Day2-1600-Telemetry, global traffic and OSM

Saturday 4:00pm, Main hall
Lily Chai

http://2017.stateofthemap.org/2017/global-traffic-with-osrm/

Transcript

1. T E L E M E T R Y enhancing & unlocking new potential in OSM
2. OV E RV I E W what is telemetry? how does Mapbox handle telemetry data? what we can calculate from telemetry data? what are the use cases? traffic
3. T E L E M E T RY any data collected from a remote device [lng, lat, alt, timestamp] telemetry pipeline clock GPS sensor +
4. “probe” [x, y, z, t] P RO B E VS . T R AC E
5. “trace” [ [x, y, z, t], [x, y, z, t], [x, y, z, t], [x, y, z, t] ] P RO B E VS . T R AC E
6. A N O N Y M I S AT I O N
7. A N O N Y M I S AT I O N
8. A N O N Y M I S AT I O N
9. A N O N Y M I S AT I O N
10. P R I VAC Y only store anonymised data data is encrypted using industry best practice clear boundaries around who has access & for what reason audit-able access logs more info – https://www.mapbox.com/telemetry/
11. “probe” [x, y, z, t] “trace” [ [x, y, z, t], [x, y, z, t], [x, y, z, t], [x, y, z, t] ]
12. B E A R I N G
13. speed = distance duration S P E E D d ∆t
14. acceleration = ∆speed duration AC C E L E R AT I O N
15. U S E C A S E S
16. VO LU M E from probe density missing streets satellite imagery alignment health of satellite imagery
17. VO LU M E from probe density missing streets satellite imagery alignment health of satellite imagery
18. VO LU M E from probe density missing streets satellite imagery alignment health of satellite imagery telemetry density raster satellite imagery edge detection edge detection vertical offset horizontal offset *
19. VO LU M E from probe density missing streets satellite imagery alignment health of satellite imagery telemetry density poor imagery quality
20. M A N E U V E R S from trace density restrictions (turns, one-ways) high-precision trajectory of lane centreline for ADAS traces present absence of traces
21. M A N E U V E R S from trace density restrictions (turns, one-ways) high-precision trajectory of lane centreline for ADAS
22. T R A F F I C from speed, bearing, acceleration road congestion traffic-aware navigation
23. T R A F F I C from speed, bearing, acceleration road congestion traffic-aware navigation
24. T R A F F I C
25. W H Y T R A F F I C origin destination estimated trip duration (ETA) date-time traffic-powered OSRM OSRM public demo server
26. LUA P RO F I L E rule-based static 100% road coverage
27. T R A F F I C P RO F I L E telemetry-based dynamic coverage fluctuates (never 100%)
28. N O I S E R E M OVA L duration distance speed bearing deceleration acceleration modality
29. P RO B E M ATC H distance from road bearing from road highway hierarchy
30. P RO B E M ATC H distance from road bearing from road highway hierarchy
31. P RO B E M ATC H distance from road bearing from road highway hierarchy
32. P RO B E M ATC H distance from road bearing from road highway hierarchy higher rank lower rank
33. P RO B E M ATC H tertiary road distance from road bearing from road highway hierarchy
34. N O R M A L I S E D G R A P H traffic data uses split at road class change intersection merge otherwise.
35. N O R M A L I S E D G R A P H traffic data uses split at road class change intersection merge otherwise.
36. N O R M A L I S E D G R A P H traffic data uses split at road class change intersection merge otherwise.
37.        0 20 40 60 80 100 120 140 160 Speed [kph] Count [-] W H I C H S P E E D
38.        0 20 40 60 80 100 120 140 160 Count [-] W H I C H S P E E D primary secondary tertiary motorway trunk links alleys service roads …etc. Speed [kph]
39. N O R M A L I S E D G R A P H traffic data uses
40. E D G E - BA S E D G R A P H OSRM uses transform maneuver → edge street → node
41. segments N O R M A L I S E D G R A P H traffic data uses E D G E - BA S E D G R A P H OSRM uses
42. segments N O R M A L I S E D G R A P H traffic data uses E D G E - BA S E D G R A P H OSRM uses T R A F F I C M A P S I N C I D E N T S T U R N P E N A LT I E S R E A LT I M E T R A F F I C VO LU M E
43. T E L E M E T RY ETA, error percentile, etc. layer against road network & attributes road network & attributes better, fresh satellite imagery where to focus (proactive) what is suspicious (proactive) where/what is an issue (reactive) where imagery is outdated DATA T E A M DATA T E A M S AT E L L I T E T E A M traffic