Skip to content

Latest commit

 

History

History
129 lines (93 loc) · 6.58 KB

README.md

File metadata and controls

129 lines (93 loc) · 6.58 KB

Summary

This document serves as a guide for the execution of the simulations and the processing of results related to the thesis "Sustainability of Autonomous Vehicles: An Agent-based Simulation of the Private Passenger Sector" and paper "On The Impact of Replacing Private Cars with Autonomous Shuttles: An Agent-Based Approach".

Overview

In the submodule "submodule @7c28ca1" you find the version of the Open Berlin MATSim Scenario that we used as a baseline.

In the directory Data-Preparation you find the python scripts to process the original input files of the Open Berlin Scenario to generate input files that we used for our simulations.

The "input", RunBerlinScenario.java and RunDrtOpenBerlinScenario.java describe three files to adjust extracted from the OpenBerlinScenario

Overview of changes to input files that we made:

  • Update config (local files with scenario settings)

  • Update shape file (local files with extended DRT range)

  • Update vehicles file (local files with increased fleet size)

  • Update plans file (local files with car trips replaced by DRT trips)

  • Update network file (local file which replaces car links by DRT mode based on the scenario setting)

With the newly generated input files, the scenarios as outlined in the thesis can be run

Details about the machine used for the 10% scenarios

  • Operating System: Ubuntu 20.04.6 LTS
  • CPU: Intel (R) Core (TM) i9-10900K CPU @ 3.70 GHz
  • Memory size: 128 GiB

Prerequisites

  • Java and Eclipse (or similar IDE) openjdk 11.0.20.1 2023-08-24 // Eclipse Version: 2023-06 (4.28.0)

  • Python: Python 3.8.10

  • Python 3.8.10 Standard Packages

  • Python Packages Preprocessing

    • pandas==2.0.3
    • matplotlib==3.7.3
    • requests==2.22.0

  • Python Packages Postprocessing

    • pandas==2.0.3
    • matplotlib==3.7.3

  • Other Font "Times New Roman" Installed on machine for heatmap generation

Step-By-Step guide To run (default) MATSim simulations on your machine

Step-By-Step guide To reproduce our scenarios

  • Clone the Data Preparation directory

Plans files

  • Execute the "Plans_Demand_Forecast_Implementation.py" file to create the plans files that include travel demand increases
  • Run it 2 times in total: First set the forecast variable to "SC2", Second set the forecast variable to "SC3"
  • Next, execute the "Plans_Manipulation.py" file to create all SAV scenario plans files
  • Run it 3 times in total: First set the forecast variable to "SC1", Second set the forecast variable to "SC2", Third set the forecast variable to "SC3"
  • You have now succesfully created all required plans files!

Network files

  • Execute the "Network_Manipulation.py" file to create the three SAV-only network files used for all SAV scenarios

  • You have now succesfully created all required network files!

  • Clone the "Input" directory of this Git Repository and replace the "Input" directory in your matsim-berlin directory located at ./matsim-berlin/scenarios/berlin-v5.5-10pct/

Finalize Non SAV scenarios

  • Move to directory ./input
  • Copy&Paste the two plans files "berlin-v5.5-10pct_SC2.plans.xml.gz" and "berlin-v5.5-10pct_SC3.plans.xml.gz" into the /input directory to run the non-SAV scenarios

Finalize SAV scenarios

  • Move to directory ./input/drt
  • Update the directory in Line 171 of each config file by adding your filepath of the matsim-berlin clone (/ADJUSTACCORDINGTOYOURDIRECTORY/matsim-berlin/scenarios/berlin-v5.5-10pct/input/drt/SCX.X/berlin.shp)
  • Note: It has to be the entire directory path of where your cloned matsim-berlin directory is located to avoid errors
  • Move to each scenario directory (e.g. SC1.1)
  • As noted in each readme file per scenario directory (e.g. SC1.1), copy&paste the according network and plans files into these directorys
  • E.g., copy&paste "berlin-v5.5-network_SCX.1.xml.gz" and "berlin-v5.5-10pct_SC1_SCX.1.plans.xml" from the Input_Processed and Input_Processed/10pct directory to the input/drt/SC1.1 directory

Run Non SAV scenarios

  • Clone the RunBerlinScenario.java file of this Git Repository
  • Move to your local directory ./matsim-berlin/src/main/java/org/matsim/run and replace the RunBerlinScenario.java file
  • You can now run the Non SAV scenarios by running this java file through Eclipse after commenting out the specific scenario to run in lines 78ff

Run SAV scenarios

  • Clone the RunDrtOpenBerlinScenario.java file of this Git Repository
  • Move to your local directory ./matsim-berlin/src/main/java/org/matsim/run/drt and replace the RunDrtOpenBerlinScenario.java file
  • You can now run the SAV scenarios by running this java file through Eclipse after commenting out the specific scenario to run in lines 78ff

Run Testing Scenarios

  • Clone the Input_Additional_Analyses directory from this Git Repository and replace your local drt file (under .berlin-v5.5-1pct/input/) with the drt files from the cloned Input_Additional_Analyses directory
  • Add the plans file and network file as outlined in the readme within drt/SC1.3
  • You can now run the testing scenarios via the same RunDrtOpenBerlinScenario.java file as the 10pct version by chossing the specific config file in line 78ff

Results

  • Processed travel demand forecast and simulation results are documented in the directory results
  • Python files used for additional postprocessing (e.g., to reproduce heat maps) can be found in the Data_Postprocessing directory

Reference

Citation

If you found our work helpful, please cite it as follows:

@InProceedings{bogdoll2024impact,
      title={On The Impact of Replacing Private Cars with Autonomous Shuttles: An Agent-Based Approach}, 
      author={Daniel Bogdoll and Louis Karsch and Jennifer Amritzer and J. Marius Zöllner},
      year={2024},
      booktitle={IEEE Forum for Innovative Sustainable Transportation Systems (FISTS)}
}