Philadelphia Smart Loading Zones: Analysis and Demand Prediction

LING CHEN

Planning & Urban Design

R Reimaging the City of Squares

Philadelphia Smart Loading Zones: Analysis and Demand Prediction

Jan 2024 - May 2024

A Data-Driven Planning Framework for Curbside Loading Zones.

The pilot generated data about individual vehicles parking in each zone. The increase in home delivery and on-demand logistics has created a need for new tools to decongest the right-of-way. Our project explores the potential of opening new smart loading zones in the city. Using pilot data, we created a predictive model that can be used to estimate demand at new locations.

Through an iterative process, our team has meticulously crafted a high-performing model leveraging a wealth of data provided by the client regarding bookings made through the Smart Loading Zones app. Additionally, we have integrated external data sources such as OpenStreetMap and census data to enrich our model’s insights and accuracy. This iterative approach has allowed us to continuously refine and enhance our model, ensuring that it effectively predicts and optimizes Smart Loading Zone demand.

Type: Smart CitiesPracticum with the city of Philadelphia
Role: Group Work with Samriddhi Khare, Michael Dunst, Tiffany Luo, Shengqian Wang
Location: Philadelphia
Date: January, 2024 - May, 2024

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