A Simplified RideSharing Application
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Updated
May 25, 2024 - Python
A Simplified RideSharing Application
Charging station planning for ride-sourcing EVs
Gym environments for logistics tasks that can be described as "Move something from A to B"
Multi-objective dynamic traffic assignment for social optimal shared autonomous vehicles
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling implemented in PyTorch.
Dynamically adjust cost of the rides in response to changing factors
Data Analysis using Unsupervised Learning on Lyft dataset
Ride-Sharing application involves building several components such as user authentication, ride management, driver and passenger matching, real-time tracking, and payment processing.
Manages ride-sharing amongst friends through an automated texting service. Built to support a couple of poor grad students without cars.
A scalable, distributed, fault-tolerant, highly-available, containerized and micro-services based ridesharing service deployed on AWS EC2
Bike pooling app(Django)
Autonomous Mobility-on-Demand Simulation
This project evaluates ride-sharing algorithms on spatio-temporal data. The data in this case represents nearly 700 million trips in New York City.
Code for ridesharing paper @ WWW 2018.
simobility - light-weight mobility simulation framework. Best for quick prototyping
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