A model-based approach to select case sites for walkability audits.

Area of Science:

• Urban Planning
• Transportation Geography
• Environmental Psychology

Background:

• Walkability audits are crucial for understanding pedestrian environments but are resource-intensive.
• Existing methods for selecting audit sites lack efficiency and targeted precision.
• Identifying micro-level environmental factors influencing walkability is essential for urban design.

Purpose of the Study:

• To propose and demonstrate a model-based approach for selecting optimal sites for walkability audits.
• To identify meso-scale areas with under- and over-estimated travel behavior.
• To reveal micro-level environmental factors associated with travel behavior variations.

Main Methods:

• Developed a meso-scale travel behavior model to predict walk shares.
• Identified geographic areas where actual walk shares deviated from model predictions.
• Selected neighborhoods for walkability audits based on these deviations.
• Analyzed audit results to correlate local environmental elements with walk shares.

Main Results:

• The model-based approach successfully identified areas for targeted walkability audits.
• Systematic under- and over-estimation of walk shares indicated potential micro-level influencing factors.
• Local environmental features were found to associate with higher-than-expected walk shares.
• The strategy proved effective in optimizing resource allocation for audits.

Conclusions:

• A model-based site selection strategy enhances the efficiency and effectiveness of walkability audits.
• This approach provides valuable insights into micro-level factors influencing pedestrian travel behavior.
• Targeted audits guided by behavioral models can lead to more informed urban planning decisions.