An efficient way to merge taxi trips.
We developed a Taxi Ride-Sharing system for a part of New York City. This system accepts passengers’ real-time ride requests and schedules taxis to pick them up via ride-sharing keeping in mind constraints with respect to time, taxi capacity and money. The entire objective behind this project is to devise an efficient ride-sharing algorithm that will be beneficial to both the customer requesting for a ride and the Taxi company (or the driver of the Taxi). Post ride-sharing, the customer will not pay more compared to a ride without sharing and compensation due to lengthened travel time and money for short distances will be made up for. Our algorithm focuses on single source – multiple destination combinations. Our single source point is Barclay’s center in Brooklyn, NYC.
Dependencies to run the project:
- Python version 3.0 or higher.
- Jupyter Notebook.
Install and Run instructions:
- Clone the repository as zip.
- Unzip the files in a folder.
- Download all the files from google drive link: https://drive.google.com/drive/folders/0Bx-5mrdb_G2KZnJCdm1lVkNoRGs?usp=sharing
- COpy the downloaed files and folders to Repository Folder
- Open cmd and navigate to the project folder.
- Run the following command: java -jar graphhopper-web-0.6.0-with-dep.jar jetty.resourcebase=webapp config=config-example.properties osmreader.osm=new-york- latest.osm.pbf
- Install Jupyter Notebook and open the project folder in localhost.
- Run the project step by step using Jupyter on 2 files (in order): Import.ipynb Apply.ipynb