Parking Space Allocation Strategy Optimization during Planned Special Events

Master thesis (2023)

Authors

Y. Wang Civil Engineering & Geosciences

Contributors

M. Rinaldi Transport and Planning - CEG (supervisor 1)
Gonçalo Correia Transport and Planning - CEG (supervisor 2)
V.L. Knoop Transport and Planning - CEG (supervisor 2)
E. Arslan Transport and Planning - CEG (supervisor 2)
Faculty
Civil Engineering & Geosciences
Copyright: © 2023 Yunyun Wang
More Info
expand_more

Published Date

25-07-2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Abstract

This project aims to relieve traffic pressure and enhance the parking experience for attendees during planned special events (PSEs). The objective is to develop an optimal strategy for efficiently allocating parking spaces during PSEs in parking lots.

PSEs, such as football games or large concerts, typically result in concentrated vehicle arrivals within a limited time period, leading to increased traffic flow, potential disruptions, elevated emissions, and safety concerns in nearby areas. By optimizing parking space allocation strategies in the parking lot, this project seeks to improve overall traffic management and relieve these challenges.

To achieve this, a linear programming (LP) algorithm and a simulation-based genetic algorithm (GA) are employed to search for the optimal solution. While the LP model offers computational efficiency, it has limitations in incorporating different route conditions. To address this, an agent-based simulation is constructed to depict the interaction and movement of vehicles within the parking lot. The simulation-based GA utilizes objective values derived from the simulation, providing a more comprehensive basis for finding the optimal solution. The allocation process considers factors such as parking lot layout, vehicle entry time step, and specific parking rules including road directions within the parking lot.

Results demonstrate that the optimal strategy obtained from the simulation-based GA outperforms comparison groups. The simulation-based GA showcases its ability to converge on the optimal solution within a large solution area. The optimal strategy saving time for all vehicles, particularly during periods of high demand. Effective parking is achieved by allocating parking spaces according to the arrival order and positioning vehicles on the left or right based on their arrival order and parking space location.

By employing these methods, this project offers a valuable contribution to the field of parking space allocation in the parking lot during PSEs, enhancing the overall parking experience for event attendees.