Authors

Jiehang Yu, Jinyi Peng, Tianyu Lang

Research Question

How can school bus routes for children with special needs in New York City be optimized to improve efficiency, punctuality, and equity, while meeting operational constraints such as maximum ride times and on-time arrival requirements?

Background

The ROUTES Capstone project analyzes and optimizes school bus routes for children with special needs in New York City. Using NYC Open Data and historic routing data, current routes are examined to identify inefficiencies and propose realistic improvements. Key Performance Indicators (KPIs) will be developed to assess aspects such as punctuality, efficiency, and social equity. The project entails designing a routing algorithm that meets strict time and operational constraints.

Methodology

Students are receiving guidance from NYCSBUS Head of Data Science to create synthetic routes based on historic vehicle activity, while using NYC Open Data for school locations and additional relevant datasets. The aim is to explore how current routes operate, identify inefficiencies, and propose realistic improvements.

Based on this analysis, a set of Key Performance Indicators (KPIs) are proposed to evaluate route quality. These KPIs reflect meaningful aspects such as punctuality, efficiency, environmental impact, or social equity. Students define and justify their own metrics, grounded in data and real-world context.

The second objective is to design a routing strategy that can generate optimized routes. This algorithm respects core requirements: students must arrive on time (e.g., before school breakfast) and that no child should spend more than 90 - 105 minutes on the bus. Additionally, the project considers other realistic constraints such as traffic conditions, vehicle limits, or neighborhood restrictions.

Finally, this project includes the production of clear visualizations to compare current and optimized routes, highlight KPIs, and show potential social impacts on stakeholders such as students, parents, and school staff.

Historically school bus routes in NYC are planned top-down and assigned to private companies to operate. This capstone project aims to explore school bus historical routing data to assess the social impacts of the optimization of the school bus service. Relying on real world data, the students will provide a practical solution to plan alternative routing and maximizing social benefits for children with special needs.

Deliverables

• Research report
• Routing algorithm
• Interactive data visualization

Data Sources

1. Distributions of pickups to help with designing realistic school bus routes in NYC (NYCSBUS)
2. Obfuscated route data cleaned from students' PPI (NYCSBUS)
3. NYC Open Data