GIS and traffic data used in a traffic hackathon Edwin Kools

Transcription

1 GIS and traffic data used in a traffic hackathon Edwin Kools

2 TOMTOM CONNECTED NAVIGATION SYSTEM IN NUMBERS 24 YEARS MILLION 270 BILLION 13.9 TRILLION of software development countries supported by our software globally accepted patents devices globally kilometers driven anually by our users speed measurements collected

3 TOMTOM CONNECTED NAVIGATION SYSTEM

4 CONNECTED SERVICES POWER THE SEAMLESS EXPERIENCE Online Search NavCloud Online Routing Real-time Map Updates Traffic Speed Cameras Weather EV POIs Parking Fuel Navigation portal Embedded software Companion apps

5 TomTom Traffic innovation in traffic information

6 ABOUT THE HACKATHON

7 150 PARTICIPANTS - 48 HOURS

8 City of Toronto goals Encourage innovation, use of new technologies and data More insight in the transportation system Link with tech and data communities Toronto to become leader in big transportation data initiatives Make Toronto a better place

9 City of Toronto challenges Which links (intersections) are the most congested? Which links (intersections) are the most unreliable? Which ones are getting worse fastest? What was the impact to other corridors with the Gardiner closure? Do lane closures increase the chance of collisions? When and where does the most impacting non-recurring congestion occur?

10 City of Toronto goals Better understand transportation in Toronto Make better use of data Use available and unknown data sources Turn this data into information Models GIS

11 TomTom goals Raise general awareness of richness and availability of traffic data Showcase TomTom traffic content and expertise Showcase quality and usability of TomTom APIs and GIS data Collaborate with City of Toronto

12 TOMTOM DATA

13 TomTom dynamic routing

14 Real-time TomTom Traffic

15 TomTom map tiles

16 TomTom hotspots

17 TomTom historical travel times

18 HACKATHON SOLUTIONS

19 Hackathon solutions Correlation found between parking violations and historical bottleneck data

20 Hackathon solutions Traffic signal optimisation

21 Hackathon solutions Traffic signal optimisation

22 Hackathon solutions Feasibility of rerouting buses during peak hours

23 Hackathon solutions Event management: Travel times during PanAm Games

24 Mapping incidents Hackathon solutions

25 Travel time analysis Hackathon solutions

26 Hackathon solutions App: earn rewards for avoiding peaks

27 Bottleneck analysis Hackathon solutions

28 Hackathon solutions 3 rd place: analysis of the walkability of streets

29 Hackathon solutions 2 nd place: Traffic/commute forecast (based on historical traffic counts, time of day, day of week and weather)

30 Hackathon solutions Winners: analysis of the reliability of Toronto s commutes

31 CONCLUSIONS

32 Conclusions Combining and merging data is valuable Innovation and creative solutions Focus on spatial data (traffic is spatial) A good weekend for all Participants City of Toronto TomTom

33 SEE YOU AT THE NEXT TRAFFIC HACKATHON!

34 THANK YOU QUESTIONS?

35 A HISTORY OF INNOVATION Launch of the Bandit Action Cam

36 OUR BUSINESS TODAY Consumer PND global leader Sports Watches Action cameras B2B off the shelf devices Automotive Maps, traffic & software components to car manufacturers BMW, VW, Ford, Toyota, Mercedes-Benz, Fiat, Audi, Opel/Vauxhall, Subaru, Peugeot Telematics Fleet management & vehicle telematics for increased efficiencies Government& Business Traffic Management, Planning, Models, Policy Development 4,200 employees in 56 offices across 37 countries worldwide

37 TomTom Traffic portfolio HISTORICAL TRAFFIC REAL TIME TRAFFIC TRAFFIC STATS Speed Profiles Custom Area Analysis Custom Travel Times TomTom Traffic TomTom Traffic Flow TomTom Route Times

38 Pioneering largest road coverage with Open Location Referencing TMC location referencing typically only covers 10% of roads With OpenLR all roads can be covered