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ASPIRES: Airport Shuttle Planning and Improved Routing Event-driven Simulation

Contributors:

Qichao Wang Qichao.Wang@nrel.gov
Devon Sigler Devon.Sigler@nrel.gov
Andrew Kotz Andrew.Kotz@nrel.gov
Zhaocai Liu Zhaocai.Liu@nrel.gov
Kenneth Kelly Kenneth.Kelly@nrel.gov
Caleb Phillips Caleb.Phillips@nrel.gov

Publication

This work will be presented at 2020 TRB Workshop on Traffic Simulation and CAV Modeling.

Purpose

To fast simulate airport shuttle operations with the data collected. The simulation inputs are passenger arrival rates, shuttle routes and frequencies, and simulation configurations. The outputs include: time dependent shuttle energy level, time dependent charging station usage, time dependent number of passengers on each bus, time dependent number of passengers at each bus stop, history of number of passengers left at each bus stop, route history of fleet shuttle buses and on-demand buses, and time dependent bus distance traveled.

This repo contains the following items

  • Core code for the software
    • DES_shuttle.py
    • environment.yml
  • Input data
    • data/
    • /data_2020/arrRate.pickle: the estimated arrival rate of passengers at each shuttle bus stop.
    • /data_2020/Time_n_Energy_Dictionary_Nested_Full: the time and energy cost of each link between two nodes from bus logger data
    • /data_2020/Time_n_Energy_Dictionary_Nested_Full_p: the time and energy cost of each link between two nodes from combined bus logger data and simulation data
    • /data_2020/FleetSize_MixedRoute/: the estimated hourly number of buses needed for each route for each day
    • /data_2020/SPOT/: folder to put the SPOT data
  • Exapmle scripts to run simulation
    • On HPC: Asim.slurm
  • Exaplme outputs:
    • Asim.log.log
    • result_baseline.pckl

Installation instructions

1. Clone this repo

In terminal, type

git clone https://github.com/NREL/ATHENA-aspires.git

2. Setup conda environment

Go to the repo

cd ATHENA-aspires

Then create the environment

conda env create --file environment.yml

Activate the environment

conda activate ASPIRES

3. Run the simulation

The simulation command includes several optional parameters. The code is in DES_shuttle.py. One example is First go to the directory that has DES_shuttle

cd <path to ATHENA-aspires>

Then type the following command

python DES_shuttle.py --StartingDayOfWeek 1 --SimTime 8 --doHotShot True --outputName baseline --maxqueue 150

Asim.slurm is the script to run ASPIRES on HPC.

4. Update data (Optional)

  • When new SPOT data is available, put the SPOT data csv files into /data_2020/SPOT/. Then remove /data_2020/arrRate.pickle.
  • When new simulation data from SUMO is available, name the simulated data as SUMO_AverageDayBusOutput.csv, place it under /data_2020/, and remove /data_2020/Time_n_Energy_Dictionary_Nested_Full_p.npy.
  • The optimized route data can be found on eagle under this path: /projects/athena/bus_opt/bus_opt_csvs/.

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