Next generation smart carpark

With the urbanized and ever-increasing demand for vehicle ownership, the need for innovative parking solutions in densely populated areas like Singapore has never been more critical. Automated Parking Systems (APS) have emerged as a promising solution, offering efficient space utilization and reduce...

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Main Author: Leong, Samuel Mun Kit
Other Authors: Huang Shell Ying
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/172054
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1720542023-12-08T15:37:30Z Next generation smart carpark Leong, Samuel Mun Kit Huang Shell Ying School of Computer Science and Engineering ASSYHUANG@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling With the urbanized and ever-increasing demand for vehicle ownership, the need for innovative parking solutions in densely populated areas like Singapore has never been more critical. Automated Parking Systems (APS) have emerged as a promising solution, offering efficient space utilization and reduced carbon footprint. This study conducts a comprehensive simulation-based investigation of various allocation policies within a realistic model of the Changi APS. The main objective of this research is to enhance operational efficiency, reduce parking and retrieval waiting times, considering Singapore’s unique land constraints. The study analyzes the differences in performance of lifts, shuttles, and other automated hardware, with different allocation policies. These policies include Nearest Parking First, Balanced Parking, Randomized Parking, and Temporary Lot Parking. The key findings reveal that, in a lightly loaded system, the Temporary Lots Parking policy outperforms others in parking and service times, despite a slightly higher retrieval time compared to Nearest Parking First. Conversely, in a heavily loaded system, the Nearest Parking First policy excels in parking time but lags behind in service and retrieval times. In conclusion, this research underscores the potential of APS as an innovative solution for optimizing parking space in urban areas while reducing environmental impact. Future research may further explore the optimal configuration of parking resources, location-specific considerations, and hybrid allocation policies to address varied urban challenges. This study provides valuable insights for policymakers, urban planners, and engineers seeking to enhance parking efficiency in high-density urban environments. Bachelor of Engineering (Computer Science) 2023-11-21T06:07:01Z 2023-11-21T06:07:01Z 2023 Final Year Project (FYP) Leong, S. M. K. (2023). Next generation smart carpark. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172054 https://hdl.handle.net/10356/172054 en SCSE22-1069 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
Leong, Samuel Mun Kit
Next generation smart carpark
description With the urbanized and ever-increasing demand for vehicle ownership, the need for innovative parking solutions in densely populated areas like Singapore has never been more critical. Automated Parking Systems (APS) have emerged as a promising solution, offering efficient space utilization and reduced carbon footprint. This study conducts a comprehensive simulation-based investigation of various allocation policies within a realistic model of the Changi APS. The main objective of this research is to enhance operational efficiency, reduce parking and retrieval waiting times, considering Singapore’s unique land constraints. The study analyzes the differences in performance of lifts, shuttles, and other automated hardware, with different allocation policies. These policies include Nearest Parking First, Balanced Parking, Randomized Parking, and Temporary Lot Parking. The key findings reveal that, in a lightly loaded system, the Temporary Lots Parking policy outperforms others in parking and service times, despite a slightly higher retrieval time compared to Nearest Parking First. Conversely, in a heavily loaded system, the Nearest Parking First policy excels in parking time but lags behind in service and retrieval times. In conclusion, this research underscores the potential of APS as an innovative solution for optimizing parking space in urban areas while reducing environmental impact. Future research may further explore the optimal configuration of parking resources, location-specific considerations, and hybrid allocation policies to address varied urban challenges. This study provides valuable insights for policymakers, urban planners, and engineers seeking to enhance parking efficiency in high-density urban environments.
author2 Huang Shell Ying
author_facet Huang Shell Ying
Leong, Samuel Mun Kit
format Final Year Project
author Leong, Samuel Mun Kit
author_sort Leong, Samuel Mun Kit
title Next generation smart carpark
title_short Next generation smart carpark
title_full Next generation smart carpark
title_fullStr Next generation smart carpark
title_full_unstemmed Next generation smart carpark
title_sort next generation smart carpark
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/172054
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