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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
```bash
pip install -r requirements.txt
python app.py
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