Automatic Parking Research Articles

Detection of parking slots occupation by temporal difference of inverse perspective mapping from vehicle-borne monocular camera

Detection of parking slots occupation is a crucial task for parking assistance, automatic parking, and autonomous driving systems. This paper proposed a novel method, called Temporal Difference of Inverse Perspective Mapping Difference (TD-IPM), without explicit 3D reconstruction or objection detection. In this method, temporal images from monocular camera are first inverse perspective mapped (IPM) onto the ground plane based on camera calibration results. Second, we proposed an algorithm, called Block Consensus based on Rotation Invariance Phase-Only Correlation (BC-RIPOC), for fast and robust motion estimation. From the estimated motion, we can align these two IPM images and generate IPM difference map. Third, the IPM difference map is segmented and filtered to generate a binary map that can distinguish objects on the ground plane or not for occupation detection. The obstacle is readily localized from the difference map as well. The proposed TD-IPM method has been validated in both underground and outdoor parking lots. Experimental results demonstrate that the proposed TD-IPM method can successfully detect various occupation objects, such as vehicles, cones, lockers, and others, with 97.9% average detection accuracy and speed of 17.5 frames per second (fps). The proposed method suggests an effective and low-cost solution to intelligent parking systems.

A novel safety message dissemination framework in LTE‐V2X system

AbstractVehicular communication plays a crucial role in improving road safety and maintaining traffic efficiency through the exchange of safety messages. Besides road safety, it can also be used to support other nonsafety features such as infotainment services, traffic management, parking assistance, and so on. In this article, we explore a hybrid long term evolution vehicle‐to‐everything architecture where we use both vehicle‐to‐infrastructure (V2I) and vehicle‐to‐vehicle (V2V) communication to simultaneously provide high throughput for infotainment services and maintain high reliability and low transmission delay for the safety messages. To this end, we propose V2I and V2V resource allocation algorithms which support a strict allocation priority for the safety messages over the nonsafety messages. We evaluate the performance of the proposed algorithms by extensive simulations using OMNeT++, INET, and SimuLTE softwares and analyze the simulation data using MATLAB software. The simulation results indicate that, as compared with using only V2I communication, the proposed algorithms decrease the end‐to‐end delay (∼23%, on average) of the safety messages with little degradation (< 10%, on average) in throughput of the background traffic. We compare our proposed algorithms with the existing algorithms and find that the proposed algorithms show a performance gain of 36.5% and 45% in terms of end‐to‐end latency and packet reception ratio, respectively.

Automotive Parking Assistant Testing Scene analysis and evaluation research

Since the existing automatic parking testing procedure scene is way too simple and idealized, it’s necessary to explore a set of effective verification procedure for the complex scene of Automatic Parking Assistant, which can evaluate the overall performance of the automatic parking function of different vehicles comprehensively, objectively and accurately. In the actual vehicle parking process, there are a lot of harsh and complex scenes which cannot be covered by the current verification system. This paper aims to build a set of effective verification system for the complex scene of automatic parking based on Artificial Intelligence technology. It can comprehensively, objectively and accurately evaluate the comprehensive performance of the automatic parking function of different vehicles.

An Automatic Parking Model Based on Deep Reinforcement Learning

When parking a car, it is crucial to ensure the car constantly approaches the parking point, gets an excellent heading angle, and avoids significant losses caused by line pressure. An automatic parking model based on deep reinforcement learning is proposed. A parking kinematics model is built to calculate the different states of its movement. Steering angle and displacement are used to achieve interaction as actions; A comprehensive reward function is designed to consider the focus of action and safety in different parking stages. Through training, the car’s automatic parking is realized, and a comprehensive analysis of the various stages and situations in the parking process is given. Besides, it is showed by a further generalization experiment that the model has good generalization.

Perancangan Aplikasi Sistem Parkir Otomatis menggunakan ERP Odoo Berbasis Internet of Things

Universitas Singaperbangsa Karawang (UNSIKA) is a favorite Public universities in Karawang, West Java. UNSIKA parking system has not met the expectations of a good parking system, especially in the field of security. This research aims to solve the problem by designing an IoT-based automated parking system application with a high level of security, informative to provide comfort for users and managers. The method in the security system is to use barcodes and fingerprints, as for the application that will be made using ERP Odoo. The results of this study are a tool called BIOPARKS (Biometric Parking System) that can reduce the risk of theft in parking lots. Also, data management applications such as vehicle data, vehicle owner data, reports in and out of vehicles, as well as a monitor of parking conditions. The use of barcode and fingerprint technology in the parking system makes the security on the parking lot more secure so that the owner of the vehicle becomes calm. Applications designed to make data management more structured, as well as facilitate monitoring of parking conditions.

Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State.

The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance.

