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Applied algorithms project · 2024-12-05

Real-Time Parking Optimization System

Implemented and explored parking allocation, routing, and dynamic-pricing algorithms in a simulated urban setting.

Role
Project developer
Contribution
Implemented and explored parking allocation, routing, and dynamic-pricing algorithms in a simulated urban setting.
Evidence
View public source ↗

Problem

Parking allocation involves competing constraints: limited capacity, changing demand, travel distance, and pricing. This project explores those tradeoffs in a simulated setting.

Approach

I implemented algorithms for allocation and routing alongside dynamic-pricing experiments. The project includes visualizations for examining the simulated parking network and comparing algorithm behavior.

Evaluation

The public source provides the implementation and experiment context. The supplied interactive map allows inspection of the modeled environment.

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Outcome

The project connects algorithm selection, simulation, and visual analysis in an inspectable application.

Limitations

Simulation results do not demonstrate measured revenue gains, reduced congestion, or production use by a city. Results depend on the assumptions and inputs used in the project.