Nghiên cứu hệ thống hộ trợ đỗ xe thông minh dựa trên vận dụng công nghệ internet = intelligent parking assist system based

逢 甲 大 學 資 訊 工 程 學 系 博 士 論 文 基於物聯網技術運用於智慧停車 輔助系統之研究 Intelligent Parking Assist System based on Internet of Things Technologies 指導教授：許芳榮 共同指導教授：蔡明峰 研 究 生：范南青 中 華 民 國 一 百 零 七 年 六 月 Intelligent Parking Assist System based on Internet of Things Technologies Acknowledgements First and foremost, I would like to my advisers, Professor Ming-Fong Tsai and Professor Fang-Rong Hsu Professor Tsai, thank you very much for your encouragement, guidance, and support for the years I spent in Feng Chia You are truly visionary and a great advisor Professor Hsu, thank you for supporting me and your useful advice that you have given me I really enjoyed those brainstorming and discussion meetings that we had Without both of you, this research would not be possible Thank you I am grateful to Professor Chyi-Ren Dow for supporting me and giving me the opportunity to study in Feng Chia Many thanks to Professor Wei-Bin Lee, Professor Wei-Chih Hong, Professor Yi-Chung Chen, Professor Tzong-An Su for the knowledge you gave me in my courses To all Professors and Teaching Assistants who have taught me, I thank you I would also like to thank to all my lab-mates in Wireless Networking Lab and Intelligent of Things Lab for giving me a great working place and great help while I work here In particular, I would like to thank my dear friend Curtis Ye for the wonderful time that we spent together I also greatly appreciate all the help from Bo Cai, Ching-Fu Hsiang, ChiaYuan, Qi-Feng and other friends Special thanks to my family, especially my Mom and Dad, for their support and encouragement over the years Finally, I am thankful to my wife for her love giving me i FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Abstract In recent years, there has been a rapid development of technologies devising solutions for intelligent transportation systems, including intelligent parking assist systems However, previous systems revealed several weaknesses, such as models which are not scalable, not provide a full range of parking services to users, not effectively manage parking resources, and have high latency in real-time parking services To overcome these problems, this thesis examines previous research and proposes a new model for intelligent parking assist systems We also introduce novel algorithms that increase the efficiency of the proposed system based on Internet of Things (IoT) technologies Our system can help users to automatically find an optimal parking space at the least cost, based on new performance metrics In addition, this thesis also proposes an intelligent parking assist system with a full range of end-to-end support services including: finding a suitable parking space based on the user’s profile, outside guidance service, enter car park service, and indoor guidance service Our system has been simulated and successfully implemented in the real world The simulation results show that our system helps to improve the probability of successful parking and minimizes user waiting time Keywords: Smart parking system, Internet of Things technologies, performance metrics ii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Table of Contents Acknowledgements i Abstract ii Table of Contents iii List of Figures v List of Tables vii Chapter Introduction to the Development of Intelligent Parking Systems 1.1 Automated parking system 1.2 Intelligent parking assist system 1.3 Classification of intelligent parking assist system 1.4 Shortfalls of current Parking Systems Chapter Architecture for Intelligent Parking Assist Systems based on Internet of Things Technologies 2.1 Internet of Things technologies 2.2 Structure of an IPAS System based on IoT technologies 11 2.2.1 Local Parking Unit 11 2.2.2 Database Server 13 2.2.3 Software Client 15 2.3 IoT Hardware for IPAS Systems 16 2.3.1 Sensors 16 2.3.2 Arduino, Raspberry Pi Control Units 18 2.4 Protocol stack for IPAS systems 19 2.5 Propose the IPAS network based on IoT technologies 21 2.5.1 Parking Network 22 2.5.2 Construct the neighbor table of nodes 25 Chapter Mathematical Models for IPAS Systems 28 3.1 Linked-Cost function estimation 28 iii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies 3.2 Total Parking Cost Estimation 31 3.3 Parking Queue Models 33 Chapter Smart Services System Over Parking Networks 35 4.1 Introduction 35 4.2 System Framework 36 4.3 Parking Services 38 4.3.1 Searching Service and Booking Service 38 4.3.2 Tracking service 40 4.3.3 Guidance service 41 4.3.4 Locking Service and Warning Service 42 4.4 Implementation 43 Chapter Enhance the Performance of Wireless Communication in Intelligent Parking System 47 5.1 Indoor guidance using Ultra-wideband signals 47 5.2 Improve the quality of data transmission in IPAS system using a look up table structure 51 5.3 An adaptive solution for data transmission between local IoT network and server system using MQTT protocol 56 Chapter Evaluate the Performance of Intelligent Parking System 60 6.1 Arena simulation tool 60 6.2 Scenarios setup 61 6.3 Evaluate the performance of IPAS system 63 6.3.1 Without consideration of parking fee 63 6.3.2 With consideration of parking fee 67 Chapter Conclusion 69 7.1 Summary 69 7.2 Perspectives 69 7.3 The future of IPAS system 70 References 71 iv FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies List of Figures Figure 1 An automated parking system Figure The basic configuration of an IPAS system Figure The basic structure of an IPAS system based on Internet of Things technologies 11 Figure 2 The role of the control unit in an IPAS system 12 Figure The use of ultrasonic sensor to detect the presence of the car at the parking space 13 Figure Propose to use Fog Computing in building intelligent parking assist system 14 Figure The interface of an IPAS system running on iOS platform 16 Figure Andruino/Raspberry Pi module used as control unit in Intelligent Parking Assist System 19 Figure Stack of protocols for Intelligent Parking Assist System 21 Figure Infrastructure/Backbone of the CPN architecture 22 Figure Car park network deployment for car parking system 23 Figure 10 Parking network 24 Figure 11 Simple neighbour tables 25 Figure 12 Neighbour tables sorted by descending values of F ( ,  ,  ) 26 Figure 13 A searching for a parking space based on the cost function 27 Figure The service queue 33 Figure System framework for IPAS services 37 Figure Illustrate the Searching/Booking Service 39 Figure Illustrate the Tracking service 40 Figure 4 Illustrate the guidance services: (a) Outside guidance, (b) Entering car park guidance, (c) Indoor guidance 42 Figure Illustrate the Car Locking and Warning Service 43 v FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Figure Procedures reserved parking spot 44 Figure Implementation of outside car park navigation system 45 Figure Implementation of inside carpark navigation system 46 Figure Enhance the accuracy of indoor navigation method for intelligent parking system using UWB signals 48 Figure Estimate the TOF between vehicle’s tag and anchor 49 Figure Determine the user’s position in the parking system 50 Figure Efficiency comparison between proposed method and other related works 51 Figure 5 Wireless communications in a local parking lot 52 Figure Apply the Lookup table structure to minimize the overhead of data transmission in IPAS system 54 Figure Comparison of Recovery Overhead of different RS codes: (a) Communication distance changes; (b) BER changes (with k = 223 bytes) 55 Figure Comparison of average recovery overhead of proposed Adaptive LookupTable method, AMFEC [57], and Ghaida [58] with number of data transmissions t = 56 Figure A new architecture for real-time data transmission in IPAS system using MQTT protocol 57 Figure 10 Comparison between the adaptive network and normal network for changes in queue length and number of sensor nodes: (a) end-to-end delay; (b) packet drop rate 59 Figure An installation setup to simulate IPAS systems using Arena software 61 Figure A 5-node network 62 Figure Average waiting time in a normal network vs the proposed network 64 Figure Average total time in normal network vs the proposed network 65 Figure Average waiting time vs parking fee 68 vi FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies List of Tables Table Comparison between Cloud Computing and Fog Computing for IPAS system 15 Table 2 Comparison of protocols used in IPAS system 20 Table Table of cost function 30 Table Reference information for each user 45 Table Simulation Parameters 62 Table Average waiting time in case of POIS(20 minute) 65 Table Average waiting time in case of POIS(15 minute) 66 Table Average total time in case of POIS(20 minute) 66 Table Average total time in case of POIS(15 minute) 67 vii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Figure Average waiting time in a normal network vs the proposed network We realize that if we use the percentage of free spaces in each car park as a parameter for planning with regard to forwarding users, the waiting time of the user for service will be greatly reduced compared to an ordinary network In Fig 6.4, we compare the average total time of each vehicle in a normal network model and our proposed network model We can see that if the value of α is 0.8 and β is 0.2, our proposed network achieves best performance compared to other pairs of (α, β) If the value of α is and β is 0, the average total time is approximately equal to the average total time in a normal network It is the worst case The best solution in this network, with (α = 0.2, β = 0.8), reduces the average total time the user stays in the system by approximately 50% 64 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Figure Average total time in normal network vs the proposed network The following results are description of all values of α and β: Table Average waiting time in case of POIS(20 minute) 65 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Table Average waiting time in case of POIS(15 minute) Table Average total time in case of POIS(20 minute) 66 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Table Average total time in case of POIS(15 minute) 6.3.2 With consideration of parking fee In figure 6.5, we can see with shortest path option (α = 1, β = 0, γ = 0), the average waiting time of the user is greater than 20 minutes and this is not the optimal value Besides the parking fee is highest with Fcost = 100 If we choose the least cost option in term of parking fee, the average waiting time that vehicles wait for parking is the longest and more than 25 minutes, but the parking fee that user should pay is the smallest with Fcost = And, with best space option, we can see in Fig 6.5 that the average waiting time is minimal With the set of values (α = 0.2, β = 0.8, γ = 0) we can see the user has the smallest average waiting time and it is smaller than 10 minutes This set of values coincides with the optimal values of the waiting time as in [10], but we could see the parking fee which users should to pay is still not an optimal value with Fcost = 36 This because the value of α is means that users only care about the wait time for parking without regard to the fee should pay for parking In this paper, we propose to use the set of values (α = 0.2, β = 0.5, γ = 0.3) because the waiting time may be acceptable by users and the cost of parking fee is near to optimal values This will bring a lot of significant for users with very long parking time 67 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Figure Average waiting time vs parking fee 68 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Chapter Conclusion 7.1 Summary This thesis studies the models of intelligent parking systems based on IoT technologies This research also introduces a novel parking network which connects all parking lots and offers intelligent services These services have the following benefits: • This thesis helps to provide an architecture of intelligent parking networks from which local parking networks with existing infrastructure can be easily integrated into the system • Our large-scale parking system architecture makes it convenient for service providers to manage and utilize the parking lot resources efficiently • This system provides more information about car parking places in real-time • It will give more options to users to select the appropriate free parking space via their smartphone • It will help users to quickly and accurately reach their desired parking space • It helps users to monitor and give warnings about the current parking situation when they are outside of a car park In addition, this study proposes a new method to help users estimate the cost in terms of travel time and parking time, because we provide an optimal solution for the parking requests searched for by users This study also proposes new methods to improve the performance of intelligent parking systems 7.2 Perspectives Parking is becoming more and more popular in modern life The research and development of smart parking models is becoming an emerging topic of interest IoT technology has recently exploded in all kinds of applications in life Therefore, this thesis raises the perspective of the construction of future data networks and the modelling of intelligent cities 69 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies 7.3 The future of IPAS system In the future, vehicles will become smart objects Vehicles will themselves be aware of the surrounding environment and will be able to provide solutions to traffic situations They will interact with other nearby vehicles and find an optimal route to the most appropriate parking lot All vehicles will be managed by unique ID addresses similar to the ID of each individual A vehicle identification system will be developed, which can identify vehicle IDs at great distances (much more than current technologies such as RFID); this will help to identify and locate vehicles more accurately and quickly The management of vehicles by ID helps operators to easily compile statistical data on the activities of each vehicle, including travel time and parking time, which will feed into plans to construct intelligent parking networks more effectively In addition, 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