simobility

A human-friendly Python framework that helps scientists and engineers to prototype and compare fleet optimization algorithms (autonomous and human-driven vehicles).
https://github.com/sash-ko/simobility

Category: Consumption
Sub Category: Mobility and Transportation

Keywords

autonomous-vehicles fleet-management mobility mobility-modeling optimization-algorithms python ridehailing ridesharing simulation-framework simulator transportation

Last synced: about 2 hours ago
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Repository metadata

simobility - light-weight mobility simulation framework. Best for quick prototyping

Host: GitHub
URL: https://github.com/sash-ko/simobility
Owner: sash-ko
License: mit
Created: 2020-01-22T18:23:34.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2020-12-29T14:07:50.000Z (over 4 years ago)
Last Synced: 2025-04-10T04:00:46.717Z (17 days ago)
Topics: autonomous-vehicles, fleet-management, mobility, mobility-modeling, optimization-algorithms, python, ridehailing, ridesharing, simulation-framework, simulator, transportation
Language: Python
Size: 126 MB
Stars: 42
Watchers: 3
Forks: 9
Open Issues: 6
Releases: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

README.md

simobility

simobility is a light-weight mobility simulation framework. Best for quick prototyping

simobility is a human-friendly Python framework that helps scientists and engineers to prototype and compare fleet optimization algorithms (autonomous and human-driven vehicles). It provides a set of building blocks that can be used to design different simulation scenarious, run simulations and calculate metrics. It is easy to plug in custom demand models, customer behavior models, fleet types, spatio-temporal models (for example, use OSRM for routing vehicles and machine learning models trained on historical data to predict ETA).

Motivation

Create an environment for experiments with machine learning algorithms for decision-making problems in mobility services and compare them to classical solutions.

Some examples:

Installation

pip install simobility

Contributions and thanks

Thanks to all who contributed to the concept/code:

Examples

Grid world simulation

Simple simulation

Taxi service

Log example

Benchmarks

Benchmark simulations with LinearRouter and GreedyMatcher. Simulations will run slower with OSRMRouter because OSRM cannot process requests as fast as the linear router.

Processor: 2,3 GHz Dual-Core Intel Core i5; Memory: 8 GB 2133 MHz LPDDR3

Simulated time	Simulation step	Vehicles	Bookings per hour	Execution time	Generated events	Pickup rate
1 hour	10 sec	50	100	4 sec	1082	96.97%
24 hours	1 min	50	100	12 sec	23745	88.37%
24 hours	10 sec	50	100	20 sec	23880	88.84%
12 hours	10 sec	200	100	18 sec	13337	99.89%
12 hours	10 sec	50	500	31 sec	40954	53.92%
12 hours	10 sec	200	500	46 sec	65444	99.3%
12 hours	10 sec	1000	500	1 min 48 sec	66605	99.98%
1 hour	1 min	1000	1000	14 sec	11486
1 hour	10 sec	1000	1000	18 sec	11631
24 hours	1 min	1000	1000	5 min 1 sec	262384
24 hours	10 sec	1000	1000	6 min 20 sec	262524

A heuristic that allows estimating a maximum number of booking a fleet of N vehicles can handle: assume that an avarage trip duration is 15 minute, than 1 vehicle can not more then handle 4 booking per hour and the upper limit for 1000 vehicles is 4000 bookings per hour.

Metrics example

{
    "avg_paid_utilization": 63.98,
    "avg_utilization": 96.87,
    "avg_waiting_time": 292.92,
    "created": 3998,
    "dropoffs": 589,
    "empty_distance": 640.37,
    "empty_distance_pcnt": 33.67,
    "fleet_paid_utilization": 63.98,
    "fleet_utilization": 96.87,
    "num_vehicles": 50,
    "pickup_rate": 15.48,
    "pickups": 619,
    "total_distance": 1902.04,
}

Simulation logs

The are multiple ways to collect simulation log - use CSV or InMemory log handler or implement your own handler: loggers

Read CSV logs with pandas:

import pandas as pd

data = pd.read_csv(
    "simulation_output.csv",
    sep=";",
    converters={"details": lambda v: eval(v)},
)

details = data.details.apply(pd.Series)

Run OSRM

wget http://download.geofabrik.de/north-america/us/new-york-latest.osm.pbf
docker run -t -v "${PWD}:/data" osrm/osrm-backend osrm-extract -p /opt/car.lua /data/new-york-latest.osm.pbf
docker run -t -v "${PWD}:/data" osrm/osrm-backend osrm-partition /data/new-york-latest.osrm
docker run -t -v "${PWD}:/data" osrm/osrm-backend osrm-customize /data/new-york-latest.osrm
docker run -d -t -i -p 5010:5000 -v "${PWD}:/data" osrm/osrm-backend osrm-routed --algorithm mld /data/new-york-latest.osrm

Owner metadata

Name: Oleksandr Lysenko
Login: sash-ko
Email:
Kind: user
Description:
Website: http://twitter.com/sash_ko
Location: Berlin
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/220472?u=409a076d99b51c5af3bc40b6103a82006cdffe70&v=4
Repositories: 23
Last ynced at: 2024-06-11T15:44:55.071Z
Profile URL: https://github.com/sash-ko

GitHub Events

Total

Watch event: 3

Last Year

Watch event: 3

Committers metadata

Last synced: 6 days ago

Total Commits: 231
Total Committers: 2
Avg Commits per committer: 115.5
Development Distribution Score (DDS): 0.009

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name	Email	Commits
Oleksandr Lysenko	s**o@g**m	229
Yabir G	y**b@g**m	2

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 7
Total pull requests: 4
Average time to close issues: about 1 month
Average time to close pull requests: about 3 hours
Total issue authors: 3
Total pull request authors: 2
Average comments per issue: 1.71
Average comments per pull request: 0.0
Merged pull request: 4
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/sash-ko/simobility

Top Issue Authors

sash-ko (5)
Xiaobing-Shen (1)
lijiawei20161002 (1)

Top Pull Request Authors

sash-ko (3)
yabirgb (1)

Top Issue Labels

research (2)

Top Pull Request Labels

Package metadata

Total packages: 1
Total downloads:
- pypi: 72 last-month
Total dependent packages: 0
Total dependent repositories: 1
Total versions: 3
Total maintainers: 1

pypi.org: simobility

Lightweight mobility simulation for quick algorithm prototyping

Homepage: https://github.com/sash-ko/simobility
Documentation: https://simobility.readthedocs.io/
Licenses: MIT
Latest release: 0.3.0 (published about 5 years ago)
Last Synced: 2025-04-26T12:01:43.605Z (1 day ago)
Versions: 3
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 72 Last month
Rankings:
- Dependent packages count: 7.373%
- Stargazers count: 10.781%
- Forks count: 11.468%
- Dependent repos count: 22.233%
- Average: 26.432%
- Downloads: 80.304%
Maintainers (1)
- sashkolysenko

Score: 8.868413284672007

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simobility

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Repository metadata

README.md

simobility

Motivation

Installation

Contributions and thanks

Examples

Benchmarks

Metrics example

Simulation logs

Run OSRM

Owner metadata

GitHub Events

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Last Year

Committers metadata

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Issue and Pull Request metadata

Top Issue Authors

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Top Pull Request Labels

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pypi.org: simobility