Identifying the Departure City

Requirements Clarification & Assessment

In this section, we aim to clarify the problem and assess the requirements needed to accurately identify the departure city of Uber rides originating from two neighboring cities, Menlo Park and Palo Alto.

1. Understanding the Problem

   • Objective: Determine the city of origin for each Uber ride.
   • Constraints: The cities are geographically close, making it challenging to distinguish based solely on proximity.
   • Assumptions: Assume access to any conceivable data except direct location data (e.g., GPS, latitude-longitude).

2. Data Requirements

   • Ride Information: Collect data such as trip start time, duration, cost, destination, and driver ID.
   • User Data: Gather information on user profiles, including home/work addresses and ride history.
   • City Boundaries: Understand the geographical boundaries of Menlo Park and Palo Alto for contextual reference.

3. Challenges

   • Data Overlap: Due to proximity, ride data may overlap, complicating city identification.
   • Data Availability: Limited access to direct location data necessitates alternative data sources.

4. Success Criteria

   • Accurately classify the origin city for a significant majority of rides.
   • Implement a solution that is scalable and adaptable to similar scenarios.