Evolution test by improved genetic algorithm with application to performance limit evaluation of automatic parallel parking system

Performance limit evaluation of automatic driving system before putting into the market is critical for driving safety. The evolution test by genetic algorithm (GA) is a method by iteratively generating new test scenarios according to the last test results. To avoid its blind search for better efficiency, a scenario complexity index is proposed to measure the test effectiveness indirectly and guide the evolution process under the assumption that a complex scenario is more challenging to realise automatic driving. The traditional crossover and mutation operators are modified to generate more complex scenarios to improve the test efficiency. The advantage of the improved crossover/mutation operators in increasing the offspring's scenario complexity index is analysed in theory. Moreover, the influence of the design parameters on the evolution test process and the global convergence are also discussed. The new evolution test by this improved GA has been applied to find the collision condition of a parallel automatic parking system to validate its effectiveness.

Specular Detection on Glossy Surface Using Geometric Characteristics of Specularity in Top-View Images.

In an autonomous driving assistance system (ADAS), top views effectively represent objects around the vehicle on a 2D plane. Top-view images are therefore widely used to detect lines in ADAS applications such as lane-keeping assistance and parking assistance. Because line detection is a crucial step for these applications, the false positive detection of lines can lead to failure of the system. Specular reflections from a glossy surface are often the cause of false positives, and since certain specular patterns resemble actual lines in the top-view image, their presence induces false positive lines. Incorrect positions of the lines or parking stalls can thus be obtained. To alleviate this problem, we propose two methods to estimate specular pixels in the top-view image. The methods use a geometric property of the specular region: the shape of the specular region is stretched long in the direction of the camera as the distance between the camera and the light source becomes distant, resulting in a straight line. This property can be used to distinguish the specular region in images. One estimates the pixel-wise probability of the specularity using gradient vectors obtained from an edge detector and the other estimates specularity using the line equation of each line segment obtained by line detection. To evaluate the performance of the proposed method, we added our methods as a pre-processing step to existing parking stall detection methods and investigated changes in their performance. The proposed methods improved line detection performance by accurately estimating specular components in the top-view images.

Arbitrary Configuration Stabilization Control for Nonholonomic Vehicle With Input Saturation: A c-Nonholonomic Trajectory Approach

This article addresses the saturated stabilization control problem for nonholonomic vehicles with a novel c-nonholonomic trajectory approach on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{SE}(2)$</tex-math></inline-formula> , with applications to automatic parking. First, by defining the c-nonholonomic configuration, a c-nonholonomic trajectory is obtained, which provides a novel approach to design stabilization controller to reach an arbitrary configuration. Second, a global discontinuous time-invariant feedback controller with input saturation is proposed, which does not involve time signal information, and its convergence is illustrated by a Lyapunov function approach. Thereafter, the motion trajectory of the proposed controller is analyzed, and the application scenario in automatic parking with the approximate desired trajectory is demonstrated. Finally, the performance of the proposed controller is validated by both numerical simulations and experiments.

Modern methods of field tests of driver assist systems

In view of stringent vehicle safety requirements the automakers are urged to develop and implement electronic driver assist systems (ADAS). However, before starting the mass production, one has to make sure that these systems function correctly and efficiently. The current level of technologies, the simulation modelling allows debugging and testing of operation algorithms for electronic ‘assistants’ in laboratory conditions thereby reducing the costs of the prototype production. This approach is employed at intermediate development stages of the system. At the final stage the ‘traditional’ approach (field tests) is used by the automobile manufacturers, the reason being that the algorithm operation has to be tested in real conditions, and the certification of vehicles with ADAS functionality using methods of simulation modelling is not provided in current state standards. Keeping this in view, the problem arises of creating a measuring unit for geolocation of the vehicle with precision accuracy and synchronized video recording from multiple cameras simultaneously. This article presents the solution developed by employees from NNSTU n.a. R. E. Alekseev as regards the development of such a test system: a schematic diagram of the system is developed; the system is installed on a light commercial vehicle being tested; the system efficiency is checked. The system performance was checked when testing blind spot detectors, lane departure warning system and parking assistant.

Principles of Formation of Aboveground Parking Lots as a Part of Residential Building or Complex

The article deals with the problem of parking and storage of personal transport in multi-storey residential development areas. Using of underground parking under a building or yard may not always be the most profitable solution. Especially taking into account that the nature of the soil in the largest megacities of Russia is very complex and it leads to a strong increase in the cost price of the project. Options for organizing above-ground parking are proposed and analyzed. The advantages and disadvantages of modern free-standing parking lots are described in the article. Examples of built-in attached parking lots within a residential group are demonstrated too. The advantages of automated parking lots built into the lower floors of high-rise buildings are listed. Project proposals are presented that demonstrate the possibility of placing automatic Parking directly in the lower floors of a residential building.

