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Computer Technology Institute, Greece German Aerospace Institute, Germany

http://www.trackandtrade.org a co-operative research project funded by the European Commission. Computer Technology Institute, Greece German Aerospace Institute, Germany Vienna University of Technology, Austria Emphasis Telematics, Greece Geomatics, Greece Greenway Systeme, Germany

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Computer Technology Institute, Greece German Aerospace Institute, Germany

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  1. http://www.trackandtrade.orga co-operative research project funded by the European Commission Computer Technology Institute, Greece German Aerospace Institute, Germany Vienna University of Technology, Austria Emphasis Telematics, Greece Geomatics, Greece Greenway Systeme, Germany WIGeoGIS, Austria TALENT, Greece

  2. 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<<<

  3. 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

  4. 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.

  5. 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 System Overview

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. Platform • Integrating data management and servicesinto a single platform • Web+Map interface based on the Cruiser platform

  12. Contact • Dieter PfoserRA Computer Technology InstituteDavaki 10GR-11526 Ampelokipoi, AthensGreecePhone: +30-210.6930.700Fax: +30-210.6930.750email: pfoser.cti.gr Web: www.trackandtrade.org

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