Introducing the eqasim pipeline: From raw data to agent-based transport simulation

 

Sebastian Hörl, Miloš Balać

 

25 March 2021

ABMTRANS 2021

Motivation

  • Agent-based transport simulations (studies) require considerable input data, which generally consists of the transport supply and transport demand
     
  • Usually the generation of transport supply and demand is decoupled from the agent-based model itself.
     
  • This leads to situations where one cannot trace back the inputs of the studies, which makes them unreproducible and unverifiable by others.
     
  • Use of proprietary data further complicates the situation

eqasim

An integrated pipeline from raw data to agent-based simulation:

  • Synthesis of travel demand
  • Agent-based simulation 

eqasim

An integrated pipeline from raw data to agent-based simulation:

  • Synthesis of travel demand
  • Agent-based simulation 

eqasim - Synthesis of travel demand

Census data

Récensement de la population

RP

Île-de-France

Dispositif sur les revenus localisés sociaux et fiscaux
Income tax data

RP

FiLo
SoFi

 

Île-de-France

RP: Flux de mobilité
Commuting data

RP

RP
Mob

 

FiLoSoFi

Île-de-France

SIRENE
Enterprise census

RP

S

FiLoSoFi

RP Mob

BD-TOPO
Address database

BD

Île-de-France

RP

FiLoSoFi

RP Mob

Enquête globale de transport
Household Travel Survey

RP

EGT

FiLoSoFi

RP Mob

Enquête national transports et deplacements
Household Travel Survey

ENTD

Île-de-France

RP

FiLoSoFi

RP Mob

SIRENE

BD-TOPO

Enquête globale de transport
Household Travel Survey

RP

EGT

FiLoSoFi

RP Mob

Enquête national transports et deplacements
Household Travel Survey

ENTD

Île-de-France

RP

FiLoSoFi

RP Mob

SIRENE

BD-TOPO

Île-de-France

Person ID    

Age

Gender

Home

1

43

male

(x,y)

2

24

female

(x,y)

3

9

female

(x,y)

RP

FiLoSoFi

RP Mob

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

BD-TOPO

Person ID    

Activity

Start

End

Loc.

523

home

08:00

(x,y)

523

work

08:55

18:12

(x,y)

523

shop

19:10

19:25

(x,y)

523

home

19:40

(x,y)

Person ID    

Mode

Start

End

523

Public T.

08:55

523

Public T.

18:12

19:10

523

Walking

19:25

19:40

08:00

Île-de-France

RP

FiLoSoFi

RP Mob

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

BD-TOPO

OpenStreetMap
Road network

RP

OSM

FiLoSoFi

RP Mob

EGT

ENTD

IDFm GTFS
Public transport schedule

GTFS

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

Open
Data

Open
Software

+

=

Reproducible research

Verifiable results

Integrated testing

Example: Policy and scenario analysis

Demand synthesis

Mobility simulation

Home office

Shared offices

New mobility services

Emissions

Traffic

Time use

Equity

Cost-benefit analysis

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

Open
Data

Open
Software

+

=

Reproducible research

Verifiable results

Integrated testing

Current use cases

Nantes

  • Population synthesis
  • Noise modeling

    Contact: Valentin Le Besond

Current use cases

Lille

  • Park & ride applications
  • Road pricing

    Contact: Azise Diallo

Current use cases

Toulouse

  • Placement and use of shared offices

    Contact: Vincent Loubière

Current use cases

Rennes

  • Micromobility simulation

    Contact: Vincent Leblond

Paris / Île-de-France

  • Scenario development for sustainable urban transformation
     
  • New mobility services

    Contact:
    Mahdi Zargayouna (GRETTIA / Univ. Gustave Eiffel)
    Nicolas Coulombel (LVMT / ENPC)

Current use cases

Paris / Île-de-France

  • Cycling simulation

    Contact: Alexandre Chasse

Current use cases

IFP energies nouvelles

Current use cases

Paris / Île-de-France

  • Simulation of automated shuttles

    Contact: Sebastian Hörl

Current use cases - Worldwide

Sao Paulo (ETH Zurich)

 

San Francisco Bay area (ETH Zurich)

 

Los Angeles five-county area (ETH Zurich)

 

Switzerland (ETH Zurich)

 

Montreal, Quebec City, Jakarta, ...

Current use cases

Balac, M., Hörl, S. (2021) Synthetic population for the state of California based on open-data: examples of San Francisco Bay area and San Diego County, presented at 100th Annual Meeting of the Transportation Research Board, Washington, D.C.

Sallard, A., Balac, M., Hörl, S. (2021) Synthetic travel demand for the Greater São Paulo Metropolitan Region, based on open data, Under Review

Some challenges ...

  • Easy-to-use user interfaces
     
  • Use of dynamic data
    Road counts, GPS traces, ...
     
  • Automatic calibration

eqasim

An integrated pipeline from raw data to agent-based simulation:

  • Synthesis of travel demand
  • Agent-based simulation

eqasim - simulation using DMC

In cases when you have access to estimated MNL or NL models, these can now be integrated directly using the DMC extension

 

It can be used to override the scoring mechanism of MATSim

 

It is a default replanning mechanism in eqasim

Hörl, S., M. Balac and K.W. Axhausen (2018) A first look at bridging discrete choice modeling and agent-based microsimulation in MATSim, Procedia Computer Science, 130, 900-907.

Hörl, S., M. Balac and K.W. Axhausen (2019) Pairing discrete mode choice models and agent-based transport simulation with MATSim, paper presented at the 98th Annual Meeting of the Transportation Research Board, Washington D.C., January, 2019.

eqasim - simulation using DMC

Zurich - Simulation of automated vehicles, MaaS, AToD,...

Île-de-France

Final thoughts

Open
Data

Open
Software

+

=

Reproducible research

Verifiable results

Thank you!

Questions ?

Contact: balacm@ethz.ch and

sebastian.horl@irt-systemx.fr

Disaggregated transport analysis

0:00 - 8:00

08:30 - 17:00

17:30 - 0:00

0:00 - 9:00

10:00 - 17:30

17:45 - 21:00

22:00 - 0:00

  • Discrete locations
  • Individual travelers
  • Individual behaviour
  • Whole day analysis

Disaggregated

Icons on this and following slides: https://fontawesome.com

Even more data!

  • Since January 2021 opening up of most of the data of IGN
  • Detailed road network for all France
  • Detailed building footprints with height, utilisation, number of appartments, ...

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

Mobility simulation

Decision-making

Analysis

Scenario

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

RP

FiLoSoFi

RP Mob

EGT

ENTD

SIRENE

OSM

GTFS

Île-de-France

BD-TOPO

Introducing the eqasim pipeline: From raw data to agent-based transport simulation

By Sebastian Hörl

Introducing the eqasim pipeline: From raw data to agent-based transport simulation

ABMTRANS 2021, 25 March 2021

  • 249
Loading comments...

More from Sebastian Hörl