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Title: Smart parking : guidance, monitoring and reservations
Author: Kotb, A. O.
ISNI:       0000 0004 6059 543X
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2016
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Today, parking is the main coordinator between the land use and transportation. As the urban population is increasing, more and more cars are circulating through the city in search for parking spaces, often contributing to the global problem of traffic congestion. Hence, several governments seek to improve their existing transportation systems and infrastructure. Examples of their initiatives include the launch of ‘Smart Parking’ projects in major urban areas. However, the developments to date in this area have some significant limitations lodged against them. In this dissertation, we propose 3 different smart parking systems: iParker, INDO and RFPark, to enhance the overall parking scheme. First, iParker and INDO are introduced as new parking management and reservations systems. Both change the parking behaviour from driver-side parking searching to system-side allocation. This is achieved by solving new Mixed Integer Linear Programming (MILP) optimisation problems with the objective of minimising driver's cost functions, while ensuring the maximum parking resource utilisation. Nevertheless, there are several differences between iParker and INDO. iParker is designed to operate as a country-wide system to offer drivers the optimal parking lot allocation and reservation before or at arrival to their destinations. This is based on minimising a driver's cost function that combines parking cost, reservation fees, proximity to multiple destinations and reservation type. As opposed to current reservation systems, iParker offers both static long-term reservations and dynamic short-term reservations, for both on-street and off-street parking lots. In addition, new pricing policies are proposed that allow the generation of more parking revenue and the fair distribution of parking traffic across parking lots. However, INDO is designed to operate inside individual parking lots who serve giant buildings - such as shopping malls - to offer the drivers the immediate optimal parking space allocation and the indoor guidance. A driver’s cost function here combines the times of driving inside the parking lot and walking inside the indoor destination. In addition, a Radio Frequency Identification/Near Field Communication (RFID/NFC) based navigation component is developed to provide commuters with guidance and navigation in the car park and the indoor destination. Based on simulation results, compared to the non-guided or the state-of-the-art guidance-based systems, iParker and INDO significantly reduce the average time to find a parking space and the drivers' cost, while the parking resources are more efficiently utilised. The pricing policies of iParker lead to the generation of more revenue and fair balance of traffic load across parking lots. In addition, INDO substantially reduces the commuting time indoors. On the other hand, RFPark is proposed as a new approach to parking monitoring. For the first time, Ultra High Frequency (UHF) passive RFID tags are deployed on the asphalt, and interrogated by RFID reader antennas above the parking spaces to detect the occupancy states. Most of the problems of the current cutting-edge parking occupancy detection systems are not present in this system. RFPark was analysed and implemented to show a pilot study in a real world outdoor parking environment in the University of Liverpool and has proved to have a very high detection accuracy. The innovative design and development of these 3 systems form a new ‘Smart Parking’ solution that offers to reduce the parking-related traffic congestion, enhance driver experience and improve the overall parking scheme. Although there are some challenges regarding the realisation of these smart systems, they are addressed here and solutions to them are proposed in this dissertation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available