The MATSim Santiago open data model

Transcription

1 DLR.de Slide 1 The MATSim Santiago open data model Development and first applications Leonardo Camus Alejandro Tirachini Benjamin Kickhöfer Credits to: Daniel Hosse Kai Turner Felix Zwick

2 DLR.de Slide 2 Agenda 1. History of MATSim Santiago 2. Recent developments 3. Challenges and first applications 4. Summary and outlook

3 DLR.de Slide 3 History of MATSim Santiago

4 DLR.de Slide 4 How it all started

5 DLR.de Slide 5 First impressions

6 DLR.de Slide 6 Open data sources 1. Street network from OSM 2. Public transit supply data as GTFS 3. Travel diaries (and other stuff) from EOD2012 Exported from Microsoft Access into *.csv Includes some freight traffic (and other information)

7 DLR.de Slide 7 v1: first simulations Raw data: individuals (~1%) trips MATSim: individuals trips

8 DLR.de Slide 8 v1: integrating public transit

9 DLR.de Slide 9 v1: behavioral parameters and calibration

10 DLR.de Slide 10 Recent developments

11 DLR.de Slide 11 Leo (v2): overview Remove agents that were interviewed in summer vacation time and on weekends Use expansion factors to create a 1% and a 10% sample Add time-dependent tolls to tollways Randomize activity end times using smartcard data Randomize activity locations using land use data

12 DLR.de Slide 12 Leo (v2): randomize activity end times using smartcard data

13 DLR.de Slide 13 Leo (v2): randomize activity locations using land use data

14 DLR.de Slide 14 Felix (v3): implementing colectivos

15 DLR.de Slide 15 Felix (v3): travel times, slack times, fares

16 DLR.de Slide 16 Felix (v3): colectivo (also) as PT feeder

17 DLR.de Slide 17 Challenges and first applications

18 DLR.de Slide 20 Influence of sample size on travel times

19 DLR.de Slide 21 Cordon pricing schemes: setup Outer cordon Inner cordon τ in = $6.000 τ out = $3.600 τ in = $6.000 τ out = $2.650

20 DLR.de Slide 22 Cordon pricing schemes: elasticities 7:30-8:30 In- and outflow Total travel distance car Number of car trips

21 DLR.de Slide 23 Summary and outlook

22 DLR.de Slide 24 Open data scenario Documentation: (more to come for v2, v3, ) Different versions of the runnable MATSim scenarios (no MATSim installation necessary): Code:

23 DLR.de Slide 25 Further steps Ideal for BSc or MSc theses; the idea is to integrate every improvement into the current state and create a new version. Possible improvements: Synthesize a 10% or 100% population Calibrate travel times, counts Add tolled roads Activity distribution according to land use data Network corrections with automatic feedback to OpenStreetMap Add freight transport (important for emissions!) Add colectivos, taxis Include capacity constraints for PT vehicles Map PT routes to the road network (interaction with cars) Include bike as transport mode

24 DLR.de Slide 26 Backup

25 DLR.de Slide 27 Opportunities Social value: better transport planning through competition (identification of weak spots of the system, policy studies, environmental/social analysis, provision of public infrastructure) Commercial value: creating a platform for innovative mobility-based services (car sharing systems, supply chain/location planning, delivery/logistic planning, navigation, ) Transparency: Participation/engagement: