Next-generation smart carpark
Parking in modern urban areas presents significant challenges due to the increasing number of vehicles and limited space. This study explores various automated allocation algorithms aimed at optimising the efficiency of parking operations. The goal is to reduce wait times, enhance user experience...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181289 |
| _version_ | 1824456660952809472 |
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| author | Lee, Shannen |
| author2 | Huang Shell Ying |
| author_facet | Huang Shell Ying Lee, Shannen |
| author_sort | Lee, Shannen |
| collection | NTU |
| description | Parking in modern urban areas presents significant challenges due to the increasing number of
vehicles and limited space. This study explores various automated allocation algorithms aimed
at optimising the efficiency of parking operations. The goal is to reduce wait times, enhance
user experience, and maximise the utilisation of available parking spaces. By comparing
different algorithms—First Available Lot (FAL), Nearest Available Lot (NAL) DurationBased Allocation, and Q-Learning—across traditional and next-generation parking structures,
this research identifies the most effective solutions for modern urban settings. The
implementation of such systems can significantly ease parking constraints and better manage
space in densely populated areas. |
| first_indexed | 2025-02-19T03:57:38Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/181289 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:57:38Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1812892024-11-22T11:18:03Z Next-generation smart carpark Lee, Shannen Huang Shell Ying College of Computing and Data Science ASSYHUANG@ntu.edu.sg Computer and Information Science Parking in modern urban areas presents significant challenges due to the increasing number of vehicles and limited space. This study explores various automated allocation algorithms aimed at optimising the efficiency of parking operations. The goal is to reduce wait times, enhance user experience, and maximise the utilisation of available parking spaces. By comparing different algorithms—First Available Lot (FAL), Nearest Available Lot (NAL) DurationBased Allocation, and Q-Learning—across traditional and next-generation parking structures, this research identifies the most effective solutions for modern urban settings. The implementation of such systems can significantly ease parking constraints and better manage space in densely populated areas. Bachelor's degree 2024-11-22T11:18:02Z 2024-11-22T11:18:02Z 2024 Final Year Project (FYP) Lee, S. (2024). Next-generation smart carpark. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181289 https://hdl.handle.net/10356/181289 en SCSE23-1184 application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Lee, Shannen Next-generation smart carpark |
| title | Next-generation smart carpark |
| title_full | Next-generation smart carpark |
| title_fullStr | Next-generation smart carpark |
| title_full_unstemmed | Next-generation smart carpark |
| title_short | Next-generation smart carpark |
| title_sort | next generation smart carpark |
| topic | Computer and Information Science |
| url | https://hdl.handle.net/10356/181289 |
| work_keys_str_mv | AT leeshannen nextgenerationsmartcarpark |