No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
A study on smart parking guidance algorithm
Abstract
Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO2 emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.
... O sistema, proposto em [Shin and Jun 2014], destina o carroà uma vaga usando uma regra de despacho baseada na avaliação dos valores de dois tipos de funções de utilidade de estacionamento. A atribuição do carro solicitanteà um determinado estacionamento deve ser feita considerando-se as características dinâmicas do estacionamento, como seu uso, a condição do tráfego, a conveniência do usuário e assim por diante. ...
... Em [Shin and Jun 2014] são considerandos cinco objetos: estacionamento, sistema de gestão de estacionamentos, servidor central, dispositivo de navegação e o motorista. Cada estacionamento dispõe de um sensor que atualiza a sua disponibilidade. ...
... [Benenson et al. 2008] nãoé realizado nenhuma comunicação entre agentes. Nos outros sistemasé feito ou uma interação com um agente gerente [Rizvi et al. 2018], com outros agentes [Aliedani and Loke 2018] ou com um servidor central [Shin and Jun 2014]. ...
O trafego de veículos em áreas urbanas aumenta quando motoristas trafegam em busca de uma vaga de estacionamento. Estacionamentos inteligentes auxiliam nesta busca otimizando e gerenciando as vagas disponíveis com auxílio de Sistemas Multi-Agentes (SMAs). Neste artigo são analisadas características de SMAs no domínio de Smart Parkings, tais como: politicas de ações, hierarquia do SMA e comunicação entre agentes. O objetivo é comparar tais características para identificar semelhanças e diferenças entre os SMAs desenvolvidos. Os resultados preliminares ajudam a identificar algumas características no desenvolvimento de soluções para smart parkings, as quais serão úteis nas proximas etapas deste trabalho.
... Researchers have introduced various parking assignment methods, including parking guidance systems, to simulate driver behavior and assess the impact of these systems. For instance, parking guidance systems proposed by Shin and Jun (2014) [3], aiming to reduce driver cruising time by directing them to available spaces. Simulation experiments were conducted to evaluate the effectiveness of these systems, with a base case assuming drivers head to the nearest parking facility without guidance. ...
... Researchers have introduced various parking assignment methods, including parking guidance systems, to simulate driver behavior and assess the impact of these systems. For instance, parking guidance systems proposed by Shin and Jun (2014) [3], aiming to reduce driver cruising time by directing them to available spaces. Simulation experiments were conducted to evaluate the effectiveness of these systems, with a base case assuming drivers head to the nearest parking facility without guidance. ...
Parking challenges escalate significantly during large events such as concerts and sports games, yet few studies address dynamic parking lot assignments in these occasions. This paper introduces a smart navigation system designed to optimize parking assignments efficiently during major events, employing a mixed search algorithm that considers diverse drivers characteristics. We validated our system through simulations conducted in Berkeley, CA during the "Big Game" showcasing the advantages of our novel parking assignment approach.
... Researchers have introduced various parking assignment methods, including parking guidance systems, to simulate driver behavior and assess the impact of these systems. For instance, parking guidance systems proposed by Shin and Jun (2014) [3], aiming to reduce driver cruising time by directing them to available spaces. Simulation experiments were conducted to evaluate the effectiveness of these systems, with a base case assuming drivers head to the nearest parking facility without guidance. ...
... Researchers have introduced various parking assignment methods, including parking guidance systems, to simulate driver behavior and assess the impact of these systems. For instance, parking guidance systems proposed by Shin and Jun (2014) [3], aiming to reduce driver cruising time by directing them to available spaces. Simulation experiments were conducted to evaluate the effectiveness of these systems, with a base case assuming drivers head to the nearest parking facility without guidance. ...
Parking challenges escalate significantly during large events such as concerts and sports games, yet few studies address dynamic parking lot assignments in these occasions. This paper introduces a smart navigation system designed to optimize parking assignments efficiently during major events, employing a mixed search algorithm that considers diverse drivers characteristics. We validated our system through simulations conducted in Berkeley, CA during the "Big Game" showcasing the advantages of our novel parking assignment approach.
... This additional traffic caused by drivers searching for a free parking space is called "parking search traffic." In addition to the loss of valuable time, parking search traffic has additional negative consequences, such as greenhouse gas emissions, noise pollution, and a financial burden for the driver due to the waste of fuel (e.g., Perković et al., 2020;Shin & Jun, 2014;Shoup, 2006). Although there are multiple approaches to reducing private car use, such as the provision of apps that make other mobility services such as public transport or bike-sharing more convenient (e.g., Schulz et al., 2023Schulz et al., , 2021, it is not likely that private cars will lose its position as the most important means of transport in developed countries. ...
... Overall, there is a large body of scientific literature on smart parking. Various studies focus on a technical perspective of smart parking, such as the development and comparison of different sensors, cameras, and radar sensors, to monitor whether a parking space is free (e.g., Al-Turjman & Malekloo, 2019; Barriga et al., 2019;Idris et al., 2009;Perković et al., 2020), or the programming of a parking guidance algorithm (Shin & Jun, 2014). Other studies examine the potential economic and environmental impact of smart parking (e.g., Rodier & Shaheen, 2010). ...
Traffic caused by drivers searching for a free parking space has numerous negative effects, such as increased emissions and noise pollution. Innovative solutions can reduce these negative effects by providing car drivers with better information via a smart parking app. However, smart parking apps currently do not offer overarching solutions which support the entire parking process. Utilizing a service-dominant logic perspective, we examine why such overarching solutions do not emerge, whereas specialized ecosystems flourish. We follow a multiple case study approach and conduct qualitative interviews with three app providers and fourteen associated parking operators in Germany. Our results show how conflicting institutional arrangements at the micro, meso, and macro context levels lead to specialization. Our study deepens the understanding of how conflicting institutional arrangements affect the emergence of service ecosystems, drawing practical recommendations to overcome specialized smart parking apps in favor of overarching solutions.
... Te frst category of studies focuses on allocating slots based on user optimum. Shin proposed a smart parking guidance algorithm which supports drivers to fnd the most appropriate parking facility [20]. To suggest the most suitable parking facilities, he considered several factors, such as driving distance and walking distance. ...
... (19) end(20) Set the objective function as min ω 2 .(21) Repeat Step 2 to Step 19 and the solution of min ω 2 is ω * 2 . ...
Various solutions, such as parking reservation systems, have been proposed to alleviate the difficulty in finding parking slots. In such systems, parking requests are submitted in advance by drivers, and the systems will reserve appropriate parking spots for drivers if their requests are accepted. However, the parking slots may be allocated unreasonably, which may lead to a waste of space and time resources. In addition, there is a game relationship between operator’s profit (OP) and users’ benefits (UB), which may affect the sustainable development of the system, if balanced improperly. Given the drivers’ arrival and departure time and their parking preference, the paper proposes a periodic reservation and allocation mode (PRAM) and establishes a dual-objective binary integer linear model to solve the reservation and allocation problem. The model aims to maximize the comprehensive benefits of the operator and users and to take full advantage of parking resources. We proposed a TOPSIS-SA algorithm (Technique for Order Preference by Similarity to an Ideal Solution and Simulated Annealing algorithm) to solve our model. Numerical experiments show that our model performs better than the baseline models on all performance metrics such as total operating profit, users’ average walking distance, acceptance rate, and utilization of parking slots.
... Automobiles have brought convenience and comfort to people's lives but have also caused many signifcant urban problems, including increased parking demand and parking space constraints [1]. Compared with on-street parking, parking lots have become an important facility to efectively relieve parking pressure due to their zoning, advanced management methods, and user-friendly experience. ...
... Compared with on-street parking, parking lots have become an important facility to efectively relieve parking pressure due to their zoning, advanced management methods, and user-friendly experience. With the rapid emergence of the intelligent transportation system (ITS), research on parking lot systems has gradually intensifed, such as through the parking lot guidance algorithm [1,2], space allocation [3], and dynamic parking pricing [4]. Tese works concentrate on parking lot efciency and mobility, but fewer studies have emphasized safety inside parking lots, which is another critical consideration in ITS besides their efciency [5]. ...
Parking lots have many complex structures, diverse functions, and plentiful elements. The frequent flow of vehicles with narrow and dim spaces increases the probability of various traffic accidents. Due to the low severity and lack of relevant data, there is limited understanding of safety analyses for parking lot accidents. This study integrates multisource data to establish a Bayesian diagnostic model for parking lot accidents. The mutual information method is used to screen the possible influencing factors before modeling to reduce the subjectivity of Bayesian networks. Studying the cause and effect analysis of accidents provides diagnosis and prediction for property damage and event causes. This provides valuable correlation information between factors and accident characteristics, as well as consequences under the influence of multiple factor chains. As the developed model has good accuracy, this study proposes a parking lot safety evaluation system with a library of countermeasures based on the model results to ensure rigorous conclusions. The combination with ITS technology gives the system high scalability and adaptability in multiple scenarios.
