Presenter: Rick Manuel Woubinwou Djouwe

Faculty Sponsor: Nada Al Sallami

School: Worcester State University

Research Area: Computer Science

Session: Poster Session 2, 11:30 AM - 12:15 PM, 163, C20

ABSTRACT

Efficient parking allocation remains a persistent challenge on university campuses, particularly during peak arrival periods when students must search repeatedly for available spaces. This study presents the design and evaluation of a risk-aware parking lot recommendation system modeled for a smart campus environment. The system dynamically simulates parking lot occupancy based on time-of-day arrival and departure patterns and recommends optimal lots according to a selected destination building.

Two allocation algorithms are implemented and compared: a greedy closest-distance approach and a weighted risk-aware selection algorithm. The greedy algorithm prioritizes minimal walking distance to the destination building, while the weighted algorithm incorporates both walking distance and a probabilistic estimate of lot saturation to reduce the likelihood of arriving at a full lot. Each algorithm ranks available parking lots using a cost function and returns the top recommendations in real time.

Experimental evaluation examines computational performance, average walking distance, and sensitivity to risk weighting under varying congestion conditions. Results demonstrate that while the greedy strategy minimizes walking distance, the risk-aware algorithm provides more balanced recommendations during peak hours by reducing exposure to high-occupancy lots.

This work illustrates how algorithmic decision strategies can improve campus parking efficiency and highlights the practical role of cost-based optimization in smart infrastructure systems.