Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Implement paper: "MOVI: A Model-Free Approach to Dynamic Fleet Management" #1

Open
sash-ko opened this issue Jan 22, 2020 · 7 comments
Labels

Comments

@sash-ko
Copy link
Owner

sash-ko commented Jan 22, 2020

MOVI, a Deep Q-network (DQN)-based framework that directly learns the optimal vehicle dispatch policy

MOVI: A Model-Free Approach to Dynamic Fleet Management

@yabirgb
Copy link
Contributor

yabirgb commented Jan 28, 2020

Is anyone working on this? I have a week free before the semester starts

@sash-ko
Copy link
Owner Author

sash-ko commented Jan 28, 2020

I already started working on it and going to use this repo for all machine learning related papers https://github.com/sash-ko/ai-transportation

@sash-ko
Copy link
Owner Author

sash-ko commented Jan 30, 2020

@yabirgb there is an interesting part is this paper - demand prediction with CNNs, it could be a topic on its own. A bit more details you can find in the technical report https://www.dropbox.com/s/ujqova12lnklgn5/dynamic-fleet-management-TR.pdf?dl=0

@yabirgb
Copy link
Contributor

yabirgb commented Jan 30, 2020

@yabirgb there is an interesting part is this paper - demand prediction with CNNs, it could be a topic on its own. A bit more details you can find in the technical report https://www.dropbox.com/s/ujqova12lnklgn5/dynamic-fleet-management-TR.pdf?dl=0

Ok I'm going to take a look, surely seems something interesting. Yesterday I finished the paper about T-share and I believe it has some ideas that can be mixed or used in the MOVI design although I need to reread it.

@yabirgb
Copy link
Contributor

yabirgb commented Feb 4, 2020

@sash-ko I'm playing around the topic of demand prediction using images and found this papers that might be interesting https://arxiv.org/pdf/1911.03441.pdf and https://arxiv.org/abs/1701.04245 (Yesterday I was trying to learn pytorch that is new for me)

@sash-ko
Copy link
Owner Author

sash-ko commented Feb 4, 2020

In MOVI paper there is only a small chapter about CNNs for demand prediction

@yabirgb
Copy link
Contributor

yabirgb commented Feb 12, 2020

In MOVI paper there is only a small chapter about CNNs for demand prediction

I implemented the demand prediction as the paper mentions plus other variations that I made. Currently I'm training and comparing the models using the data from https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page converting PULocation and DOLocation to a coordinate inside the region. I'll prepare a document with the comparison.

Moreover I'm implementing the model from https://arxiv.org/pdf/1911.03441.pdf to compare it too

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

No branches or pull requests

2 participants