Parking Platform Research Articles

An adjustment method of shared private idle parking spaces matching scheme considering demanders cancel reservations

An adjustment method for the initial matching scheme between private idle parking spaces and demanders is proposed in this paper. We consider a shared parking platform to determine the initial matching scheme. However, the demanders may cancel reservations due to the change of destinations or parking time before the matching scheme is executed. Meanwhile, new demanders make reservations. We develop a multi-objective optimization model satisfies adjustment principles to obtain the adjusted matching scheme that mitigates the negative impacts of cancellation reservation. The objective is to maximize the satisfaction of demanders, the satisfaction of private idle parking spaces, and the platform profit. The improved nondominated sorting genetic algorithm II (INSGA-II) is then developed to solve the model and determine the adjusted matching scheme. Our results suggest that the performance of the adjusted matching scheme outperforms that of non-adjusted matching scheme for various experimental sizes.

A many-to-many matching method considering priority for shared private idle parking spaces and demanders

There has been widespread and growing concern about parking. This paper attempts to provide decision support for a shared parking system to reduce parking difficulty. We study a many-to-many matching problem between shared private idle parking spaces and their demanders. A novelty is that the demanders are allowed to use different parking spaces successively in parking relocation service support. This can further reintegrate the idle time of the parking spaces and improve their utilization rate. A multi-objective optimization model is constructed to maximize the number of matched demanders, the total priority of the parking spaces, and the total priority of the demanders. More importantly, the priorities of the parking spaces and the demanders are innovatively considered. Each of the parking spaces and the demanders is given a priority for the matching and the priority of a parking space or a demander will be increased if the parking space or demander rarely gets matched successfully. This helps reduce the withdrawal of parking spaces and the demanders from the parking platform. In addition, an NSGA-II algorithm is designed to solve the model efficiently. Finally, the feasibility of the proposed method is illustrated via an example.

R&D and Application of Smart Park Energy Control Platform Combined with MLM Technology

Abstract As the core of park intelligence, the smart park energy control platform realizes the efficient management and optimal use of park energy by integrating and applying IoT technology. This study focuses on the research development and application of a smart park energy management and control platform using IoT technology, firstly constructing the IoT smart park platform, designing the login module, the park information module, and the energy consumption analysis module, and describing the steps of the smart park energy collection algorithm, and then designing the model of the energy prediction and planning algorithms, i.e.In the construction of the LSTM heating temperature prediction model and the GRU network modeling. Testing and research can be done by using a smart park as an example. The empirical study shows that the construction of the IoT smart park platform can improve the accuracy of monitoring, and the difference between the actual collection results and the system monitoring results is no more than 0.03 kW. After optimizing the configuration, the park’s energy supply system can meet the electric heating and cooling loads with optimal efficiency. Through the comprehensive evaluation of the operation of the extensive energy information monitoring platform, the environmental pollutant emissions are reduced by about 20%, and the platform has a remarkable effect on energy saving and emission reduction.

Auction-based parking mechanisms considering withdrawal behaviors

Auction-based parking mechanisms (ABPM) have been recognized as promising solutions to the parking problem. As the operator of the ABPM, the parking platform should not only be well-operated to provide parking services for demanders in need but also maintain commercial viability for sustainable operations. Motivated by this, we propose three ABPMs, namely, the ABPM without withdrawal right, the ABPM with costless withdrawal right, and the ABPM with non-free withdrawal right. Particularly, we characterize the parking demanders' withdrawal behaviors in the ABPMs. This behavior is motivated by the demanders' negative utilities derived from the auction sequence, where the demanders will first submit bid prices and are then allowed to withdraw from the parking market after the announcement of auction results when they are aware of their true valuations. We derive the equilibrium bidding strategies and the platform's expected revenues under the above three mechanisms and compare them in terms of the analytical results. It has been found that the introduction of withdrawal right will stimulate demanders to raise their bids for winning and the ABPM with non-free withdrawal right generates the highest revenue under certain conditions. A case study of parking in Beijing Financial Street has been conducted to illustrate the findings and explore managerial implications, including adapting the ABPM with non-free withdrawal right, narrowing the parking supply-demand gap, and enhancing travel experiences on the way to parking.

Determining an Optimal Government Subsidy Scheme for Shared Parking Management via a Bi-Level Programming Approach

A bi-level programming model is formulated to determine a government subsidy scheme for shared parking management. The government, as the upper-level decision-maker, seeks to maximize the social benefit by providing subsidy to the shared parking platform, incentivizing the platform to rent more shared parking slots, which can increase the utilization rate of idle parking slots and reduce the curbside parking cruising time of parking demanders. At the lower-level formulation, the shared parking platform, as a reseller, not only matches shared parking slot demanders but also determines which shared parking slots to rent, which is approached by a two-sided decision-making process. A “one-to-many” matching principle is adopted for the platform to maximize its revenue. A modified genetic algorithm is designed to solve the proposed model. Results indicate that the government subsidy has a positive impact on stimulating the shared parking market. Specifically, from the perspective of the government, the subsidy can increase the number of matched shared parking demanders, improve the supply of parking slots, and reduce curbside parking cruising time. From the perspective of the shared parking platform, the subsidy can lead to higher revenue.

Accelerating Benders decomposition approach for shared parking spaces allocation considering parking unpunctuality and no-shows

By allocating idle private parking spaces to demanders, shared parking reuses idle resources and effectively alleviates parking problems. In practice, there may be parking unpunctuality behavior of demanders, as well as the potential no-show behavior of owners and demanders. These stochastic factors affect the allocation of shared parking spaces. In this paper, we study the shared parking spaces allocation problem considering parking unpunctuality and no-shows. First, the allocation problem considering parking unpunctuality is formulated as a stochastic programming model, with the objective to maximize the profit of the shared parking platform. Sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm is exploited to solve the model effectively, where initial optimality cuts are explored to speed up the convergence of the algorithm. Then the proposed approach is extended to incorporate no-shows. Numerical experiments show great performance of the proposed approach. The experiments also show that the fluctuations of the unpunctual time and the no-show probability have a significant impact on the shared parking system, and balanced supply and demand is helpful to increase the profit of the platform and the satisfaction of demanders.

Competition among parking platforms in the presence of indirect network effects

A parking market including conventional public parking and novel shared parking is considered for matching parking demands and supplies. To investigate the competition between the public parking platform and the shared parking platform, a market equilibrium approach is proposed to investigate the interactions among the parking platforms, parking demanders, and parking owners, where indirect network effects referring mutual attractions between demands and supplies are incorporated. Targeted for profit maximization, we first formulate a basic model and derive the equilibrium results of parking platforms’ profits. Results show that indirect network effects positively affect the two parking platforms’ profits when the equivalent gains from alternative activities for parking owners are large, while negatively affect the profits otherwise in certain cases. Extensions regarding some considerations are then discussed, where Model D is proposed for dual decision of the shared parking platform and Model S is proposed for the social welfare maximization objective of the public parking platform. Comparisons of the three models in terms of equilibrium results are simulated consequently. Managerial implications to enhance the profits of the two parking platforms are further discussed.

Prospect Theory-Based Two-Sided Satisfied and Stable Matching Mechanism for the Shared Parking Slots Problem

The contradiction between the dramatic increase in the aggregate number of automobiles and the short supply of parking spaces leads to parking difficulties. Sharing mode helps improve the efficiency of existing parking spaces, increase resource utilization, and alleviate the difficulty of parking. This paper focuses on the matching mechanism in the shared parking slots problem, which involves three agents: shared parking suppliers, shared parking demanders, and shared parking platform. We propose a prospect theory-based two-sided satisfied and stable matching model (PT-TSSM) with two objectives to maximize the satisfaction degree of both shared parking demanders and shared parking suppliers. Numerical experiments are illustrated to demonstrate the efficiency of the proposed model. Moreover, the PT-TSSM model is compared with the other two shared parking mechanisms. The proposed model considers the satisfaction degrees of both shared parking demanders and suppliers, while first book first serve (FBFS) cares only one side of the participants. And compared with deferred acceptance (DA), our model not only takes two-sided stable matching into account but also considers the satisfaction degree of all the demand and supply participants, which obtain a two-sided satisfied and stable matching scheme.

Online stochastic weighted matching algorithm for real‐time shared parking

AbstractParking management plays an important role in the efficiency of transportation systems. We study the problem of matching shared parking slots with demanders online on a parking platform with the aim of managing parking spaces intelligently and efficiently. In our setting, the demanders submitting parking requests sequentially are assumed to be drawn from a distribution over demander types. No further assumptions about the demander arrival stream are needed. Matching decisions are triggered by arrival events instead of time points. This benefits the demanders by immediate responses to parking requests. An online matching algorithm is designed to make real‐time decisions and maximize social welfare. We demonstrated that the algorithm has a large competitive ratio, which implies a good performance of the algorithm. Numerical experiments are conducted to further examine the performance of the algorithm. The experimental results show that our proposed algorithm can achieve such a large competitive ratio in a real‐time matching way as the batch matching algorithm does in a serious delay matching way.

Intelligent parking platform based on huawei soft ker cloud

Nowadays, parking problem in urban cities has getting more and more urgent. Most of the problems are mainly due to the information share and management. In the work, we develop a cloud platform based on Huawei soft Ker cloud. On the cloud platform, we build a new smart parking platform, and implement methods, programs, and simulation test system for design and debugging. The functions of license plate recognition, car search and navigation, payment, parking lot search, intelligent parking are implemented in the platform through code debugging.

Optimal allocation of shared parking spaces for hospital parkers considering parking choice behavior under bounded rationality

ABSTRACT Lack of parking spaces at downtown hospitals causes urban problems like patient access delays and additional carbon emissions. This paper proposes a cumulative prospect theory-based shared parking space allocation model (CPT-SPSA model) to alleviate the parking difficulties. The CPT-SPSA model aims to maximize the profit of the shared parking platform under time window constraints considering the parking choice behavior of hospital parkers. To determine the parking choice behavior, cumulative prospect theory (CPT) is utilized to model parkers’ evaluation of parking lots considering individual heterogeneity. Numerical experiments indicate that the profit of the platform and the utilization rate of the shared parking spaces are improved significantly and more successful matches of shared parking supply and demand are achieved under the CPT-SPSA model. Those with different parking purposes vary in acceptance of each parking lot. The platform can earn more profit by reasonably adjusting the parking fees of the shared parking spaces.

Robust method of shared parking allocation based on buffer time

Shared parking platform determines the parking allocation schemes according to the time windows of parking supplies and parking demands. In order to deal with uncertain situations such as early arrival or delayed departure during parking, the robustness of the parking allocation scheme is enhanced by reserving appropriate buffer time. This paper builds a bi-objective optimization model of parking space allocation problem that maximizes the platform revenue and the robustness. The bi-objective function is transformed into a single objective function by the weighted sum method, and the nonlinear model is transformed into a linear model by adding auxiliary decision variables. Finally, the effectiveness of the method is verified by a numerical example, and the sensitivity analysis of key parameters is carried out. The results show that within a reasonable time, the method can obtain the optimal solution and various index values of the example. With the increase of the dual-objective adjustment coefficient, the platform revenue segment increases, while the robustness segment decreases. The non-dominated solutions are screened out from the optimal solutions obtained by different adjustment coefficients, and the approximate Pareto frontier curve is obtained by fitting. The robustness reduction varies in the range of [0.02, 6.75].

Shared parking acceptance under perceived network externality and risks: Theory and evidence

Despite the increasing interest in shared parking, little attention has been devoted to its perceptions and acceptance among drivers. To fill such a gap, this paper develops a novel theoretical framework in which perceived network externality, cost risk, safety risk, and management pressure are incorporated into the Combined Technology Acceptance Model and Theory of Planned Behavior (C-TAM-TPB). This paper merely focuses on positive network externality. First, a mathematical model is proposed to verify some of the hypotheses. The analytical results show that both a driver’s utility and the shared parking platform’s equilibrium demand are increasing in the effect of network externality and decreasing in the effect of risks. Second, a structural equation modeling approach with the partial least squares algorithm is employed for parameter estimation and model assessment. We conducted a quantitative study with 321 usable responses. The empirical results show that, except for management pressure, all the other constructs measured in the study had a significant total effect on user attitude and use intention towards shared parking. The corresponding amount of variance in attitude and use intention explained by our research model was 68.4% and 72.6%, respectively. Our findings shall provide useful insights into the better implementation of shared parking applications from managerial, technological, and operational perspectives.

PriParkRec: Privacy-Preserving Decentralized Parking Recommendation Service

Insufficient parking space and traffic congestion are important usual suspects in our urban life. Organisation and managing available parking spaces have raised a lot of awareness. Traditional centralized parking approaches are with an insidious single point of failure and unsuitable for large organization because the manager is overburdened with authority and responsibility. The malicious service provider enables to (i) track the precise mobility patterns of citizens. (ii) collect the data to infer privacy-sensitive information, e.g., where the parking requester (i.e., driver) socialize, work, and live; (iii) analyze trajectories to monitor the location of the driver for entertainment (e.g., discovering one-night stands). To design a decentralized smart and practical parking platform without compromising the privacy of the entities is an urgent issue for the smart city. Blockchain (or distributed public ledger technology) is a near-ideal decentralized and distributed solution for centralized parking-space-recommendation systems. However, most of the existing parking recommendation solutions on top of blockchain ignore to protect the privacy of drivers during parking spot detection and matching phases while cannot maintain the property of anonymity of the drivers. In this paper, an efficient and privacy-preserving parking-space recommendation service platform, named as PriParkRec, along with the proof-of-concept solution to protect the requester's privacy in PriParkRec while maintaining most of the benefits of current parking-space sharing service, i.e., accountability, (anonymous) authentication, (anonymous) payment, and reputation ratings. Indeed, PriParkRec service relies on well-known privacy-enhancing cryptographic building blocks (e.g., oblivious PRF, private set intersection, anonymous credentials, anonymous payment, and smart-contract, etc), these building blocks are carefully integrated together to achieve privacy and security goals to revolutionize the existing car-parking service system coming with the private blockchain and industrial internet of things (IIoTs) technologies.

Research on Integrated Management Platform of Smart Park Based on CIM

At present, the construction of smart cities and smart parks in China has been widely concerned, and the intelligent decision-making in the process of urban planning, design, construction and management is in urgent need of refined, visualized, dynamic and integrated expression of urban entity information. Therefore, this paper studies a technical theory of digital description and expression of cities, namely CIM (City Information Model). Our team independently innovates, developing smart park management platforms. This platform is based on BIM (Building Information Model), GIS, IOT (Internet of Things) and other new generation information technologies. BIM mainly studies parametric information inside buildings, while GIS focuses on external spatial geographic information. IOT Internet of Things technology realizes the transmission and processing between information and data. This platform integrates and upgrades these technologies to build a smart park platform. This paper explores the presentation and current situation of CIM theory and technology under the background of smart city construction, smart park construction and operation and maintenance management.

A Live Smart Parking Demonstrator: Architecture, Data Flows, and Deployment

Smart Parking is essential for any future smart cities due to the tremendous growth of the car fleet. Such infrastructures require a certain amount of equipment. Indeed, smart parking integrates a lot of actors, to manage the parking its equipment must be managed accordingly. Here, is proposed a distributed architecture to manage them by collecting efficiently their data. Two types of data relating to the parking must be collected: those coming from the deployed equipment in the parking and those coming from the internet due to remote users. Thus, a system of two main servers based on the multi-agent concept is proposed. This system manages the parking platform. The first server is dedicated to the parking equipment data collection (Processing Server–PS). The second server (Processing Web Server–PWS) collects the users’ online data such as reservation, and it is responsible for pricing policies, and receive post-processed data from the Processing Server. The parking equipment integrates a lot of commercial solutions, an intelligent multi-platform application based on this two server philosophy is developed and can be used for parking operation by users and parking managers. The flowcharts of the agents from the two mains servers are presented. These flowcharts are currently used in our demonstrator and still under improvements. Here, we present the architecture (hardware and software) of our smart parking demonstrator developed by our department and suitable for the experimentation of our future work related to this hot topic.

Development of Intelligent Car-Parking System

In this modern world, the paradigm of smart cities has gathered major popularity. Thanks to the evolution of microcontroller, the notion of smart city seems more convincing. This paper proposes an algorithm that helps users to find a free parking space for cars automatically. Microcontrollers and sensors have already made a huge impact on learning and predictive analysis. The widespread affirmation gave a new life to this open source hardware component which potentially became a big challenge to many industrial products and new interests in electronic system and prototyping.This paper deals with effective parking solution which involves the use of ultrasonic sensor, atmega series, wireless signal module, cloud server and decrease the time spent for searching parking spaces. IoT based new parking platform enable to connect, analyze and automate data gathered from devices and execute smart parking possible. The proposed system not only reduces manpower but also reduces traffic congestion, and facilitating secure parking system within a limited area.

Design of Cylindrical Three-dimensional Garage System

The increasing of car ownership makes the problem of parking difficult to become more and more prominent. The application of three-dimensional garage is one of the most effective solutions at present, which saves both cost and space. Based on the traditional three-dimensional garage, this paper designs a cylindrical three-dimensional garage system. The lifting device of the vehicle is composed of screw, parking platform, and transmission track. The control system of the garage is designed with the single-chip microcomputer as the control core. Finally, the control circuit of the software simulation system realizes the function of automatic exit storage of vehicles, which verifies the feasibility of the design.

Pricing strategies for shared parking management with double auction approach: Differential price vs. uniform price

Focusing on the price issue in shared parking, two auction-based pricing strategies are designed in a double environment covering parking suppliers and demanders. A novel uniform price strategy (UPS) is proposed to set unique transaction prices for winning participants, it is in contrast with the differential price strategy (DPS), which sets differential transaction prices. The DPS and UPS are compared from the perspective of parking platform’s payoff and participants’ utilities theoretically and numerically. It shows that the DPS is superior to the UPS in terms of parking platform’s payoff whilst the UPS outperforms the DPS in terms of participants’ utilities.

Smart Monitoring and Control of Bus Stand and Goods Transport System Activity using Cloud Computing

This work focuses on the, implementation and validation of smart public transport system as well as goods transport system based on the application of GPS (Global Positioning System) technology, GSM (Global system for mobile communication) using Cloud computing. This system has been distributed into four modules as In-Bus/truck module, Bus/truck-stand module, cloud system and user mobile apps. After initialization of In-Bus/truck module, driver gets the information regarding to the platform availability on parking zone that are assigned to it. If the platform is vacant then driver needs to park the bus/truck at said position only. The drivers may get allotted or waiting parking platform’s information through SMS or on Drivers app. The GSM integrated GPS technology can also be used to get the current location of vehicles and the available vacant seats or vacant space in truck. This information will be recorded automatically by the system. IOT module ESP12E NODEMCU is used for controlling and handling whole operations by collecting the data. This system will also guide the drivers and the bus/truck stand controller to control all vacant ports based on real time operation. One In-Bus/truck module (configured along ESP12E) needs to be installed into each vehicle to be monitored. One Bus/truck-stand module has to be installed in to each platform. Cloud system is needed to collect the whole data for big public/goods transport systems for automation of 1000s of vehicles at a time. ThingSpeak cloud is used and computing is performed by MATLAB computing. For late running, on-time running and before time running vehicles, messages are automatically sent regarding to its location and vacant seats/space. And will be displayed on rolling board on platform. Passenger/user may get the correct information by sending message on his mobile from anywhere through mobile app. Mobile app is developed to perform all the task of monitoring to passenger/user, and drivers.