, Flow, Speed, Occupancy 

− To add when XML publisher is upgraded: 

− Roadworks, Incidents, Car Parks, Accidents, MIDAS 

− VMS 215,000 records since June 2010 

− TL ANPR 277,000 records since June 2010 


FREFLOW – Data Warehouse 

− Transport for London 

− Traffic Signal Timing, LDIS, (VMS), LTIS, (Traffic 

Information), IRID, (Image Recognition (CCTV), Fault/Asset 

Management, UTC/SCOOT Data, LCAP, (ANPR (Journey 

Time)), OUTCAST, (Historic UTC and Traffic Signal Data), 

Journey Time Estimator (based on GPS and Loop Data) 

− 2,500,000 records per day 


FREEFLOW – Conclusions 

− Data Warehouse 

− Has proven the UDG XML SIRI interface for UTMC data object 

exchange 

− There is now a proven open standard that allows the easy 

sharing of data in line with current IT industry practice 

− The use of defined XML schema as part of the standard allows 

automatic code generation to be used to speed up 

implementation 

− IDS 

− Integrates state of the art modelling with rule based protocols 

− Fully exploits a wide range of data sources 

− Supports institutional learning

FREEFLOW: New tools for advanced network management ... - UTMC

Create successful ePaper yourself

Delete template?

Save as template?