This research competition offers both monetary prizes and academic recognition for top performers.

### Total Prize Pool: $100 USD

#### 🥇 First Place - $50
- Cash prize
- Featured solution presentation
- Co-authorship opportunity on research writeup
- Citation rights in future publications
- Recognition on competition website

#### 🥈 Second Place - $30
- Cash prize
- Co-authorship opportunity on research writeup
- Citation rights in future publications
- Recognition on competition website

#### 🥉 Third Place - $20
- Cash prize
- Citation rights in future publications
- Recognition on competition website

### Winner Requirements

All prize winners must:

1. **Share their solution**: Provide well-documented source code and methodology
2. **Reproducible results**: Include instructions to reproduce your predictions
3. **Documentation**: Write a clear explanation of your approach
4. **Open source**: Release winning solution under an OSI-approved license (MIT recommended)
5. **Compliance**: Follow all competition rules and eligibility requirements

See the **Rules** page for complete details on winner obligations.

### Academic Recognition

Beyond monetary prizes, winners will:
- Be acknowledged in any publications resulting from this competition
- Have the opportunity to co-author research papers about the competition
- Have their solutions featured in the competition writeup

### Timeline

- **Winners Announcement**: 14 days after competition close
- **Code Submission Deadline**: 14 days after winner notification
- **Prize Distribution**: After code verification and compliance review

### Eligibility

This competition is open worldwide to individuals and teams (max 5 members). See the **Rules** page for complete eligibility requirements.

**Note**: Winners are responsible for any applicable taxes on prizes.

### Recognition Over Rewards

While the monetary prizes are modest, this competition offers valuable:
- Academic recognition and publication opportunities
- Portfolio material showcasing your machine learning skills
- Contribution to traffic safety research with real-world impact
- Networking with data science and transportation safety communities

The primary goal is advancing research in traffic safety through collaborative data science. Top solutions will help inform the development of real-world driver assistance systems that could save lives.