This document summarizes big transport data collection and analysis efforts in Thessaloniki, Greece. Over 1.4 million people live in Thessaloniki and make an estimated 1.3 million daily trips using private vehicles, public transit, taxis, bicycles, and other modes. Sensors including Bluetooth detectors and GPS data from 1,200 taxis and 600 buses provide real-time and historical data on traffic flows, speeds, travel times, origins and destinations, and mobility patterns. This data is analyzed at the Center for Research and Technology Hellas to support improved transportation planning, modeling, and driver information systems.

1. Dr. Josep Maria Salanova Grau
Center for Research and Technology Hellas - Hellenic Institute of
Transport
Head of “Data collection and processing, algorithm design, and use of
specialized transport software packages” laboratory
Email: jose@certh.gr
Web: www.hit.certh.gr
Big Transport Data in Thessaloniki.
What are the benefits?

2. Thessaloniki on the map
~1.400.000 inhabitants
~450.000 private cars & 20.000 motorcycles
1.300.000 daily trips
1 (+1) public transport operator for urban trips
~35 public transport operators for extra-urban trips
1.950 taxis
6.433 kms of streets
8,8 kms of dedicated bus lanes
12 kms of dedicated bicycle lanes
89,4 kms of ring road
197.696 parking places

3. Existing ITS layout
• Peripheral
• Urban
• Central

4. Thessaloniki Mobility lab

5. Mobile sensors in Thessaloniki
• Stationary sensors network: Point to point tracking of MAC ids along
the network through 43 Bluetooth device detectors.
▫ Travel time estimation
▫ Route choice model calibration
▫ Origin – Destination matrix estimation / Mobility patterns estimation
▫ Traffic flow extrapolation
• Dynamic sensors fleet: Floating Car Data provided in real time by a
professional fleets composed of 1.200 taxis and 600 buses
▫ Traffic status estimation (average speed)
▫ Origin – Destination matrix estimation / Mobility patterns estimation
▫ Taxi/bus performance indicators
• Social media (geolocated tweets & Facebook check-in events)
▫ Activity patterns estimation
▫ Events / incidents detection
▫ Attraction models estimation

6. Dynamic Sensors Data

7. Floating Car Data (taxis)
▫ Device ID
▫ GPS position (X, Y, Z)
▫ Orientation (degrees)
▫ Speed (km/h)
▫ Timestamp
▫ Zone
▫ Status

8. Floating Car Data (taxis)
• 1.200 vehicles (dispatching application)
▫ Circulating 16-24 hours per day
▫ Pulse generated each 100 meters (10-12 seconds)
▫ 500-2.500 pulses per minute

9. Floating Car Data
Real time traffic conditions information based on a combination of traffic
modeling and real time measurements (traffic flow and speed)

10. Stationary Sensors Data

11. Bluetooth devices detectors
• 43 detectors (EEA, SEE-ITS & EASYTRIP)
▫ 4 million detections per week (peak period)
▫ 25.000 unique devices detected per day (one intersection)
▫ 1 million “tracked” trips per week
▫ 20.000 “tracked” trips per day (one path)
• More detectors installed in other cities and in Bulgaria (SEE-ITS &
EASYTRIP)

12. Point to point BT network
Real time travel time provision to drivers (VMS, internet,
smart device)

13. BDE pilot in Thessaloniki

14. • Probe data that is used
▫ Floating Car Data (500-2.500 locations per minute)
▫ Bluetooth detections (millions of daily detections in 43
locations)
• Services that are being implemented
▫ Improved topology-based map matching
▫ Mobility patterns recognition and forecasting
GPS Data
Map Matching
Traffic Classification and
Prediction
Classification and
Prediction Data
Bluetooth Data
Results
BDE pilot in Thessaloniki

15. Dr. Josep Maria Salanova Grau
jose@certh.gr +30 2310 498 433
Thank you!
http://opendata.imet.gr/dataset
Emmanouil Chaniotakis
chaniotakis@certh.gr +30 2310 498 495
Dr. Evangelos Mitsakis
emit@certh.gr +30 2310 498 459
Dr. Georgia Aifandopoulou
gea@certh.gr +30 2310 498 457