Travel Time Prediction for Indian Metro Cities using Open Datasets

Ujaval Gandhi (~spatialthoughts)


6

Votes

Description:

Abstract

In this talk, we will demonstrate how two large open datasets - Uber Movement and OpenStreetMap (OSM) - can be used to develop a pretty robust travel time predictor for urban travel. The foundation of our model is the anonymized and aggregated taxi trip data shared by Uber through their Uber Movement platform. This is a large dataset which has both spatial and temporal components to it. We combine this dataset with OpenStreetMap road network and routing data to build a model of travel time that accounts for travel distance, hour-of-the-day and historic traffic. We will demonstrate the process and show a live demo of the model in action.

We will introduce modern geospatial libraries such as geopandas, shapely, folium and services such as Open Source Routing Machine and OpenRouteService that make working with large spatio-temporal datasets easy. Come and learn about how you can use these open datasets and learn about incorporating spatial datasets in your data science workflows.

Talk Outline

We will discuss some background info and our motivation, followed by a walk-through of our code.

  • Motivation [3 minutes]
  • Background [5 minutes]
    • Overview of OpenStreetMap
    • Overview of Uber Movement
  • Working with Geospatial Data [10 minutes]
    • Data Processing and Analysis
    • Network Analysis and Routing
    • Visualization
  • Machine Learning with Geospatial Data [5 minutes]
  • Future plans and next steps [2 minutes]
  • Q & A [ 5 minutes]

Prerequisites:

Basic knowledge of Python. Familiarity with data science workflows is preferred.

Speaker Info:

Ujaval Gandhi

Ujaval is the founder of Spatial Thoughts - a learning platform for modern geospatial technologies. He got his Masters in Geospatial Information Engineering from University of Wisconsin-Madison. After joining Google Inc. in California, he moved to India in 2006. He was one of the early employees at Google India and part of the team that launched Google Maps for India. He has worked on multiple Geo teams at Google and led the aerial imagery group in India. He was the lead trainer for Google Earth Engine in India and conducted numerous training sessions across the country.

Ujaval’s interest and expertise is using open-source spatial analysis software to automate GIS and Remote Sensing workflows. He is a world-renowned GIS expert and training facilitator who is passionate about advancing the use of open-source technologies in teaching and research. He is also a visiting faculty/researcher at University of Johannesburg, South Africa.


Vishnu Prasad JS

Vishnu is a MBA student at School of Management Studies, NIT Calicut. His specialization is in data analytics and finance. He is currently a research intern at Spatial Thoughts.

Speaker Links:

Ujaval Gandhi is accomplished public speaker and a keen follower of geospatial industry. He has been invited for talks, lectures and panel discussions at various industry and academic events. See his recent talks and videos

He is an active contributor to the QGIS open-source project and writes widely used CC-licensed tutorials. He also publishes OpenCourseWare for Python and Spatial Analysis

Section: Scientific Computing
Type: Talks
Target Audience: Beginner
Last Updated: