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Big (Traffic) Data
Probe Data Analytics and Processing for Traffic Information, Traffic
Planning and Traffic Management
Ra...
2
A B
2
3
Huge investment and
maintenance costs to
detect traffic information
Typically every 2 km a
loop required to get
precise ...
4
Change
5
Facebook Social Activity Graph
(friend interactions)
Traffic Community of 350M+ connected users
• 9 trillion anonymous speed
measurements (9.000.000.000.000)
• 8 billion speed...
7
IQ Routes
GPS PROBE DATA
8
Time-Space Characteristics
t
x
4
Local detection
(loops)
Moving Detection
Floating Car
1 1
2
1
2
Probe vehicle
(e.g. GPS)
From Modeling to Measuring
9
Classical tools for observing traffic flow: Simulation and Data from Loop-Detectors
Simulated...
From Modeling to Measuring
10
Direct speeds observations with GPS probe data
• GPS data allows traffic
observation everywh...
TomTom Congestion Index Europe (Q3 2013)
Traveltime delays compared to free flow situation at night hours
11
http://www.to...
Speeds Over Time (City, e.g. Berlin)
12
Sun Mon Tue Wed Thu Fri Sat
speed
Speed Frequencies Weekdays (City e.g. Berlin)
13
6 km/h 43 km/h
numberofprobes
Speed Probe Data (Freeway, e.g. A9 south of Berlin)
14
Speeds Over Time (Freeway , e.g. A9 south of Berlin)
15
Sun Mon Tue Wed Thu Fri Sat
speed
ORIGIN-DESTINATION ZONE ANALYSIS
16
Data collection of origin-destination
data is difficult
Current techniques include
- S...
17
Selected link: links to links Selected link: zones to zones
A B
A 30 5
B 10 20
OD MatrixRoute choice
Detailed junction analysis per path
Speed measurements
over time
Speed measurements
grouped by day of the
week
Speed frequ...
Junction Stop Characteristics
Number of average
stops per traversal
Average stop time per
traversal
Data fusion Send to users
GPS
Probe Data
GSM
Probe Data
Journalistic
info
Historic
Traffic
Map Data
Various input sources
...
Probe Data Example of Traffic Incident
GPS and GSM input sources and incident output message
21
• Example from Dec 13, 201...
JAM TAIL WARNINGS
Detection of jam tails for a safety warning in the navigation unit
• Over 35% of drivers have admitted t...
Real-time road speed data
Enable traffic information and traffic
management
 Measured speed on each road segment
 On all...
24
The TomTom Traffic Manifesto
If 10% of the road drivers use HD Traffic
guided navigation in conurbations there is
a
1. ...
10% 10%
How to estimate the journey time reduction
claims in the TomTom Manifesto?
Use of traffic modelling and simulation...
26
Dynamic Navigation for personal and collective benefits
24 Hour Time Lapse – NYC
27
5 day historical– NYC
Monday
31 minutes
Tuesday
16 minutes
Wednesday
9 minutes
Thursday
18 minutes
Friday
4 minutes
Tim...
The (future) Traffic Management Challenge
Load balanced vs unbalanced routing system using dynamic route guidance
vs.
Educated Guess – Probe Data Source?
29
Educated Guess 2nd – Probe Data Source?
30
Thank You
ralf-peter.schaefer@tomtom.com
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EDF2014: Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany: Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management

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Industry Keynote Talk by Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management.

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EDF2014: Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany: Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management

