May 2024
Intermediate to advanced
352 pages
8h 50m
English
Content preview from Metaheuristics for Machine Learning
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11Adapting Underground Parking for the Future: Sustainability and Shared Autonomous Vehicles
Vamsidhar Talasila1*, Madala Pavan Pranav Sai1, Gade Sri Raja Gopala Reddy1, Vempati Pavan Kashyap1, Gunda Karthik1 and K. V. Panduranga Rao2
1Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India
2Department of Computer Science and Engineering, Sree Vahini Institute of Science and Technology, Tiruvuru, India
Abstract
A significant field of worldwide science and technical innovation is the creation of shared autonomous vehicles (SAVs). SAVs’ ability to drastically minimize the requirement for parking is one of its most coveted qualities in urban areas. Particularly in densely populated metropolitan areas, the town’s underground parking space (UPS) is presently the biggest fixed-traffic area. The requirement for UPS renewals will become more urgent in the SAV situation. However, due to its unique form attributes, which are significantly constrained by outside factors, the UPS is challenging to renew, requiring aimed techniques and tactics. To gather information for this study, fieldwork was initially done to examine the geographical morphology and operating circumstances of typical UPSs in various parts of Ningbo. The time series assessment technique and functional substitution choice models for the sustainable renewal of subterranean parking were developed dependent on the driver status reaction and the multiple-purpose feature ...
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