... To solve this challenge is the main goal of this work. A smart parking system however also requires additional considerations like user experience (UX)-design or individual parking guidance where the goal is to propose different parking locations to different drivers so that the overall congestion is reduced and the utilization of space resources of a city is maximized [84]. Although there are interesting applications for AI in this field including evolutionary algorithms [4] as well as reinforcement learning [39], the question of parking guidance is out of scope for this work. ...
... For a broader view on parking including technical details of sensor connectivity, IoT and deployment details we recommend [55]. For deeper information regarding optimal parking guidance and allocation good starting points are [49,84]. In the following we introduce the most relevant concepts from previous literature regarding the time series forecasting scenario and the imperfect data scenario. ...
Finding an available parking spot in city centers can be a cumbersome task for individual drivers and also negatively affects general traffic flow and CO2 emissions. In the context of smart cities and the internet of things this problem can be mitigated by using available data to monitor and predict parking occupancy in order to guide users to an available parking location near their destination. With this goal in mind there arise multiple challenges of which we introduce selected ones to propose novel solutions based on machine learning. The focus of this work is to enable the usage of readily available and inexpensive data sources like parking meter transactions, opposed to expensive technology like in-ground sensors or cameras where the costs prevent a widespread coverage. Our proposed data sources do not directly monitor the actual parking availability but still provide enough signal for our algorithms to infer the real parking situation with high accuracy. As part of this work we developed a parking availability prediction system based on parking meter transactions that was deployed to 33 german cities. A main contribution of our work is the proposal of a novel way to generate labels based on the parking transactions and to use semi-supervised-, more specifically positive-unlabeled learning, to leverage the sparse signal in order to require as little data as possible. Additionally, we utilize and design novel methodologies in the area of transfer learning to learn simultaneously from different cities which leads to the previously seldom explored setting of combining transfer learning with positive-unlabeled learning. We therefore introduce a novel algorithm to tackle this problem type. We hope that our work enables the deployment of smart parking systems at lower costs and therefore leads towards the goal of smart parking guidance in smart cities.
... Parking selection has been studied extensively as well [25]. It has been modeled as a multi-input problem measuring the utility of a parking space by accounting for availability, driving duration, walking distance to the destination, parking cost, traffic congestion, etc [26]. ...
This paper gives a thorough overview of Solar Car Optimized Route Estimation (SCORE), novel route optimization scheme for solar vehicles based on solar irradiance and target distance. In order to conduct the optimization, both data collection and the optimization algorithm itself have to be performed using appropriate hardware. Here we give an insight to both stages, hardware and software used and present some results of the SCORE system together with certain improvements of its fusion and optimization criteria. Results and the limited applicability of SCORE are discussed together with an overview of future research plans and comparison with state-of-the-art solar vehicle optimization solutions.
... Thus, there is a consensus in the literature about the importance of minimizing cruising-for-parking (Inci, 2015). Potential solutions include parking guidance systems (Shin and Jun, 2014), parking reservation schemes (Liu et al., 2014), intelligent parking systems (Cao and Menendez, 2018;Najmi et al., 2021), or parking pricing schemes (Bifulco, 1993;Fosgerau and de Palma, 2013;Qian and Rajagopal, 2014;Liu and Geroliminis, 2016;Alemi et al., 2018;Liu, 2018;Zhang et al., 2019;Jakob et al., 2020;Gu et al., 2021;Rodríguez et al., 2022). Many of them are based on parking search models. ...
... With economic growth and household income increase, vehicles have become more popular owning to their attractive properties including comfortability and convenience (1). However, urban parking supply, i.e. the total number of parking spaces, is usually inadequate for limited land resources and expensive construction costs (2)(3)(4), especially in central business districts (CBD). The parking shortage increases cruising traffic volume (5)(6)(7), inducing unauthorized on-street parking (8,9) and even traffic accidents due to distribution, anxiety, stress, and tiredness of drivers in searching for available parking spaces (10,11). ...
With increasing vehicle ownership and utilization in urban areas, parking robot systems have become a promising tool to cope with both the parking difficulties and hazards in parking lots. With assistance of the parking robot systems, vehicles are not human-operated in parking lots but fetched by a parking robot to the target places. This study starts by depicting the parking robot allocations and movements consisting of empty-loaded and loaded trips as well as picking-up and setting-down operations. Then, with multi-stage processes aiming to minimize the empty-loaded and loaded travel time, respectively, a two-stage allocation model was proposed to assign parking robots to vehicles and allocate the vehicles with target places. Furthermore, a cellular automaton (CA) simulation was introduced and extended with additional priority rules to solve potential travel conflicts occurring in parking lots. Basing on a campus parking lot in Shanghai, China, the flowchart of the CA simulation was proposed to implement and validate the proposed allocation model. The results demonstrate that, compared with the one-stage allocation model, the proposed allocation model has the potential to decrease queue length and waiting time both at parking lot entrances and parking spaces, which may assist in design and operation of future parking lots.
... Parking Guidance (Routing) System is the key part of the SPS and provides an effective way to minimize parking time spent looking for parking by using dynamic traffic information [62]. In this part, we investigated the influence and effects of driver collaboration in search of parking, and for that reason, we have developed two cases (two strategies): ...
Finding parking spots in urban areas poses significant challenges due to the ever increasing complexities of the transportation endeavor, resulting in issues like traffic jams, higher fuel consumption, and environmental pollution. In this regard, this paper introduces an innovative Cooperative parking search strategy that relies on agent decision-making and Vehicle-to-Everything (V2X) communication. This approach allows vehicles to share real-time information regarding their parking intentions and available spots, enabling agents (representing vehicles) to collectively make informed decisions and optimize the parking search process. The proposed strategy aims to enhance the efficiency of parking searches by facilitating real-time information exchange through V2X communication. To demonstrate its effectiveness, we conducted a proof-of-concept implementation using OMNeT++ simulator and SUMO traffic generator to simulate real-world conditions in Laghouat City. The simulation considers a variety of parameters, including recommended parking distance, traffic congestion, and parking space availability. Numerical results show that agent cooperation can reduce the overall parking search time for all drivers by up to compared to alternative methods, including greedy and selfish approaches.
... The lidar sensor of the self-driving car can perform the signal person's task (Hou and Ai 2020;Zhao et al. 2019). Cars can park in the parking area without the support of a parking attendant (Shin and Jun 2014;Zhao, Liang, and Chen 2018). Moreover, since the work does not involve drivers, shuttle vans are not needed. ...
... Furthermore, the objectives of the system-oriented models were divided into three subcategories: (a) minimizing the total parking costs; (b) maximizing the parking revenues; and (c) determining the parking fees at each allocation time. With an objective of assigning each driver with the lowest-cost parking lot, Shin and Jun [8] formulated a user-oriented allocation model and M found the model achieves an efficient parking resource utilization. By simultaneously allocating the drivers with both the ideal and second-best parking lots, Tasseron and Martens [9] discovered the travel time decreases while the walking distances remain unchanged. ...
Parking reservation systems allocate large parking flows to popular parking lots, which may increase the queue length and waiting time at the entrances of those parking lots. To alleviate or even solve the queuing problem, this article proposes a moving amendment method to determine the allowable parking flow entering parking lots at each allocation time. Based on this, a system-oriented proportional allocation model is formulated with the consideration of parking lot entrance capacity constraints. With the proportional allocation model, the parking flow assigned to a parking lot is proportional to the entrance capacity of the parking lot. Then, an agent-based simulation is introduced to investigate the performance of the proportional allocation model. Finally, the simulation result of an empirical case study in the Wujiaochang central business district in Shanghai, China, shows that compared with an ordinary allocation scheme without the consideration of entrance capacity constraints, the proportional allocation model has potential to decrease the queue length and waiting time at parking lot entrances. The proposed proportional allocation model may assist in the design and operation of parking reservation systems.
... The benefits and drawbacks of both static and dynamic routing methods were explored. In [11],the first commercially available intelligent parking guidance system was introduced. The algorithm proposed for intelligent parking guidance took into account the criteria used to choose the parking spot. ...
... Parking recognition is an important component of automatic parking systems. With the continuous increase in car ownership, parking difficulties have become one of the serious problems faced by urban sustainable development [1]. Due to the continuous changes in the surrounding environment, especially in dark environments with insufficient lighting at night, there is a large area of blurred vision, and parking under such conditions becomes more difficult. ...
Parking space recognition is an important part in the process of automatic parking, and it is also a key issue in the research field of automatic parking technology. The parking space recognition process was studied based on vision and the YOLOv5 target detection algorithm. Firstly, the fisheye camera around the body was calibrated using the Zhang Zhengyou calibration method, and then the corrected images captured by the camera were top-view transformed; then, the projected transformed images were stitched and fused in a unified coordinate system, and an improved image equalization processing fusion algorithm was used in order to improve the uneven image brightness in the parking space recognition process; after that, the fused images were input to the YOLOv5 target detection model for training and validation, and the results were compared with those of two other algorithms. Finally, the contours of the parking space were extracted based on OpenCV. The simulations and experiments proved that the brightness and sharpness of the fused images meet the requirements after image equalization, and the effectiveness of the parking space recognition method was also verified.
... The model could enable the parking spaces to be used effectively and thus reduce the parking search time. Shin and Jun [22] set fixed weights for the factors of travel time, walking distance after parking, parking price, and traffic congestion levels in order to recommend the most suitable available spaces in parking lots. The parking simulation showed that it could improve parking utilization. ...
Intelligent parking services can provide parking recommendations and reservations for travelers. They are an effective method for solving the cruising for parking problems in big cities. This research conducted a sequential parking decision behavior survey and analyzed travelers’ parking choices and reservation behaviors at different stages of the travel process. Then, a parking recommendation model was established to consider the travelers’ psychological thresholds and the attention to parking factors. The effects of different parking recommendation schemes in different situations were further explored based on parking simulations. It was concluded that travelers were more willing to accept and use the parking recommendation system. A total of 56% of travelers chose to make parking reservations during the travel process. The satisfaction proportion of the psychological threshold for the parking reservation group was higher than that for the non-parking reservation group. A dynamic parking recommendation scheme with a regulation threshold can change the recommendation strategy according to the overall utilization of parking lots. The implementation of the scheme can not only improve travelers’ parking experience, but it can also effectively balance the utilization of parking resources. It can be applied to different parking utilization situations and produce good performance. The research results provide references for the design and application of intelligent parking services in order to solve parking problems.
... The simulation is performed in an environment that is closer to the real environment than in our previous study. Since an increase in the number of vehicles in a parking lot affects parking time, it is important to conduct the evaluation in an environment where the number of vehicles is large [9]. ...
Automated valet parking (AVP) systems aim to use automated driving technology to park a vehicle from the passenger’s boarding/exiting location to a parking space in a parking lot and recall the vehicle from the parking space to the boarding/exiting location. For multiple vehicles to move efficiently through a parking lot, travel must be mediated between each vehicle. We have proposed a driving control method that improves the efficiency of AVP by using the Spatio-Temporal Grid Reservation mechanism. We previously compared it with an autonomous driving, which showed that the proposed method improved the efficiency of vehicle movement when vehicles are entering small parking lots. In this paper, we modified our previous method to accommodate the increasing number of vehicles in a parking lot and created Spatio-Temporal Grid Model as a vehicle movement model. we evaluate this model by comparing it with Conflict Zone Model and MAPF Model created by the methods proposed in related studies, in addition to an autonomous driving model. We performed simulations varying the percentage of vehicles arriving at the parking lot and showed that Spatio-Temporal grid model improves the efficiency of vehicle movement when vehicles are entering and exiting the lot.
... Furthermore, the RPR pattern can improve the performance of route searching by sensing the road network environment and available parking spaces in real-time [53][54][55]. In this way, Chai et al. [56] proposed a dynamic parking guidance system that integrates parking destination switching and real-time traffic routing to minimize expected travel costs. ...
... Jong-Ho Shin and Hong-Bae Jun [16] introduced a smart parking guidance algorithm which provides actual time status of availability of parking in smart cities. This algorithm considers many parameters such as driving distance to the guided parking facility, expected parking cost, walking distance from the guided parking facility to destination, and traffic congestion due to parking guidance. ...
With the large increase in population, automated industries and need of vehicles, parking of the vehicles is becoming a critical issue in various cities. Unmanaged parking of vehicles leads to noise pollution, air pollution, traffic congestion. During peak hours, it is difficult task to find vacant parking lot and it becomes the major challenge for driver to park the vehicle. A lot of work is being done in the whole world to manage the efficient parking of vehicles. To give the clear overview about efficient parking system, we go through some existing studies over the period of 2009-2022 which proposed various parking solutions. This survey gives an exhaustive study of available parking solutions and also proposed som
... The simulation is performed in an environment that is closer to the real environment than in our previous study. Since an increase in the number of vehicles in a parking lot affects parking time, it is important to conduct the evaluation in an environment where the number of vehicles is large [9]. ...
p>Automated valet parking (AVP) systems aim to use automated driving technology to park a vehicle from the passenger’s boarding/exiting location to a parking space in a parking lot and recall the vehicle from the parking space to the boarding/exiting location. For multiple vehicles to move efficiently through a parking lot, travel must be mediated between each vehicle. We have proposed a driving control method that improves the efficiency of AVP by using the Spatio-Temporal Grid Reservation mechanism. We previously compared it with an autonomous driving model, which showed that the proposed method improved the efficiency of vehicle movement when vehicles are entering small parking lots. In the present paper, we evaluate our proposed method by comparing it with a vehicle movement model based on a method proposed in a related study, in addition to an autonomous driving model. We performed simulations varying the percentage of vehicles arriving at the parking lot and showed that the proposed method improves the efficiency of vehicle movement when vehicles are entering and exiting the lot.</p
... The simulation is performed in an environment that is closer to the real environment than in our previous study. Since an increase in the number of vehicles in a parking lot affects parking time, it is important to conduct the evaluation in an environment where the number of vehicles is large [9]. ...
p>Automated valet parking (AVP) systems aim to use automated driving technology to park a vehicle from the passenger’s boarding/exiting location to a parking space in a parking lot and recall the vehicle from the parking space to the boarding/exiting location. For multiple vehicles to move efficiently through a parking lot, travel must be mediated between each vehicle. We have proposed a driving control method that improves the efficiency of AVP by using the Spatio-Temporal Grid Reservation mechanism. We previously compared it with an autonomous driving model, which showed that the proposed method improved the efficiency of vehicle movement when vehicles are entering small parking lots. In the present paper, we evaluate our proposed method by comparing it with a vehicle movement model based on a method proposed in a related study, in addition to an autonomous driving model. We performed simulations varying the percentage of vehicles arriving at the parking lot and showed that the proposed method improves the efficiency of vehicle movement when vehicles are entering and exiting the lot.</p
... There are different ways to communicate parking information to drivers, as shown in Fig. 1. Several studies have envisioned a centralized system ( "guidance system") that takes as inputs curb availabilities on the one hand and travel destinations and parking preferences on the other hand, and then computes an optimal parking assignment [15][16][17][18][19][20] . ...
Delivery vehicle drivers are experiencing increasing challenges in finding available curb space to park in urban areas, which increases instances of cruising for parking and parking in unauthorized spaces. Policies traditionally used to reduce cruising for parking for passenger vehicles, such as parking fees and congestion pricing, are not effective at changing delivery drivers’ travel and parking behaviors. Intelligent parking systems that use real-time curb availability information to better route and park vehicles can reduce cruising for parking, but they have never been tested for delivery vehicle drivers. The current study tested whether providing real-time curb availability information to delivery drivers reduces the travel time and distance spent cruising for parking. A curb parking information system deployed in a study area in Seattle, Wash., displayed real-time curb availabilities on a mobile app called OpenPark. A controlled experiment assigned drivers’ deliveries in the study area with and without access to OpenPark. The data collected showed that when curb availability information was provided to drivers, their cruising for parking time significantly decreased by 27.9 percent, and their cruising distance decreased by 12.4 percent. These results demonstrate the potential for implementing intelligent parking systems to improve the efficiency of urban logistics systems.
... They propose a system of information and guidance parking that provides auxiliary users with information about the city's plans and regulations, as well as an estimate of displacement time. An algorithm for intelligent parking guidance was proposed by Shin and Jun [19]. The algorithm allows drivers to identify vacant spaces based on parking occupancy in real time. ...
Generally, dense urban areas suffer from local parking shortages: a limited supply coupled with a diffuse demand in both space and time. According to this plan, additional vehicles will be searching for available parking spaces, particularly during peak hours. Searching for parking disrupts the economic, environmental, and social sustainability of the city. The purpose of the paper is to optimize parking management, by guiding drivers who request a vacant space. Multi-agent systems can be used as an appropriate modeling approach for the development of such a smart parking guidance system. In order to verify and validate the model, simulations were performed in Tunis city-center. The numerical results show that smart parking guidance systems can manage parking areas more efficiently. It can reduce energy consumption and carbon dioxide emissions, increase revenues for parking managers and satisfy drivers' requirements.
... Shin and Jun [17] mentions an approach that would assist drivers in finding the most suitable parking space, taking into account the real-time status of parking facilities in the city. In order to suggest the most suitable parking space, driving factors to the guided parking facility, walking distance from the guided parking to the destination, the expected parking cost and the traffic jam due to parking guidance are considered in the proposed algorithm. ...
In Internet of Things (IOT)-based smart cities, negative reasons such as cost, energy and air pollution when searching for a parking space increase the importance of smart parking systems. In this study, a two-stage hybrid approach is proposed so that drivers can find a parking space that will consume the least time and energy. The first stage focuses on car parks having at least one free parking space located near the target address in an n diameter circumference, which are also open for business. An AVL tree-based hierarchical structure is created with driving time from the starting point to each car park and walking time from each car park to the destination, and it focuses on the most appropriate car park. In the second stage, the most suitable parking space is searched and made available, if found, in hierarchical parking monitoring system. In order to demonstrate the effectiveness of the approach, the results compared with hierarchical, hierarchical Binary Search Tree (BST) and non-hierarchical solutions in terms of energy and time performance are shown on a simulation. Proposed approach gave the best result with 99% energy efficiency. In addition, a dynamic cloud-based reservation system was proposed for the parking lot determined in the study.
... Among the control strategies devised to efficiently manage the parking process and to present intelligent solutions to drivers, we can mention the smart parking guidance algorithm proposed in Shin and Jun (2014), in order to suggest drivers, the most appropriate parking facility on the basis of the real-time state of parking lots, the driving distance to the facility, the walking distance from the facility to the destination, the parking cost, and the traffic congestion level. Moreover, a parking assignment strategy is proposed in Tran Thi Kim et al. (2020) to minimise parking expenses and to balance parking demand among multiple parking lots, both public and private, in case some are overloaded, and others are underutilised. ...
There have been tremendous developments in theories and technologies in control for smart systems. In this paper we review applications to various systems that are crucial for the future of smart cities, for example enterprise and manufacturing systems, transportation systems, energy systems, and data centres. Beyond discussing the existing technological trends and the methodological approaches developed so far for managing and controlling such systems, we also provide visions on the future challenges for these systems in these various aspects.
... Indeed, there has been a boom of new business models including transaction brokers and information-gathering platforms (Parkopedia, SpotHero, Yellowbrick, Bestparking) that provide parking information-related services. The parking research literature has analyzed drivers' search strategies (Polak and Axhausen, 1990;Thomson and Richardson, 1998;Bonsall and Palmer, 2004;Karaliopoulos et al., 2017) and examined more broadly the theoretical or simulated advantages of different designs and applications of innovative technology to parking guidance systems (Caicedo, 2010;Wang and He, 2011;Kokolaki et al., 2012;Shin and Jun, 2014). However, parking research to date has evolved separately from the consumer behavior literature and has tended to overlook the importance of just how consumers acquire information and transform it into useful knowledge that determines their choices. ...
Parking regulations have been widely adopted by cities as a tool to tackle traffic-related externalities. Both researchers and practitioners have proposed parking policy interventions that tend to rely on the assumption that parkers have perfect information about the availability of parking options and their characteristics (prices and quality) when determining consumers’ behavior. However, research shows that when information acquisition (search) is costly it is rational for consumers not to be fully informed at the expense of their taking non-optimal decisions, with negative welfare implications.
We conduct an empirical study of the level of knowledge and information held by drivers in the car parking market. We draw on a survey conducted with 576 garage customers in Barcelona to estimate different regression models to assess how drivers transform information into actual knowledge, identifying the factors that aggravate/mitigate misinformation and misperception (subjective information levels and its accuracy). We find that parkers know little about available parking alternatives and their prices, and the accuracy of their knowledge is poor and biased towards prioritizing curbside parking. Costly search does not help drivers increase their knowledge levels, with garage facilities’ and surrounding areas’ characteristics playing a relevant role. We also find that garages have effective obfuscation strategies to keep drivers uninformed and exploit their localized market power by reducing price saliency and increasing fee complexity. Our results suggest that information should be carefully considered in the design and implementation of parking policy interventions and transport information systems, in order to avoid undesired market distortions.
... Quickly finding a vacant space in a parking lot is difficult if not impossible, especially on weekends or public holidays [10,11]. Seeing these conditions, this study seeks to create a parking monitoring system that functions to display the number of quotas and the location of empty parking lots, so that it is expected to eliminate vehicle buildup at the parking entrance and also assist users in finding the location of the available parking locations. ...
Parking area is one of the facilities that must be available in specific or public places such as parks, recreation areas, malls, offices, business areas and agencies, and other places. Currently, the existing parking facilities generally do not provide information on the presence or absence of vacant parking spaces. This often causes problems in finding parking spaces, where vehicle users, especially four-wheeled vehicles (cars) will look for empty parking spaces by walking around so they can spend a lot of time. This study aims to create a parking lot monitoring system that is equipped with a microcontroller-based monitoring system so that vehicle users can find out how many parking spaces are available and where the parking lot is located. This parking monitoring system was developed using the prototyping method so that determining the need for the actual system is easier to realize. The test results of this device show that this prototype can provide information regarding the number of vacant parking lots and their locations. The impact of this research is that it can eliminate the accumulation of vehicles in front of the parking lot entrance, because vehicle users can easily and quickly find a parking location.
... Beside tracking parking slot's availability, ML algorithms were used to maximise utilisation of parking facilities, minimise customers' searching time for available parking space [19,35,48] and create efficient smart parking pricing systems [32,45,51]. For example, Aydin et al. [9] proposed a smart parking system that can assist users in finding an available parking space and to minimise the time spent in locating the nearest available car park using the genetic algorithm. ...
Integration of artificial intelligence (AI), Internet of Things (IoT) and Cloud computing technologies in a unified system to address a real-world problem is challenging and of high demand. This chapter discusses the processes, challenges and solutions concerning designing an airport smart parking system. IoT parking sensors, Open Automatic License Plate Recognition (OpenALPR) library, and the IBM cloud-based IoT platform are integrated to tackle technical challenges, including the automatic identification of plate numbers, models, and colours of vehicles in parking spaces, in both indoor and outdoor parking environments. The chapter also addresses several issues related to the system, i.e., the system architecture design, the selection of sensing technologies and hardware and software platforms, while taking into account specific characteristics of IoT and AI technologies. Although the proposed system is developed for the airport smart parking problem, the discussion is relevant to problems in other domains from the system design and integration perspectives.
In modern societies, the need for a high degree of mobility in transportation systems is increasingly evident. Consequently, the establishment of a sustainable transport system that aligns with social needs, economic growth, and environmental concerns becomes paramount. This chapter aims to shed light on the role of transport in sustainable development and the challenges associated with achieving sustainable mobility. A thorough analysis of the primary factors contributing to the growing demand for mobility is provided. Additionally, the chapter examines the key decision-makers involved in shaping transportation systems, with a particular focus on the pivotal role of intelligent transportation systems. These systems are considered a vital component in addressing road congestion and enhancing overall traffic performance, such as reducing congestion and noise levels while promoting sustainable mobility.
This paper examines how to outline and adopt innovative business models for the Smart Cities of the future. Smart Cities are intelligent and efficient communities and ecosystems employing digital technologies to respond a growing waste of resources, unsustainable environmental impact, and inefficiency in traditional processes. Considering the greatest benefits of Smart Cities on economies, societies, and environment, many countries have now introduced national Smart City projects in order to transform life, improve business operations and market competitiveness. However, despite growing interests towards Smart Cities, it remains still difficult to adopt this paradigm due to digital transformation, interaction strategies, social and cultural problems. Therefore, this paper aims to break down the barriers to these problems and support the literature and management to understand how to implement profitable business models for Smart Cities of the future. Specifically, we identify four main areas characterizing Smart Cities (i.e., Smart Mobility, Smart Living, Smart Energy, and Smart Public Ecosystems) where digital technologies have shown greater progress with large savings. For each area, multiple case studies have been discussed and Business Model Canvases have been developed for generalizing effective methodological approaches toward efficient implementation of Smart City paradigm. Results are threefold. As for digital transformation problems, we show how digital technologies (e.g., Cloud, IoT, Big Data and AI) are applied profitably through innovative business models; as for interaction strategies problems we indicate how to organize innovative ecosystems involving public and private actors to promote Smart Cities; as for social and cultural problems we delineate change management and communication practices useful to instill in all stakeholders a culture towards the Smart City. With these findings the paper aims at enriching scientific knowledge about the Smart City Paradigm by means of a business model perspective and to offer public administrations insightful guidelines for the transition toward Smart Cities.
Since the introduction of Bitcoin and Ethereum, blockchain introduced new ways to handle payment and dealing with financial transactions. From 2009 till now, several blockchain systems were developed. However, the main issue for each blockchain is to know where to use it and what the best use case fits with it. Transaction per second (TPS) and confirmation time (CT) give the possibility to evaluate the speed and performance of each blockchain. It demonstrates the speed of blockchain in processing any transaction and saving it to the ledger. This work reviews and presents the current status of the state-of-the-art blockchain performance.
The way the vehicles are placed in a parking space partitioned into parking slots reachable through internal routes means that the available space is not used at best of its capacity. In this paper, a solution model is proposed, adopting a chequered parking layout, which aims at optimizing the available surface and, consequently, increasing the capacity in terms of available parking slots. To this aim, an isomorphism with the game of fifteen is found and a solution is proposed.KeywordsParkingQueueChequered parkingThe game of fifteen
With the number of motor vehicles in cities rapidly increasing, scheduling and management in large parking lots need to be timelier and more accurate, and vehicle detection technology plays a crucial role in this process. Magnetic sensors have attracted enormous interest in vehicle detection owing to their low cost and easy installation. However, most of the studies extract features manually, and the results are given by the potential difference in magnetic signal which is susceptible to environmental interference. Moreover, each parking space corresponds to a sensor, which is costly to deploy and maintain in a large parking lot. The main challenge lies in the difficulty of eliminating the interferences from vehicles in adjacent parking spaces that decrease the accuracy. In this article, a deep learning parking detection algorithm based on
W
-shape magnetic wireless sensor network is proposed for large parking lots with vertical parking spaces. The number of required sensors is greatly reduced by analyzing the sensor deployment which can greatly reduce the costs accordingly. To improve the adaptability of the algorithm in different environments, the deep learning model is trained with the collaborative information from multiple sensors. Test in the actual scene shows that the algorithm can significantly reduce costs and improve adaptability while ensuring high detection accuracy. Thus, it is easier to implement in large parking lots.
Nowadays, with the increasing number of vehicles in the urban environment, finding a parking space has become an important and challenging issue. Vehicles may have to spend a lot of time looking for a parking space, which can lead to excessive fuel consumption, area traffic congestion, increased air pollution, and even driver impatience and immorality. To solve this problem, this article has used Roadside-to-Vehicle/Vehicle-to-Roadside (R2V/V2R), Roadside-to-Roadside (R2R) and Parking-to-Roadside/Roadside-to-Parking (P2R/R2P) communication in Vehicular Ad-hoc Network (VANET) and learning automata with variable actions to select and reserve the most suitable parking space. The performance of the proposed method was evaluated using computer simulation. The simulation results showed the efficiency of the proposed method in terms of improving service quality, reducing computational overhead, and making optimal use of parking resources in the city compared to existing methods. The proposed algorithm helps reduce air and noise pollution by reducing traffic congestion caused by parking space searches, and also helps increase the use of parking facilities efficiently.
Parking activities are one of the major problems in modern cities' transportation management systems. It is a complex and expensive process, and its price is determined not only by service tariffs, but also by resources invested in finding and traveling to vacancy spaces. Parking problems in larger cities can lead to increased air pollution, noise, driver time losses, stress and congestion. Parking guidance information systems (PGIS) have been successfully used to improve services and reduce harmful effects. Using case-based reasoning methodology in parking management and guidance systems could improve services and reduce required resources. Data collected from the existing drivers’ experience can be used by PGIS to generate solutions in free parking space search.
During a planned special event (PSE), vehicular and pedestrian movements are concentrated around the PSE venue for short periods, leading to potential conflicts and safety issues. Vehicles tend to park as close as possible to the venue for the convenience of attendees. Taking into account the characteristics of PSE traffic patterns, a strategic vehicle parking planning model is proposed to integrally optimize the assignment of parking lots and inbound/outbound routes around the venue. Two prioritized objectives were considered for traffic safety and for the convenience of attendees. The proposed model was first validated in a small-scale example, and then adopted in a real-world case that took place in Taiyuan, China. The resulting parking plan presented an efficient reduction in the conflict points between vehicular and pedestrian movements, leading to an acceptable average walking distance for attendees. To evaluate the impact of different management preferences on the parking plan, a series of weights for conflict points were set according to potential conflict locations, occurrence times, and types. The results demonstrated that the number of conflict points with higher weights could be effectively reduced by the parking plan.
The dynamic parking spot allocation via "Internet+" become a feasible approach to solve the problem of cruising-for-parking. The traditional research mainly focuses on the dynamic mechanism
design without considering the timing of parking matchings. In the random dynamic environment, users may obtain more high-quality parking slots by appropriate delay after arriving near their destinations. However, it depends on the current parking supply and demand pattern. In this paper, an intelligent delay matching strategy was proposed for the first time. The problem was formulated by the multi-agent deep Q learning (M-DQN), and each user was recognized as an agent. When users entered the allocation pool, the system applied the Hungarian algorithm for parking slot matching. As the total number of agents was variable, the framework of centralized training and distributed execution was proposed to realize the cooperative optimization of multi-agents. To compare the effect of the intelligent delay strategy, the paper designed the zero-wait strategy Greedy and the maximum-wait strategy Max Delay. In numerical experiments, three different parking scenarios were designed by the measured parking data of Siping Road Campus of Tongji University, China. During the morning rush hour on weekdays, Greedy is the best strategy, the average total parking time of M-DQN and Max Delay represent significant increases compared with Greedy. During the off-peak hour on weekdays, the average total parking time of M-DQN is reduced by 23.8% and 22.4% respectively compared with Greedy and Max Delay. During the evening rush hour on weekdays, the average total parking time of M-DQN is reduced by 12.8% and 14.5% respectively compared with Greedy and Max Delay. M-DQN can learn the optimal delay matching strategy according to the states of parking supply and demand. The results show the proposed delay matching strategy and the multi-agent deep reinforcement learning method can effectively reduce the users’ average parking time and walking distance, under the environment with balanced parking supply and demand. Moreover, the scenarios with higher parking turnover rate have the better matching effect. However, there are still some limitations in the application of the delay strategy, which is not suitable for the scenario with tight parking supply and low parking turnover rate.
A rapid rise in the number of cars running on roads has increased the need for parking spaces due to which many difficulties are faced by drivers to find a parking space in car parking areas in big cities. Utilizing the capabilities of computer vision, the authors propose an automated parking space detection and management system. This chapter presents an approach for classifying parking lots either filled or empty based on the Convolutional Neural Network (CNN) running on the administrator’s or owner’s system. Our application provides an efficient and robust way of occupancy detection in various light conditions, weather conditions, presence of shadows, and partial occlusions. The authors used a publicly available CNRPark dataset that contains nearly 9000 images captured from various cameras in different conditions and with obstacles. Along with this, the LSTM model is trained based on the classification data provided by the CNN model collected over a long period to predict the future availability of parking lots based on the specific day of the week, festival, and national holiday. Additionally, a deep learning model is used as an alarming system to detect unwanted events occurring in the parking space. This security system which detects oddity helps to improve the reliability of the system and cameras. No manual monitoring is required due to this anomaly detection system which takes the same input as the slot detection model. All these features make our system more efficient, reliable, and cheaper than traditional methods of parking space management systems such as barriers, sensors, etc. This system is served to the user through a web app and Android app from where the user can gather useful information.KeywordsDeep learningParking space detectionConvolutional neural networkAnomaly detectionLSTM
Due to the observed growth in the number of vehicles in recent years, a parking spaces availability problem has occurred. In this paper, a proposed system is implemented to, achieve a low complexity autonomous parallel parking system, to decrease traffic congestion, achieve less fuel consumption, and prevent vehicle damage like scratches and other damages due to miscalculations from drivers. The target is to minimize the parking time using an autonomous system that leads to an increase in the efficiency of traffic flow. The algorithm will be implemented using a Raspberry-PI microcomputer. A hybrid hardware and software system will be used with a low error percentage.
A planned special event (PSE), such as a sports game or a concert, can greatly affect the normal operations of a transportation system. To facilitate traffic, the road network is usually reconfigured, which could include road closures, reversed lanes, and limited access to parking facilities. For recurring PSEs, event-goers are often provided with recommended routes to designated parking areas in advance. Such network reconfiguration and route and parking recommendations are, however, often ad hoc in practice. This paper focuses on the PSE traffic planning problem. We propose to simultaneously consider parking, ridesharing, and network configuration. The problem is formulated as an optimization problem with integer decision variables. We developed a flow-based traffic simulation tool that is able to incorporate parking and lane changing (which cannot be ignored around ridesharing drop-off locations) to evaluate the objective function. We also developed effective and efficient heuristic solution algorithms. The models and algorithms are tested using the real network and traffic data from Super Bowl XLIX in 2015. The results show that our methods and approaches are able to produce an effective comprehensive traffic plan with reasonable computation time. For the Super Bowl XLIX case study, the resulting optimal plan is able to save 39.6% of the total vehicle-hours associated with default network configurations. Sensitivity analysis has also been conducted with respect to the compliance rate of travelers following recommended routes. It is found that the resulting near-optimal PSE traffic plans are able to tolerate some uncertainty in the compliance rate.
In smart parking guidance systems, the ability to estimate the availability of vacant parking spaces is important to make effective guidance. In this paper, we propose a general architecture for building crowdsensing-based parking guiding system, in which the occupancy state of parking lots can be detected by smart vehicles equipped with sensors and wireless communication devices, or by parking meters and parking fee-paying terminals, and the state information can be used to estimate the probability of finding available spaces for incoming smart vehicles. Five representative scenarios that can be used in such a framework were investigated. The problem to estimate the availability of parking spaces in each scenario was modeled as an M/M/c/c queuing problem with closed-form analytical solutions. The scenarios were validated in a simulation platform and their performance in various parking environments was investigated. Experimental results revealed that the crowdsensing-based parking prediction method can lead to 30.91% or more relative improvement on average estimation error than steady-state prediction in typical parking environments.
With the rapid development of urbanization and the swift rising of the number of vehicles in cities, the process of finding a suitable parking space not only wastes a lot of time but also indirectly aggravates the problem of traffic congestion. To assist the decision-making and alleviate the pain of parking, researchers propose a variety of methods to improve the parking efficiency of existing parking lots. Different from existing studies, we address the parking issue from an incremental rather than a stock perspective. In this paper, we propose a LSTM-based prediction model to make full use of contract parking spaces, which are characterized by the periodic departure time and complementary to the idle space during the peak period of the city. In addition, we utilize multi-source data as the input to improve the prediction performance. We evaluate our model on real-world parking data involved with nearly 14 million parking records in Wuhan. The experimental results show that the average accuracy of the ParkLSTM prediction reaches 91.091%, which is 11.19%–19.70% higher than other parking behavior prediction models.
This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments.
With the developing world, cities have begun to become smarter. Smart parking systems, with the ever-increasing number of vehicles, are among the important matters in smart cities. The reason for this is that the search for parking spaces that are already insufficient, brings along a serious cost, air pollution and stress issues. In this study, a new approach that attempts to forecast the parking lot occupancy rate in the short- and medium-term with its deep learning-based Gated Recurrent Units (GRU) model was proposed. Initially, data belonging to 607 carparks located in the city of Istanbul in Turkey, and weather data have been collected, and a multivariate time series data set has been created. In the second stage, to forecast the parking places that would be available in the short- and medium-term, the GRU model was used in the system proposed. To show the effectiveness of the model, the results obtained through the 27 different models were compared by means of the Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM), which were some other sequence models. According to the experimental results made on the weather data obtained from İSPARK dataset and AKOM, the our proposed GRU model achieves 99.11% accuracy gave the best results with 0.90 MAE, 2.35 MSE and 1.53 RMSE metric values. Experimental results obtained with various hyperparameters clearly demonstrate the success of the GRU deep learning model in prediction parking occupancy rates.
We propose a new "smart parking" system for an urban environment. The system assigns and reserves an optimal parking space for a driver based on the user's requirements that combine proximity to destination and parking cost, while also ensuring that the overall parking capacity is efficiently utilized. Our approach solves a Mixed Integer Linear Program (MILP) problem at each decision point in a time-driven sequence. The solution of each MILP is an optimal allocation based on current state information and subject to random events such as new user requests or parking spaces becoming available. The allocation is updated at the next decision point ensuring that there is no resource reservation conflict and that no user is ever assigned a resource with higher than the current cost function value. Implementation issues including parking detection, reservation guarantee and Vehicle-to-Infrastructure (V2I) or Infrastructure-to-Vehicle (I2V) communication are resolved in the paper. Our system can save driver time, fuel and expense, while reducing the traffic congestion and environment pollution. We also describe a deployment and testing pilot study of the system in a garage at Boston University (C) 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Program Committee
Operators of parking guidance and information systems (PGIS) often encounter difficulty in determining when and how to provide reliable car park availability information to drivers. Reliability has become a key factor to ensure the benefits of urban PGIS. The present paper is the first to define the guiding parking reliability of urban parking variable message signs (VMSs). By analyzing the parking choice under guiding and optional parking lots, a guiding parking reliability model was constructed. A mathematical program was formulated to determine the guiding parking reliability of VMS. The procedures were applied to a numerical example, and the factors that affect guiding reliability were analyzed. The quantitative changes of the parking berths and the display conditions of VMS were found to be the most important factors influencing guiding reliability. The parking guiding VMS achieved the best benefit when the parking supply was close to or was less than the demand. The combination of a guiding parking reliability model and parking choice behavior offers potential for PGIS operators to reduce traffic congestion in central city areas.
Parking is becoming an expensive resource in almost any major city in the world. Current technically advanced solutions for parking management are concerned with the application of secured wireless network and sensor communication for parking reservation. Moreover new rules concerning financial transactions in mobile payment allow the definition of new intelligent frameworks that enable a convenient management of public parking in urban area. The paper discusses the conceptual architecture of IPA (Intelligent Parking Assistant) which aims at overcoming current parking management solutions and thereby becoming a leading paradigm for the so called “smart cities”.
Parking Guidance and Information (PGI) signs are thought to enable a more efficient use of the available parking stock. Despite the installation of PGI systems in many cities and their operation for a number of years, there is a lack of reliable evidence of the size of the benefits that these systems can achieve. This paper describes the development of driver parking choice models (both during the journey and pre-trip) and the implementation of these models in the existing network traffic simulation model RGCONTRAM. Besides quantifying the effects of the PGI system on both the drivers seeking suitable parking spaces and the parking stock itself, this also enables quantification of the impact of parking choice on the wider network. Factors influencing PGI effectiveness are described and conclusions are drawn that illustrate the potential of PGI to induce the demand to spread more efficiently across the parking stock.
In metropolitan areas, parking management influences drivers search time and cost for parking spaces, parking revenue, and traffic congestion. The wide deployment of wireless parking meters with sensing and communications capabilities allows the parking authority to monitor the state of each parking space in real time and optimize the parking management.
In this thesis, we study state-of-the-art parking policies in smart parking systems, and show that the smart parking system needs to be "smarter". Our design goals of the smart parking systems include: (1) simplify the operations of parking systems, (2) improve drivers' satisfaction, (3) increase parking revenue, and (4) alleviate traffic congestion. Through analysis and simulations, we first show that the proposed reservation-based parking policy has the potential to achieve the above goals. We then model the behavior of both service providers and drivers in smart parking systems, and explore the dynamic pricing scheme to achieve the goals in smart parking system design.
Furthermore, we design and implement a prototype of Reservation-based Smart Parking System (RSPS) that allows drivers to effectively find and reserve the vacant parking spaces. With the real time tracking of parking status via various sensing technologies, a smart parking system will dynamically update the parking price according to the physical parking status, and the parking price will affect drivers decision on parking slot selection, therefore, affect the parking status. A smart parking system can be regarded as a full-fledged cyber-physical system (CPS). Through extensive experiment based on real traffic traces and a real-world parking map, the results show that the proposed reservation-based parking policy has the potential to simplify the operations of parking systems, as well as alleviate traffic congestion caused by searching for parking.
Adviser: Lisong Xu and Wenbo He
Suppose curb parking is free but all the spaces are occupied, and off-street parking is expensive but immediately available. In this case, you can cruise to find a curb space being vacated by a departing motorist, or pay for off-street parking right away. This paper presents a model of how drivers choose whether to cruise or to pay, and it predicts several results: you are more likely to cruise if curb parking is cheap, off-street parking is expensive, fuel is cheap, you want to park for a long time, you are alone in the car, and you place a low value on saving time. The model also predicts that charging the market price for curb parking—at least equal to the price of adjacent off-street parking—will eliminate cruising. Because the government sets curb parking prices, planners and elected officials strongly influence drivers’ decisions to cruise. The failure to charge market rates for curb parking congests traffic, pollutes the air, wastes fuel, and causes accidents. Between 1927 and 2001, studies of cruising in congested downtowns have found that it took between 3.5 and 14 min to find a curb space, and that between 8 and 74 percent of the traffic was cruising for parking.
In this paper, we present PARKAGENT, an agent-based, spatially explicit model for parking in the city. Unlike traditional parking models, PARKAGENT simulates the behavior of each driver in a spatially explicit environment and is able to capture the complex self-organizing dynamics of a large collective of parking agents within a non-homogeneous (road) space. The model generates distributions of key values like search time, walking distance, and parking costs over different driver groups. It is developed as an ArcGIS application, and can work with a practically unlimited number of drivers.The advantages of the model are illustrated using a real-life case from Tel Aviv. Taking detailed data from field surveys, the model is used to study the impact of additional parking supply in a residential area with a shortage of parking places. The PARKAGENT model shows that additional parking supply linearly affects the occurrence of extreme values, but has only a weak impact on the average search time for a parking place or the average walking distance between the parking place and the destination.
In this paper, we present PGS, a parking guidance system based on wireless sensor network(WSN) which guides a driver to an available parking lot. The system consists of a WSN-based VDS(vehicle detection sub-system) and a management sub-system. The WSN based VDS gathers information on the availability of each parking lot and the management sub-system processes the information and refines them and guides the driver to the available parking lot by controlling a VMS(Variable Messaging System). The paper describes the overall system architecture of PGS from the hardware platform to the application software in the view point of a WSN. We implemented the WSN based VDS of PGS and experimented on the system with several kinds of cars. The experimental results show that PGS succeeds in detecting various kinds of cars and the predicted battery life-time using measured current profiles is over 5 years.
Intelligent parking services that help drivers with reservation of a parking spot, navigation and automated payment have reached the deployment phase. These services may provide significant benefits to drivers and municipalities. Drivers may experience an increase in comfort and lower and more reliable travel times, while cities may expect a reduction in search traffic, congestion and emissions. But how large are these benefits, and how do they compare to the benefits of more traditional parking guidance and information systems, such as panels that indicate the number of available places in car parks? This paper addresses these questions by conducting a simulation study for a large city in the Netherlands and comparing the effects of the new and the traditional approach.
We propose a “smart parking” system for an urban environment based on a dynamic resource allocation approach. The system assigns and reserves an optimal resource (parking space) for a user (driver) based on the user's objective function that combines proximity to destination with parking cost, while also ensuring that the overall parking capacity is efficiently utilized. Our approach solves a Mixed Integer Linear Program (MILP) problem at each decision point in a time-driven sequence. The solution of each MILP is an optimal allocation based on current state information and subject to random events such as new user requests or parking spaces becoming available. The allocation is updated at the next decision point ensuring that there is no resource reservation conflict, that no user is ever assigned a resource with higher than the current cost function value, and that a set of fairness constraints is satisfied. We add an event-driven mechanism to compensate for users with no assignment that are close to their destinations. Simulation results show that using this “smart parking” approach can achieve near-optimal resource utilization and significant improvement over uncontrolled parking processes or state-of-the-art guidance-based systems.
The concept of urban parking guidance information system is briefly
given on the paper. From a different point of view, the purpose of the
system is set forth, and the basic functions of the system are analyzed.
Then a framework for the system design and module design features are
put forward, even a framework for the system design is given from the
management level and technical level. Finally, a parking guidance
information system development is put forward combining with the final
status of China's largest city parking and traffic congestion situation.
The time spent searching for free parking spaces can produce considerable environmental pollution. Information on parking availability can be a powerful instrument for reducing these search costs. This paper develops a demand assignment model to evaluate the benefits of manipulating information with the objective of reducing the time and distances involved in finding a parking-place; including the walking distances involved. Using the full search procedure it was found that improvements of some 10% in efficiency could be achieved, but only at high computational costs. A genetic algorithm was programmed that increases the possibility of finding the optimum information conditions that can be translated into lower emissions of toxic greenhouse gases.
This paper presents car-parking guidance with fuzzy knowledge-based decision making. The characteristic knowledge of all parking spaces is subjectively quantified via the fuzzy linguistic sets such as walking distance from parking place to building entrances, car safety, shade from sunlight outdoors, etc. With fuzzy definitions on those characteristics of parking space, the method of the ordered weight averaging can be applied to determine the truth value of the proposition: most desired characteristics of parking space are the characteristics of parking space to which the driver is being guided. The truth values of each parking space are to be used to rank all the available parking spaces. The parking space which has the maximum of the truth value is selected as the best parking space. Accordingly, the direction to the best parking space is guided in real-time by the traffic lights at intersections in parking lots for the drivers approaching. For viability of the proposed methodology, a model of real parking lots was used to simulate the interaction of the drivers to signs of traffic lights in real-time implementation.
This paper reviews published evidence of the effects of dynamic information and guidance on drivers’ choices of car parks. A major conclusion is that overall response levels to dynamic information are much lower than might be expected. Behavioural generalizations are difficult due to the varying nature of the systems being developed as well as the studies that have been undertaken. The lack of conclusions able to be generalized highlights the complexity of the parking choice process. Wide variations in awareness and usage rate were found between different groups of drivers, including age, gender, trip purpose and frequency. Explanations of the responses of drivers to PGI systems can be made by considering the drivers’ level of knowledge, their ability to interpret information as well as their preference for different types of information.
Curb parking is an indispensable part of urban public parking system. A reasonable curb parking pricing scheme makes contribution to improve the use efficiency of curb parking and to reduce traffic congestion. This paper analyzes the parking choice behavior from the micro-aspects, and the choice utility function is established to combine with the travel time, search time, waiting time, access time, and parking pricing. Through the utility function, the Probit-based parking choice behavior model is formulated. Based on that, the curb parking pricing model is proposed by considering the constrained conditions. Finally, the incremental assignment algorithm of the model is designed and the model is applied to the parking planning of Tonglin, China. The results show that the proposed model has practicality and reliability in the practical operation.摘要路内停车是城市公共停车的重要组成部分, 合理的路内停车定价对于提高停车场使用效率, 缓解城市交通拥挤均有积极作用, 本文微观上分析车辆停放的选择过程, 结合车辆停放者的行程时间、停车场搜索时间、停车等待时间、出口时间和停车场自身费用建立当前停车场的选择效用函数, 通过效用函数建立了车辆停放者的概率选择模型, 通过考虑停车选择的约束条件, 在提高整个停车设施使用效率的前提下建立路内停车定价模型。结合容量加载方法进行求解, 并给出铜陵市路内停车定价优化模型的实例, 实例证明了模型和算法具有实用性和可靠性。
In 2000, the average driver in US metropolitan areas endured 27 hours of traffic delays, a rise from 7 hours in 1980. In many other countries, traffic delays are considerably worse than in the United States, and in developing countries urban traffic congestion is increasing with alarming rapidity. For fifty years, economists have been advocating congestion pricing as the way to deal with urban traffic congestion; but today, even after some successes, congestion pricing is encountering considerable political resistance. The authors of Alleviating Urban Traffic Congestion advocate active consideration of more microscopic policies that attack the problem at the scale at which actual policy decisions are made. Microscopic models, rather than macroscopic models that are too simplified and too aggregated, they argue, will lead to the analysis of a wider and more creative range of policies, at least some of which should work well and be politically acceptable. After developing the themes of the book, the authors illustrate them by examining some areas of urban transport policy that have been neglected by the macroscopic approach. These include downtown parking policy, the encouragement of bicycling, the staggering of work hours by dominant employers, and the use by medium-sized cities of a "multimode" ticket that charges cars entering the city center a toll equal to the transit fare. The reorientation of urban transport analysis that they advocate will by no means eliminate traffic delays but should speed up the adoption of a richer, more flexible, and ultimately more effective set of policies to alleviate urban traffic congestion.
The search for free parking places is a promising application for vehicular ad hoc networks (VANETs). In order to guide drivers to a free parking place at their destination, it is necessary to estimate the occupancy state of the parking lots within the destination area at time of arrival. In this paper, we present a model to predict parking lot occupancy based on information exchanged among vehicles. In particular, our model takes the age of received parking lot information and the time needed to arrive at a certain parking lot into account and estimates the future parking situation at time of arrival. It is based on queueing theory and uses a continuous-time homogeneous Markov model. We have evaluated the model in a simulation study based on a detailed model of the city of Brunswick, Germany.
This paper proposes a smart parking system to solve the problem of unnecessary time consumption in finding parking spot in commercial car park areas. A parking reservation system is developed in such a way that users book their parking spots through short message services (SMS). The SMS sent will be processed by a wireless communication instrumentation device called micro-RTU (Remote Terminal Unit). This micro-RTU will reply the confirmation of booking by giving the details of reservation like password and lot number. The password will be used to enter the parking area and valid for a certain period of time. The system is fully automated with the use of the Peripheral Interface Controller (PIC). This microcontroller is capable in storing information of empty parking spaces, provide passwords as well as allowing or denying access to the parking area. A prototype of a car park system has been designed to demonstrate the capability of the proposed work. The demonstration has proven the capability of the system to reserve the parking, gain entry to the parking area and hence eliminates the hassle of searching empty parking lots.
Operators of parking guidance and information (PGI) systems often have difficulty in determining the best car park availability information to present to drivers in periods of high demand. This paper describes a behavioural model of parking choice incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system.Relationships were developed for estimating the arrival rates at car parks based on trip patterns, driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. Drivers' perceptions of waiting times at car parks were assumed to be influenced by the PGI signs for observers of the signs and actual car park utilisation levels for non-observers. The model assumes that the choice of car park does not change after entering the city centre, even if conditions observed are different from those initially perceived.A mathematical programme was formulated to determine the optimal display PGI sign configuration to minimise queue lengths and vehicle kilometres of travel (VKT). The model was limited to off-street parking choices and illegal parking was not incorporated. A simple genetic algorithm was used to identify solutions that significantly reduced queue lengths and VKT compared with existing practices.These procedures were applied to an existing PGI system operating in Tama New Town near Tokyo. Significant reductions in queue lengths and VKT were predicted using the optimisation model. This would reduce traffic congestion and lead to various environmental benefits.
Modern prosperous cities strongly need advanced parking assistant systems, intelligent transportation systems providing drivers with parking information. Existing parking information systems usually ignore the parking price factor and do not automatically provide optimal car parks matching drivers’ demand. Currently, the parking price has no negotiable space; consumers lose their bargaining position to obtain better and cheaper parking. This study uses an intelligent agent system, and considering negotiable parking prices, selects the optimal car park for the driver. The autonomous coordination activities challenge traditional approaches and call for new paradigms and supporting middleware. An agent-based coordination network is proposed to bring true benefit to drivers and car park operators. These modern intelligent agents have capabilities including planning, mobility, execution monitoring and coordination. These properties can be used to construct the integrated parking assistant system.
The basic concepts of the parking reservation system and parking revenue management system are discussed in this paper. The proposed “intelligent” parking space inventory control system that is based on a combination of fuzzy logic and integer programming techniques makes “on line” decisions whether to accept or reject a new driver’s request for parking. In the first step of the proposed model, the best parking strategies are developed for many different patterns of vehicle arrivals. These parking strategies are developed using integer programming approach. In the second step, learning from the best strategies, specific rules are defined. The uniqueness of the proposed approach is that the rules are derived from the set of chosen examples assuming that the future traffic arrival patterns are known. The results were found to be close to the best solution assuming that the future arrival pattern is known.
This paper reports on models developed from data collected using the PARKIT parking choice simulator. PARKIT provided an experimental environment in which drivers’ choice of car parks, and of the routes chosen to reach them, could be observed and the influence of different levels of parking-stock knowledge (derived from experience or from information provided via roadside message signs) monitored. Separate models were estimated for the drivers’ initial choice of car park and for their revision of that choice as their journey progresses and they learn about actual conditions. The importance of price, walking time and driving distance is confirmed but the addition of variables describing the drivers’ choices on previous days, their expectations and their immediately preceding route-choice, greatly improved the models’ explanatory power. It is noted that variables such as these are not generally considered because they are rarely available to the modeller. Different discrete choice model structures were found to be appropriate for different decisions. Route choice was represented as an exit-choice model (whereby each journey is treated as a sequence of decisions—one at each intersection encountered). The paper discusses the incorporation of these choice models into a network assignment model and concludes that much of the power of the choice models is lost if the network model is not able to support use of information about travellers’ socio-economic characteristics and knowledge of the network and about the detailed network topology.
This paper proposes a time-dependent network equilibrium model that simultaneously considers a traveler’s choice of departure time, route, parking location and parking duration in road networks with multiple user classes and multiple parking facilities. In the proposed model, travelers are differentiated by their trip purpose and parking duration, parking locations are characterized by facility type and parking charge, and the decision-making process of travelers on travel and parking choices is assumed to follow a hierarchical choice structure. The model is formulated as a variational inequality problem, and is solved by a heuristic solution algorithm. Numerical results for two example networks are presented to show the solution quality and investigate the solution sensitivities to some input data. It is found that parking behavior is significantly affected by travel demand, walking distance, parking capacity, and parking charge. The proposed model provides a useful tool for studying the complex temporal and spatial interaction between road traffic and parking congestion, and can be used to assess the effects of various parking policies and infrastructure improvements at a strategic level.
This paper investigates the role of parking pricing and supply by time of day in whether to drive and park in the central business district (CBD). A stated preference survey of car drivers and public transport users was undertaken at a number of parking locations, public transit interchanges, and shopping centres in Sydney CBD during 1998. In the context of a current trip to the CBD, respondents were asked to consider six alternatives, including three parking locations in the CBD, park outside of the CBD with public transport connection to the CBD, switch to public transport, or forego that trip to the CBD. The three parking locations were defined by hours of operation, a tariff schedule, and access time to the final destination from the parking station. Data from the survey were then used to estimate a nested logit model of mode and parking choices, which was then used to simulate the impacts of supply pricing scenarios on CBD parking share. The change in CBD parking share attributable to supply by time of day is less than 3%, compared to 97% attributable to parking prices.
According to the problem that the directing information is static in most parking guidance and information systems (PGIS) nowadays, this paper suggests establishing the real-time and dynamic PGIC that is providing the dynamic information guidance for the vehicles that need parking. First of all, it adopts the principal component analysis to choose the main factors that affect the drivers' parking choice activity. Then according to fuzzy clustering algorithm, it categorizes the drivers that need parking and assign them parks, in order to carry out the real-time and dynamic guidance in the process of parking.
Parking guidance – modelling, simulation and impact assessment Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities
- E Jonkers
- Van Noort
- M Van
- J L Veen
Jonkers, E., Van Noort, M., Van der Veen, J.L., 2011. Parking guidance – modelling, simulation and impact assessment. In: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2011. Lam, W.H.K., Li, Z.-C., Huang, H.-J., Wong, S.C., 2006. Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities. Transport. Res. Part B: Meth. 40 (5), 368–395.
Analysis of Parking Reliability Guidance of Urban Parking Variable Message Sign System Mathematical Problems in Engineering
- Z Mei
- Y Tian
- D Li
- Y Seong-Eun
- C P Kit
- K Taehong
- K Jonggu
- K Daeyoung
- S Changsub
- S Kyungbok
- J Byungtae
Mei, Z., Tian, Y., Li, D., 2012. Analysis of Parking Reliability Guidance of Urban Parking Variable Message Sign System. Mathematical Problems in Engineering, 2012. Seong-Eun, Y., Kit, C.P., Taehong, K., Jonggu, K., Daeyoung, K., Changsub, S., Kyungbok, S., Byungtae, J., 2008. PGS: Parking Guidance System based on wireless sensor network. In: 3rd International Symposium on Wireless Pervasive Computing, 2008. ISWPC 2008.
Study of the mode of real-time and dynamic parking guidance and information systems based on fuzzy clustering analysis Study on urban parking guidance information system design Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies Cruising for parking
- A Shi
- H Bo
- W Jian
Shi, A., Bo, H., Jian, W., 2004. Study of the mode of real-time and dynamic parking guidance and information systems based on fuzzy clustering analysis. In: Machine Learning and Cybernetics, 2004. Song, J., Wen, Z., 2011. Study on urban parking guidance information system design. In: Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies. Soup, D., 2007. Cruising for parking. Access 30, 16–22.
Feasibility study of real time parking information at Metrorail parking facilities-Virginia Stations. Washington Metropolitan Area Transit Authority
- Wilbur-Smith Associates
Wilbur-Smith Associates, 2009. Feasibility study of real time parking information at Metrorail parking facilities-Virginia Stations. Washington Metropolitan Area Transit Authority. <http://www.wmata.com/pdfs/planning/Real_Time_Parking_Study.pdf>. Yanfeng, G., Cassandras, C.G., 2011. Dynamic resource allocation in urban settings: a smart parking approach. In: 2011 IEEE International Symposium on Computer-Aided Control System Design (CACSD).
Cruising for parking
- Soup