Pedestrian Environment Index (PEI) Implementation
This project implements the Pedestrian Environment Index (PEI) methodology as developed at the University of Illinois Chicago (see the research paper: https://www.sciencedirect.com/science/article/pii/S0966692314001343). The PEI provides a composite measure of the walkability of an environment, incorporating the following subindices:
- Population Density Index (PDI)
- Commercial Density Index (CDI)
- Intersection Density Index (IDI)
- Land-use Diversity Index (LDI)
Team
| Name | Seniority | Major | Department | GitHub Handle | Topic Area |
|---|---|---|---|---|---|
| Yilun Zha | PhD | Planning/Urban Design | ARCH | elonncha | Mobility-PEI |
| C. "Albert" Le | Sophomore | Computer Engineering | ECE | balbertle | Mobility-PEI |
| Chunlan Wang | Masters | Architecture (DC) | ARCH | wang-123-xi | Mobility-PEI |
| Yichao Shi | PhD | Architecture | ARCH | SHIyichao98 | Mobility-PEI |
| Atharva Beesen | Junior | Computer Science | COC | AtharvaBeesen | Mobility-PEI |
Motivation
Understanding the walkability of an environment is important for urban planning, public health initiatives, and promoting active transportation. This implementation of the PEI can be used by researchers to:
- Assess the current walkability of neighborhoods or regions
- Compare walkability across different areas
- Identify areas with potential for improvement
Getting Started
- Prerequisites:
- Python 3.x
- Libraries: * osmnx * pandas * numpy * matplotlib.pyplot * csv * census
- Census API Key: Can be found at: https://api.census.gov/data/key_signup.html. Must paste key in text file titled census_api_key.txt in the same directory as PDI_generator.ipynb to access population data.
Installation
You can install the required libraries using pip:
- Usage:
Contributing
License
Idk how licensing works... Just don't sell it I guess.