An improved parking space recognition algorithm based on panoramic vision

In order to reduce parking difficulties caused by small parking spaces, low driver driving experience, and complex parking environment, parking assistance systems have attracted attention, but the identification of parking spaces is a key problem and technical difficulty. In this paper, an improved parking space recognition algorithm based on panoramic vision is proposed. Firstly, in the look-around image forming part, a method of distortion correction (DC) and perspective transformation (PT) based on LUT (Look Up Table) transformation is proposed to improve the processing speed of the algorithm. Then, to improve the accuracy of parking space recognition, an improved method combining rough extraction and fine matching is proposed to identify parking spaces in a look-around image. The experimental results show that the method achieves a detection rate of 97.63% under sufficient illumination and 79.77% even under insufficient illumination.

SISTEM PARKIR BERBASIS WEB + IOT PROJECT KIT SERI RFID DI HASIM TEKNIK KARAWANG

Advances in technology today require humans to increase their effectiveness and efficiency in various ways. Basically the purpose of creating a tool is to help human work to be more effective and efficient. Thus, humans are expected to function in a relatively short time, especially when it comes to safety. The parking lot is a medium that is used as a way of getting in and out of vehicles. Anticipating some problems in the parking lot, for example: losing parking papers, losing cars in parking lots, and preventing illegal parking at high levels. Then we need an automatic parking door system. This final project aims to build a prototype of an IoT-based automated parking system.&#x0D; This project is a simple parking simulator with a microcontroller device programmed to use the Arduino idea. Hardware integrated with mysql database and run by simple web. The automated parking system is designed using nodemcu lolin, expansion board, 16x2 + i2c LCD adapter, mini mp3 dfplayer, 0.5 watt ohm earbuds, infrared sensor, rfid rc522 and SG90 servo motor. Infrared sensor detects vehicle, rfid receives input by tapping card and then gives output to i2c and web. Furthermore, the output from the LCD goes to the service motor which opens and closes the parking door, and the dfmp3 player, as well as the speaker which makes a sound when the card is tapped. This prototype automatic parking system can provide access and close automatic parking doors which saves time and effort. It can be concluded that the prototype of this IoT automatic parking system can be used as a guide for the development of a better technology.

Composite fault diagnosis methodology for urban vehicular ad hoc network

Vehicular Ad-hoc NETwork (VANET) is a meteoric growing research area due to the technological advancement in sensing, computation, communication, and radio wireless technology. The demand for VANET is increasing day by day due to the numerous diverse applications. Applications of VANET include safety applications like reduction in the road accident by broadcasting messages to the driver, convenience applications like automatic parking service, commercial applications like selling and buying of products through a network of wheels, productive applications like automatic environmental parameters monitoring, vehicular cloud service like secure toll transaction, etc. The aforementioned VANET applications will become non-operational if the communication unit of the vehicle becomes inoperative or malfunctioning. This paper proposes a composite fault diagnosis methodology by detecting and classifying the fault of the On Board Unit (OBU) of the vehicular ad hoc network. The fault detection includes the detection of two categories of the fault i.e. hard fault in which the communication unit is in the inactive state and not able to communicate with other communication units and soft fault in which the communication unit is in the active state but communicates incorrect data with other communication devices. The hard fault is detected by the repeated time out mechanism and by a statistical method called Kolmogorov–Smirnov test (K-S test). The detection of soft fault (permanent, intermittent, and transient) is performed by a statistical method called the Chi-square test. Apart from the detection of the soft fault, the classification of soft fault is carried out by ECOC-SVM. Finally, the result of the fault is transmitted to the faulty vehicle. The parameters such as Fault Detection Accuracy (FDA) and False Alarm Rate (FAR) are used to validate the proposed fault detection protocol. The parameter False classification rate (FCR) is used to measure the performance of the soft fault classification. Finally, the performance of the transmission of the result to the faulty vehicle is evaluated through the parameters end-to-end (E2E) delay, number of hops, and network gaps by comparing the proposed work with existing routing protocols of VANET like GSR, A-STAR, Bhoi et al.

A kriminalisztika alapkérdései és az önvezető járművek

Driving is already supported by a number of technical devices. Just think of the cruise control, lane change system, automatic deceleration, automatic parking system, electronic stability control, automatic emergency brakes or lane departure warning. Although the introduction of self-driving vehicles in Hungary still seems to be a distant future, it is already present in many countries (especially in the USA). There are countless fears and uncertainties about self-driving vehicles, but the benefits are undeniable. The introduction of self-driving vehicles raises a number of legal, technical, informatics and ethical issues. Of them, the study examines the advantages and disadvantages of introducing self-driving vehicles in the light of basic forensic issues, after clarifying ethical issues (see trolley- problem) and guilt issues. Within this, it is limited to traffic offenses (so the issue of cyber-terrorism related to self-driving vehicles, or even drug trafficking, is not the subject of the study). It has been found that some questions may make it more difficult to detect a crime (it is often difficult to answer the question who committed it). From the product manufacturer to the programmer, the operator or the user, many people can be held criminally liable. In comparison, thanks to the technical means and the network connection, we can count on ease of detection of the crimes with the help of self-driving vehicles in many issues. Arrived: 8 September 2020Accepted: 8 November 2020

A Novel Misalignment Tolerant Magnetic Coupler for Electric Vehicle Wireless Charging

The lateral misalignment for static electric vehicle (EV) wireless charging could be much larger than 100 mm if the parking assistance systems are unavailable. This article proposes a split flat solenoid coupler (SFSC) to significantly extend the lateral misalignment and reduce the copper and ferrite usage. To obtain a good balance among coupling, misalignment tolerance, and cost, an optimization method for SFSC is proposed where the size limitations and ferrite tile specifications are considered. The optimized SFSC is compared with two magnetic couplers recommended in SAE J2954 in terms of coupling coefficient and misalignment tolerance. To eliminate the impact of coil size and make the comparison fair, the quantified misalignment tolerance is introduced. The proposed SFSC provides much better misalignment tolerance than the recommended couplers. A 1000-W prototype is built to show the advantages of the proposed coupler. The output current keeps unchanged when the lateral misalignment is as high as 400 mm. A highest power transfer efficiency, from dc input to dc output, of 89.12% is achieved when the output power is 1000 W.

Research Review on Parking Space Detection Method

The parking assist system is an essential application of the car’s active collision avoidance system in low-speed and complex urban environments, which has been a hot research topic in recent years. Parking space detection is an important step of the parking assistance system, and its research object is parking spaces with symmetrical structures in parking lots. By analyzing and investigating parking space information measured by the sensors, reliable detection of sufficient parking spaces can be realized. First, this article discusses the main problems in the process of detecting parking spaces, illustrating the research significance and current research status of parking space detection methods. In addition, it further introduces some parking space detection methods, including free-space-based methods, parking-space-marking-based methods, user-interface-based methods, and infrastructure-based methods, which are all under methods of parking space selection. Lastly, this article summarizes the parking space detection methods, which gives a clear direction for future research.

Automatic Parking Path Planning Based on Ant Colony Optimization and the Grid Method

This paper analyzes the path planning problem in the automatic parking process, and studies a path planning method for automatic parking. The grid method and the ant colony optimization are combined to find the shortest path from the parking start point to the end point. The grid method is used to model the parking environment to simulate the actual parking space of automatic parking; then this paper makes some improvements to the basic ant colony optimization, finds the destination by setting the ants’ movement rules in the grid, and finds the shortest path after N iterations; since the optimal path found is a polyline, it will increase the difficulty of controlling vehicle path tracking and affect the accuracy of vehicle path tracking. The bezier curve is used to generate a smooth path suitable for vehicle walking. Finally, through matlab simulation, the obstacles in the environment are simulated, and the parking trajectory is obtained. The results show that the path planning method proposed in this paper is feasible.

Unmanned parking method based on cloud platform

With the intelligent development of automobile driving, automatic parking technology is widely concerned by relevant technicians at home and abroad. Automatic parking technology is a method that can realize automatic parking in and out of parking Spaces without manual intervention. At present, automatic parking system has been equipped and used in many models, but there are many problems such as low parking accuracy and unable to effectively identify irregular parking Spaces. In order to solve the above problems, this article is based on a cloud platform developed a driverless car parking method, through the cloud server, GPS (Global Positioning System) and inertial navigation. It can according to the parking information and real-time Positioning planning adjustment path of the vehicle, and controls the complete vehicle posture adjustment, so as to improve the accuracy of parking and parking intelligent identification accuracy and ensure the safety and efficiency in the process of path planning. The effectiveness of the method is verified by simulation experiments with MATLAB software, which can be demonstrated by data.

Semi-Autonomous Parking system for Automatic Transmission vehicles

This paper proposes an automated perpendicular parking strategy for a car which is to be designed. The design considers general cases of perpendicular parking for a rectangular body within a rectangular space. The system works in phases named: The Scanning phase, the parking environment is detected by ultrasonic sensors mounted on the extreme ends of body and a parking position and maneuvering path is produced if the space is enough. Then in the positioning phase, the model positions itself and get aligned with the parking space avoiding potential collisions. Finally, in maneuvering phase, the model moves to the parking position in the parking space in a specified path, which requires clutch, brake control, backward and forward maneuvers depending on the dimensions of the parking space. Based on the characteristics, a collision-free path is planned about the surroundings. The strategy is to be integrated into an automated parking system, and implemented in the car, showing capable of safe parallel parking in tight situations and as automated parking device to help vehicle drivers.