README.md

metadata

title: Uber Driver Recommendation System
emoji: 🚖
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.31.0
python_version: '3.10'
app_file: app.py
pinned: false

🚖 Uber Driver Recommendation System

An intelligent, lightweight ML-powered recommendation system that suggests the best ride options for drivers by optimizing earnings, efficiency, and ride quality.

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🎯 Overview

This project simulates a real-world ride allocation system (like Uber/Ola) where multiple ride requests are ranked and recommended to drivers using a machine learning model.

The system focuses on:

• Maximizing driver earnings 💰
• Minimizing idle time ⏱️
• Improving ride efficiency 🚗

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🧠 How It Works

1. Synthetic ride data is generated
2. Feature engineering calculates efficiency metrics
3. A Random Forest model predicts a reward score
4. Ride options are ranked based on score
5. Top recommendations are displayed with explanations

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⚙️ Features

• ✅ ML-based ride scoring engine
• ✅ Real-time recommendation simulation
• ✅ Explainable AI ("Why this ride?")
• ✅ Clean and minimal Gradio UI
• ✅ Fast and lightweight (HF Spaces ready)

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📊 Input Parameters

• Pickup Distance (km)
• Trip Distance (km)
• Fare (₹)
• Surge Multiplier

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📤 Output

• Top 3 recommended rides
• AI-generated score
• Key reasons (high fare, low pickup, surge, etc.)

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🚀 Run Locally

pip install -r requirements.txt
python app.py