  1. 1. Big (Traffic) Data Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management Ralf-Peter Schäfer Fellow & VP Traffic and Travel Information Product Unit ralf-peter.schaefer@tomtom.com 1 Copyrights: TomTom Internal BV 2014
  2. 2. 2 A B 2
  3. 3. 3 Huge investment and maintenance costs to detect traffic information Typically every 2 km a loop required to get precise real-time traffic infos Can we do better?
  4. 4. 4 Change
  5. 5. 5 Facebook Social Activity Graph (friend interactions)
  6. 6. Traffic Community of 350M+ connected users • 9 trillion anonymous speed measurements (9.000.000.000.000) • 8 billion speed measurements per day (6.000.000.000) • 22 trillion driving seconds (22.000.000.000.000) • Speed estimation via map matching and data analytics
  7. 7. 7 IQ Routes GPS PROBE DATA
  8. 8. 8 Time-Space Characteristics t x 4 Local detection (loops) Moving Detection Floating Car 1 1 2 1 2 Probe vehicle (e.g. GPS)
  9. 9. From Modeling to Measuring 9 Classical tools for observing traffic flow: Simulation and Data from Loop-Detectors Simulated elementary traffic jam patterns: Interpolated and smoothed data from loop detectors:
  10. 10. From Modeling to Measuring 10 Direct speeds observations with GPS probe data • GPS data allows traffic observation everywhere • Independent from stationary devices • Sampling rate sufficient for real-time traffic information
  11. 11. TomTom Congestion Index Europe (Q3 2013) Traveltime delays compared to free flow situation at night hours 11 http://www.tomtom.com/congestionindex
  12. 12. Speeds Over Time (City, e.g. Berlin) 12 Sun Mon Tue Wed Thu Fri Sat speed
  13. 13. Speed Frequencies Weekdays (City e.g. Berlin) 13 6 km/h 43 km/h numberofprobes
  14. 14. Speed Probe Data (Freeway, e.g. A9 south of Berlin) 14
  15. 15. Speeds Over Time (Freeway , e.g. A9 south of Berlin) 15 Sun Mon Tue Wed Thu Fri Sat speed
  16. 16. ORIGIN-DESTINATION ZONE ANALYSIS 16 Data collection of origin-destination data is difficult Current techniques include - Stop cars: road side interviews - Get address from license plate and send survey - Telephone interview - Panel fills in a diary of their movements - Point to point tracking: license plates (full) or bluetooth (sample)
  17. 17. 17 Selected link: links to links Selected link: zones to zones A B A 30 5 B 10 20 OD MatrixRoute choice
  18. 18. Detailed junction analysis per path Speed measurements over time Speed measurements grouped by day of the week Speed frequency distribution, free flow estimate Distribution of Travel time delta
  19. 19. Junction Stop Characteristics Number of average stops per traversal Average stop time per traversal
  20. 20. Data fusion Send to users GPS Probe Data GSM Probe Data Journalistic info Historic Traffic Map Data Various input sources 20 REAL-TIME TRAFFIC INFO FROM USERS TO USERS
  21. 21. Probe Data Example of Traffic Incident GPS and GSM input sources and incident output message 21 • Example from Dec 13, 2011 • Near Stuttgart, Germany • GPS data from floating cars • Speed data matched to road elements • GSM data from mobile phone calls • Sophisticated algorithm • After fusion and incident detection • Live incident output to PND
  22. 22. JAM TAIL WARNINGS Detection of jam tails for a safety warning in the navigation unit • Over 35% of drivers have admitted to experiencing an accident caused by sudden or unexpected traffic holdups • Jam ahead warning messages in traffic output can be used to create these safety messages with great accuracy 22
  23. 23. Real-time road speed data Enable traffic information and traffic management  Measured speed on each road segment  On all important roads  Without the need of road-side equipment  By using Floating Car Data  Updated every minute 23 TOMTOM TRAFFIC Traffic Flow Flow conditions (speed) on all roads
  24. 24. 24 The TomTom Traffic Manifesto If 10% of the road drivers use HD Traffic guided navigation in conurbations there is a 1. Individual journey time reduction for informed users by up to 15% 2. A collective journey time reduction for ALL by up to 5% http://www.tomtom.com/trafficmanifesto
  25. 25. 10% 10% How to estimate the journey time reduction claims in the TomTom Manifesto? Use of traffic modelling and simulation in a simplified road network Assume a share of equipped navigation users (e.g. traffic guided drivers) Assume high acceptance rate for detour choices when approaching a traffic jam! Results from simulation below for medium and high traffic flow Source: F. Leurent, T. Nguyen, TRB 2010.
  26. 26. 26 Dynamic Navigation for personal and collective benefits 24 Hour Time Lapse – NYC
  27. 27. 27 5 day historical– NYC Monday 31 minutes Tuesday 16 minutes Wednesday 9 minutes Thursday 18 minutes Friday 4 minutes Time Saved: 1 Hour, 18 Minutes
  28. 28. The (future) Traffic Management Challenge Load balanced vs unbalanced routing system using dynamic route guidance vs.
  29. 29. Educated Guess – Probe Data Source? 29
  30. 30. Educated Guess 2nd – Probe Data Source? 30
  31. 31. Thank You ralf-peter.schaefer@tomtom.com

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