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Traffic State Information based on Mobile
Phones
DI Walter Schneider Mag. Elisabeth Mrakotsky
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Arsenal research - Transport Technologies

• Real-time prognosis of traffic data and travel
  time estimation
• Development of simulation models for short-time
  prediction of traffic flows
• Intelligent sensorsRecording and evaluation of
  traffic situation

Transport Technologies
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Approach

• Traffic State Information Which data are
  needed?
• Timestamp
• Location
• Average speed between two points
• Direction
• Sensor Technology Which traffic sensors could
  provide this?
• Floating Car Data (FCD)
• How to proceed?
• Arsenal research developed a method based on
  mobile phones

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Focus of the project

• Application on a mobile phone
• Cell positioning
• Precise localizations through cell transitions
• Client server communication
• Travel time for main roads
• Average speed
• Origin-destination matrix
• Georeferencing on RDS TMC location code
• Generating traffic state information
• Evaluation of results in co-operation with the
  traffic department of the national broadcast
  company

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Method for cell positioning
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Develop the mobile application

• Mobile phone

• Symbian
• Series 60
• UIQ

STK Application
JAVA Application
New approaches
PDA
GPS
System evaluation
Measurement of cell transitions
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Test area Geo-referenced cell transitions
Vienna
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Travel time first step
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Travel time second step
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Traffic state information
Travel time betweentwo points in comparison to
free flow
results in a percentage of the delay

• Traffic state according to the obtained delay
• free flow
• synchronized traffic
• traffic congestion

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Evaluation of traffic state information
Travel time information on the mobile device
Past running time
Current delay
Expected Travel time (at free flow conditions)
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Results and Conclusion

• Cell transitions
• Good results in urban areas
• Simple method to get travel times
• Nearly 97 correct traffic state information
• Can serve as a basis for local based services
• Development on mobile phones
• Problems with often changing operating systems
• Implementation in a fleet
• Testfleet was too small to launch a service
• Gap between RD and commercial usage

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Next steps

• Method
• Combination with other data sources (e.g. weather
  conditions)
• Bidirectional data flow (traffic information
  comes back to the user)
• Mobile phones
• Platform independence (JAVA Application was part
  of a theses work)
• Implementation in a fleet
• Further development is required to make the
  system practicable
• Launching a marketing concept to get a critical
  mass

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Thank you for your attention!
DI Walter Schneider Phone 43 (0)
50550-6625 www.arsenal.ac.at walter.schneider_at_ars
enal.ac.at