NYC Traffic & Road Infrastructure Analysis
CIS 9440 - Data Warehousing & Analytics | Group 3
NYC Traffic & Road Infrastructure Analysis
Investigating the relationship between traffic density and road infrastructure degradation across New York City's five boroughs (2020-2025).
Introduction
New York City’s road infrastructure handles some of the highest traffic volumes in the United States. When roads degrade, potholes form, traffic signals fail, street lights go dark, and the burden falls on residents, delivery networks, and emergency services alike. Yet maintenance resources are finite, and response times vary widely across boroughs.
This project builds a data warehouse that integrates two NYC Open Data sources to investigate whether traffic volume is a meaningful predictor of infrastructure complaints, and whether boroughs with higher traffic also experience slower repair response times.
Analytics Questions
Q1: Does traffic volume correlate with complaint frequency?
To what extent does high traffic volume (specifically heavy vehicle counts) correlate with the frequency of “Street Condition,” “Street Light Condition,” and related 311 complaints?
Q2: Does response time vary across boroughs?
How does agency response time for road repairs vary between high-traffic zones and low-traffic zones? Is there a measurable “maintenance lag” in high-traffic areas?
Key Metrics / KPIs
| KPI | Description |
|---|---|
| Pothole Incidence Rate (PIR) | Total “Street Condition” complaints ÷ avg daily traffic volume per segment |
| Traffic-to-Repair Correlation (T2R) | Do higher traffic volumes go with faster or slower resolution? Computed at the borough level (five data points), so it is a descriptive comparison, not a statistical test |
| Peak-Load Service Lag | Avg days-to-close in peak traffic months vs. non-peak months, where “peak” means the counted street segments were busier than their own average |
Data Sources
| Source | Description | Link |
|---|---|---|
| NYC 311 Service Requests | Community-reported road/infrastructure issues, filtered to street-related complaint types, 2020-2025 | NYC Open Data |
| DOT Automatic Traffic Volume Counts | 15-minute interval automated traffic counts at DOT sensor locations, 2020-2025 | NYC Open Data |
Potential Stakeholders
- NYC Department of Transportation (DOT): prioritize preventive maintenance on high-traffic / low-complaint roads before failure occurs.
- Logistics & Delivery Companies: identify high-incident routes that increase vehicle maintenance costs or delivery delays.
- Urban Planners: assess whether current road materials are sufficient for the actual traffic load detected by sensors.
Project Summary
Group Members
| Name | Role | Links |
|---|---|---|
| Bridgette Wang | Detail Manager | GitHub · 📫 Email |
| Paven Oommen | Communicator | GitHub · 📫 Email |
| Sung Ik Park | Technician | GitHub · 📫 Email |
| Zesen Chen | Technician | GitHub · 📫 Email |
| Raúl J. Solá Navarro | Facilitator | GitHub · 📫 Email |