Simulation scenarios for automated mobility

Static vs. dynamic demand

Sebastian Hörl

SystemX

5 Feb 2019, Paris

The street in 1900

http://www.loc.gov/pictures/item/2016800172/

The street today

https://commons.wikimedia.org/wiki/File:Atlanta_75.85.jpg

The street of tomorrow?

  • Autonomous Mobility

  • Mobility as a Service

  • Mobility on Demand

  • Electrification

  • Aerial Mobility

Julius Bär / Farner

I. MATSim

Mesoscopic Transport Simulation

Senozon VIA

https://pixabay.com/en/traffic-jam-stop-and-go-rush-hour-143391/

MATSim

Home

Work

Shop

Home

until 8am

9am to 6pm

6:15m to 6:30pm

from 6:45pm

walk

public

transport

walk

MATSim

Network simulation

Scoring of the plans

Selection and modification

Scenario

MATSim with Discrete Choice Model

Network simulation

Scoring

Replanning

Network simulation

Choice Model

* Hörl, S., M. Balac, K.W. Axhausen (2018) Pairing discrete mode choice models and agent-based transport simulation with MATSim, presented at the Annual Meeting of the Transport Research Board 2019

https://pixabay.com/en/zurich-historic-center-churches-933732/

II. AMoD in Zurich

Fleet control

* Hörl, S., C. Ruch, F. Becker, E. Frazzoli, and K.W. Axhausen (2019) Fleet operational policies for automated mobility: a simulation assessment for Zurich, Under Review.

Fleet control

Load-balancing heuristic

Simple heuristic, fast runtime

 

Gloal Euclidean Bipartite Matching

Standard algorithm in OR

 

Feedforward Fluidic Optimal Rebalancing Policy

Linear program matching a priori known trip rates

 

Adaptive Uniform Rebalancing Policy

Linear program distributing vehicles equally

Fleet control

Fleet sizing with dynamic demand

Fleet sizing with dynamic demand

Fleet sizing with dynamic demand

Autonomous vehicles?

Cost structures?

User preferences?

System impact?

1. AV Cost Calculator

2. Stated preference survey

3. MATSim simulation

AMoD Cost Calculator

Bösch, P.M., F. Becker, H. Becker and K.W. Axhausen (2018) Cost-based analysis of autonomous mobility services, Transport Policy, 64, 76-91

AMoD Survey

Felix Becker, Institute for Transport Planning and Systems, ETH Zurich.

Model integration

Results

Work in progress ...

Spatial constraints

Operational constraints

Intermodality

https://commons.wikimedia.org/wiki/File:Zeichen_365-65_-_Ladestation_f%C3%BCr_Elektrofahrzeuge,_StVO_2014.svg

https://www.flickr.com/photos/viriyincy/4528290409

https://de.wikipedia.org/wiki/Datei:Zeichen_316_-_Parken_und_Reisen,_StVO_1992.svg

III. Paris Scenario

https://pixabay.com/en/paris-eiffel-tower-night-city-view-3296269/

Sociodemographics

Activity Chains

Locations

MATSim

Census data, FILOSOFI

Enquête globale de transport (HTS)

- OD from census data

- Specifically designed sampling algorithm

Paris Transport Scenario - Demand side

Paris Transport Scenario - Demand side

Paris Transport Scenario - Demand side

Paris Transport Scenario - Demand side

Paris Transport Scenario - Demand side

Road network

Public Transport

Locations

MATSim

OpenStreetMap

GTFS from IDFm

Paris Transport Scenario - Supply side

Paris transport scenario - Supply side

Paris transport scenario - Supply side

Paris transport scenario - Supply side

Traffic counts

Paris transport scenario - Simulation

Paris transport scenario - Simulation

Paris transport scenario - Simulation

IV. Case study

AMoD in Paris

* Hörl, S., M. Balac, and K.W. Axhausen (2019) Dynamic demand estimation for an AMoD system in Paris, Upcoming.

AMoD in Paris

Travel Behaviour

Zurich model, calibrated for Paris population

AMoD Cost

Costs for Berlin

Fleet control

Heuristic algorithm

AMoD in Paris

Maximum static demand: 2.3M trips

AMoD in Paris

Maximum static demand: 2.3M trips

AMoD in Paris

Potential studies

  • Financial aspects: Profits, subsidies
     
  • Dispatching algorithms under customer behaviour
     
  • Sensible scenario diameters
     
  • Interaction with land use
     
  • Emissions

Final remarks

Thanks!

Questions?

Contact: sebastian.hoerl@ivt.baug.ethz.ch

Simulation scenarios for automated mobility

By Sebastian Hörl

Simulation scenarios for automated mobility

SystemX, Paris, 5 Feb 2019

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