Parking Assistance System Research Articles

ADAS and automation-arelevant contribution to maintaining mobility of older drivers?

Driving is the most important and safest form of mobility for the majority of senior citizens. However, physical and mental performance gradually decline with age, which can lead to more problems, critical situations or even accidents. Vehicle technology innovations such as advanced driver assistance systems (ADAS) have the potential to increase the road safety of older people and maintain their individual mobility for as long as possible.This overview article aims to identify ADAS that have the greatest potential to reduce the number of accidents involving older drivers. For this purpose, the accident and damage occurrence as well as the driving behaviour and compensation strategies of older people are examined in more detail. Suitable ADAS should compensate for typical driver errors, reduce information deficiencies and have ahigh level of acceptance. For older drivers, emergency braking, parking assistance, navigation, intersection assistance and distance speed control systems as well as systems for detecting blind spots and obstacles appear to be particularly suitable.Some of the disadvantages of ADAS are the lack of market penetration, acceptance problems and interface designs that have not yet been optimally adapted to the needs of older users. For older drivers in particular, it appears to be apriority to develop coherent and integrated solutions in the sense of cooperative assistance instead of pushing ahead with high and full automation with many system limits and exceptions, which can place high demands on attention, for example if the vehicle has to be taken over in acritical situation.

Robust Parking Space Allocation System Using Open CV and Scikit-learn

The proliferation of urbanisation has led to an increased demand for efficient parking management systems. In response, this project presents a Smart Parking Assistant system aimed at providing real-time space availability notifications to users through their smartphones. