Vision-based parking control system for docking to recharge an agricultural electric vehicle

Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent that customer are satisfied with parking control system to improve the quality of the system services and diversify the system services. The degree of satisfaction is different from customer to customer in same condition and can be represented as linguistic variables. In this paper, we present therefore a technique that quantify how much customer are satisfied with parking control system and fuzzy inference system architecture as a solution that can help us to make a efficient decision for these parking problems. In this architecture, inference engine using fuzzy logic compares context data with the rules in the fuzzy rule-based system, gets the sub-results, aggregates them and defuzzifies the aggregated result using MATLAB application programming to obtain crisp value. Fuzzy inference system architecture presented in this paper, can be used as a efficient method to analyze the satisfaction degree which is represented as fuzzy linguistic variables by human emotion. And it can be used to improve the satisfaction degree of not only parking system but also other service systems of various domains.

Deep learning can be applied on vehicle image classification diverse purposes such as real-time vehicle recognition, vehicle license plate character recognition, vehicle logo identification, and vehicle color classification. We categorize electric vehicle model images according to electric vehicle types and classify each image using Convolutional Neural Network for electric vehicle parking and charging system. The suggested model can support optimization problem of charging equipment installation and usage by recognizing the electric vehicle type real-time basis at the entrance of parking or charging system and directing each vehicle where to park and charge as each has different charge method and needs different charging equipment. The model is built using transfer learning, that is, we pre-train the network with large dataset compensating the small amount of main dataset and then fine-tune the network with our electric vehicle type dataset. We perform 10-fold experiments and achieve final test accuracy of 77.6%.

The world’s population is growing at an exponential rate, which has created a slew of new issues in our daily lives. Among these challenges is the difficulty of finding available parking spaces. To overcome this obstacle, an effective system for detecting vacant parking spaces is crucial, particularly in densely populated areas. Even though there are numerous parking detecting systems on the market today, they all have their own set of restrictions. There are primarily two types of parking systems available. The first is a hardware-based system that uses hardware to detect whether a space is vacant or occupied, and the second is a smart parking system that uses cameras to classify parking status. Vision-based parking systems are becoming increasingly popular due to benefits such as flexibility and cost efficiency. However, due to challenging weather conditions and various occlusions caused by objects, such systems are challenging to develop. The limitations of a vision-based parking system must be addressed for it to become more accurate. To date, many researchers have attempted to incorporate deep learning-based parking systems with various algorithms but none of them has focused on reducing the complexity of Convolutional Neural Network (CNN) training through unsupervised pre-processing steps. In this study, an attempt is made to reduce the complexity of CNN by integrating salient features as a pre-processing step for normalizing weather conditions. It has been observed that salient features-based pre-processing makes the system more robust in terms of accuracy and time efficiency.

Due to the increase in the number of vehicles, the usage of petrol and diesel is increasing. These are natural resources which are non renewable. So keeping it in mind electric vehicles are introduced and being introduced. At this time the usage of electric vehicles is very less compared to petrol and diesel cars. But keeping future in mind we have to develop a user friendly parking system for electric vehicles. Electric vehicles must be charged which takes a long time. So this research is to provide an idea for developing a user friendly and advanced electric vehicle car parking system. As automation is taking place, we use IOT and sensors (ultrasonic sensor, infrared sensors, ANPR, voltage sensor) to automate our parking system. By using these IOT concepts we can easily attain automation. We have to take every aspect into consideration and design a system without any technical fault. Safety and security are also important. We should be ready to handle any situation. We should build certain exit plans and emergency systems. So we came with a prototype of a parking system which includes charging, automation, safety measures and user friendly. So this is the overview of our project and research and everything will be explained in detail in the working part.KeywordsIoTIVR (interactive voice response)RFID (radio frequency identification card)OTP (one time password)Arduino

Goals of parking lot management system include counting the number of parked vehicles, monitoring the changes of the parked vehicles over the time, and identifying the stalls available. To decrease the cost of the production, an integrated vision-based system is a good choice. In this paper, we propose a vision-based parking management system to manage an outdoor parking lot by four cameras set up at loft of buildings around it, sending information, including real-time display, to database of ITS center via internet. This system enables drivers to find parking spaces available or monitoring the parking lot where they parked their cars easily by wireless communication device. To increase accuracy, in the beginning, color manage is done to all input images, maintaining color consistency. Then, an adaptive parking lot background model is generated. The adequate color of each parking space is found out using statistical method in color image sequences captured by a camera, and foreground is extracted based on color information. The result will be further modified by shadow detection based on luminance analysis. Vision-based parking management system can manage large area by just several cameras. Adjusting position of the camera can easily make this system suitable for most cases. Besides, this system is endurable and is easy-installed because of its simple equipment.

U.S federal and state governments invest millions of dollars for enforcing parking control in the metro city area. Tasks like parking enforcement, towing of illegally parked vehicles and maintenance require many man-hours and resources. The parking control and revenue system in the metro are essentially dependant on devices like coin or token based parking meters, which require the use of exact change and is therefore cumbersome. Also a patrol officer is required to monitor these spaces constantly. This entails the need for a more efficient and redundant system. In this paper, we propose an architecture for automated parking meter and driver assistance system that shall be connected to a centralized traffic control authority responsible for parking enforcement and toll collection. This system would provide a more efficient and redundant way of enforcing parking control and toll collection and also assist drivers in metro area for searching an available parking space. The above-mentioned architecture enables automated parking toll collection.

Feedback control systems employing video cameras as sensors have been studied in the robotics community for many years. An especially interesting feature of such systems is that both the process output and the reference set-point are typically observed through the same sensors (i.e., cameras). Due to this unusual architectural feature, it is sometimes possible to achieve precise positioning, despite sensor/actuator and process model imprecision, just as it is in the case of a conventional set-point control system with a perfect loop-integrator and precise output and exogenous reference sensing. But in contrast to a set-point control system where what to choose for an error is usually clear, in vision-based systems there are many choices for errors, each with different attributes. The aim of this paper is to discuss these issues in a fairly general setting and to provide concrete examples to illustrate the concepts involved in geometrical terms.

CNC machines are still suffering from machine blindness. They cannot automatically assess the performance of applied machined tasks. In this article, an approach is made to improve the performance of CNC machining by utilizing on-line vision-based monitoring and control system. To facilitate the integration of computer vision with CNC machines a system is proposed and developed to tackle a number of pinpointed issues that obstruct such integration. A practical executable methodology of these steps is developed to enable their beneficial implementation on lab-scale CNC milling machines. Two different models of bench type CNC machines are employed to generalize the findings. Two cameras are mounted on the machine spindle of each of the two employed CNC machines to provide valid image data according to the cutting direction. Proper selection and activation of relative camera is achieved automatically by the developed system which analyze the most recent conducted tool path movement to decide on which camera is to be activated. In order to assess the machining surface quality and cutting tool status, image data are processed to evaluate resulting tool imprints on the machined surface. An indicating parameter to assess resulting tool imprints is proposed and used. The overall results show the validity of the approach and encourage further development to realize real industrial scale intelligent vision-controlled CNC machines.

Present decade has seen the growth and advancements in Electric Vehicle (EV). For the LPG and diesel cars that produce pollution and pose as threat to the environment, EVs are an eco-friendly and sustainable alternative particularly for CO2 reduction and alternative energy purposes. With the growing popularity of EV, there is a need for their charging ports. And parking of vehicles has always been a cumbersome task. And hence, EV also requires an efficient parking system. The project that we are working on involves a “Smart Parking as well as Green Charging system of EV”. We are building an IOT based Car Parking System using Node MCU, Arduino UNO, Servomotor and 6 IR sensors. We use Internet of Things (IoT) for a hassle-free parking system and getting the information on Blynk application about the slot availability. Second part of project is charging the EV using a 15V solar panel that is used to charge a 12V battery on the platform where car is parked

A dual-stage parking system for differential-drive robots

Parking organizers often do not want to replace lost vehicles as written on the ticket. Even though Article 102 of PP 79/2013 stipulates that the parking organizer must replace, but is not equipped with clear sanctions. The problem formulations of this research are the parking control system and the parking manager's responsibility for the parked vehicles loss. The research purpose are to analyze the parking control system and the parking manager's responsibility for the parked vehicles loss. This research is legal research with primary sources, secondary sources, and tertiary sources collected by the literature study method and analyzed by prescriptive methods. The parking control system aims to support the parking work system to make it more effective, efficient and safe. The existence of parking lots, provision of facilities, and security guarantees are a unified system. If there is a parked vehicle missing, the parking organizer must replace it as stipulated in Article 102 PP 79/2013, but the sanctions are not clearly regulated. The inclusion of writing in the parking location that contains a statement that is not responsible for loss is known as a standard clause that contradicts Article 18 of Law 8/1999, and can be sued civilly for illegal acts and defaults based on Article 1694, Article 1234, Article 1239, Article 1365 , 1366, and 1367 BW. So parking organizers must maintain security and replace losses.

Managing parking lots usually involve tasks that should provide important information such as parked car counts, and available parking spaces and their locations. This can be used to direct drivers in real-time towards empty spaces which will minimise the time spent looking for one and thus reduce traffic congestions. Using an image-based integrated parking system is an effective way to automatically track a parking lot without exhausting time and manual resources. In this paper, we present a low-cost vision-based parking system to manage a closed area parking lot by using cameras that takes real-time footage of the parking lot. The footage is processed using HSV-based histogram technique and the resulting models are compared against pre-trained models. These models define either a Parked or an Empty class. The parking spaces within the processed footage are then categorised using this two classes based on their matching probability.

Recently autonomous parking has got a great attention from researchers from both Academy and Industry and being known as one of the key subsets of autonomous driving. Since autonomous driving is at its hype but with many remaining concerns, autonomous parking is more practical for daily applications and more feasible to be immediately realized mass-production in the automotive industry. Current solutions for autonomous parking require multiple maneuvers and a significant amount of time to park, which lead problematic in many real-life applications, depending on traffic situation around the ego-vehicle. In this paper, we present a parking strategy for vision-based autonomous parking systems in which the ego-vehicle is capable of completing its auto-park by one maneuver, or up to maximum three required maneuvers. Experiments show that the proposed method provides a significant improvement in reducing the number of maneuvers as well as time to park. Indeed, a rate of more than 95% successful parking in heavy traffic flows within a parking area is achieved using this method. We will also prove that the method is lightweight and very efficient for real-time applications.

To improve the safety and efficiency of automated parking, a path planning and tracking control system for automated parking under dual-vehicle coordination is proposed. The Hybrid A* algorithm is modified to consider both the front wheel angle constraints of the vehicle and the collision-free constraints between vehicles while searching for a path. Based on whether cubic spline interpolation is used to smooth the path, the control system is divided into Parking System 1, with unsmoothed paths and Parking System 2, with smoothed paths. The AHP-TOPSIS method is used to calculate the weights of evaluation indicators, and the parking performance of different systems is evaluated based on the normalised system scores. Two application scenarios – vertical parking and parallel parking – were selected, and two operating conditions – two-vehicle cooperative parking in and cooperative parking in and out – were chosen for simulation analysis in PyCharm. The simulation results show that Parking System 2 outperforms Parking System 1 in the aforementioned operating conditions. In the vertical parking scenario, the parking performance of System 2 improved by at least 180.23% in both cooperative parking in and cooperative parking in and out conditions. In the parallel parking scenario, the parking performance improved by at least 181.53% in the cooperative parking-in scenario and by at least 99.04% in the cooperative parking-in and parking-out scenario.

In a conventional parking system that is currently still widely used, vehicle owners must show the parking card or the receipt for the parking hours, so that the fee will be paid. In this experimental study, a parking system was developed by utilizing Radio Frequency Identification (RFID) technology based on a microcontroller control system. The use of this technology makes it possible to make a subscription parking system that is served automatically and flexibly by a parking lot. RFID has data information that can be used as a user’s identity to enter the parking area. In this research, parking system design and implementation were made by simulating a miniature portal door system to enter and exit vehicles on campus using RFID cards/tags as subscription IDs. AT89C51 microcontroller is used as a system controller. By using this RFID technology, the parking subscription system becomes more flexible and faster.