Computer Technology Institute, Greece German Aerospace Institute, Germany

Computer Technology Institute, GreeceGerman Aerospace Institute, GermanyVienna University of Technology, AustriaEmphasis Telematics, GreeceGeomatics, GreeceGreenway Systeme, GermanyWIGeoGIS, AustriaTALENT, Greece

http://www.trackandtrade.orga co-operative research project funded by the European Commission

TRACK&TRADE Web presentation

Project OverviewSlide 2 of 12

Motivation Use of Floating Car Data (FCD) to assess

“traffic” Floating car data?

– basic vehicle telemetry, e.g., speed, direction, ABS use– the position of the vehicle ( tracking data)– GPS tracking

Traffic assessment– data from one vehicle as a sample to assess overall

traffic conditions – cork swimming in the river – large amounts of tracking data (e.g., taxis, public transport,

utility vehicles, private vehicles) accurate picture of the traffic conditions

– >>>cheap data source<<<



Motivation Travel time fluctuation in

road network Live assessment

– deriving travel times from FCD (tracking data)

– one vehicle one route

– many vehicles (good) coverage of the entire road network

Historic data– collections of FCD to derive

trends

– complement live data



The Project Goal

To build a Web-based platform that

1) enables “people” to contribute their “tracking” data in the “simplest” possible way and

2) based on the collected tracking data, provides basic, value-added services (API) serving as building blocks for rich(er) services.



System Overview

Public data collection and dissemination site

Web services Data collection Data dissemination

– travel time maps– travel time assessment– travel time prediction– building blocks for

richer applications/services



Data Scenario GPS vehicle tracking data

– large variety of vehicles– vehicle fleets, e.g., taxis, school buses,

delivery trucks, – indiv. vehicles

Real-time data – Berlin, Vienna, and Athens

Berlin Vienna Athens



Data Scenario

Definition of a data model for FCD (tracking data)

– rely on existing standards (KML, geoRSS)

Creation of a data collection service for FCD– key aspect – simple set up for adding new FCD source to data

mart

– analysis of data provider expectations – encryption, type of connection



Data Pre-Processing

Map-matching algorithms– relating the GPS vehicle tracking data (FCD) to

road network

– compensates for measurement (GPS) and sampling error (30s) in the tracking data



Data Management

Computing link-based travel times– derivation of current and future travel times from collected

– current and– historic travel time data

From route-based to road-based travel times– “distributing” travel times from routes (tracking data)

to links in the road network

Inhomogeneous FCD problem– different types of vehicles producing data

– making travel time data comparable



Services

FCD collection service– simplest possible way for new data providers to connect to the

data mart

Value-added services to provide elementary building blocks of rich(er) services (API)

– Travel time maps – visualization of travel time conditions

– Travel-time assessment and prediction service - given a road network and time horizon provide (expected) travel times

Evaluation– integration with existing services – fleet management, routing,

traffic-light switching



Platform

Integrating data management and servicesinto a single platform

Web+Map interface based on the Cruiser platform

http://www.cruiser.gr/



Contact

Dieter PfoserRA Computer Technology InstituteDavaki 10GR-11526 Ampelokipoi, AthensGreece

Phone: +30-210.6930.700Fax: +30-210.6930.750email: pfoser.cti.gr Web: www.trackandtrade.org

Documents

Computer Technology Institute, Greece German Aerospace Institute, Germany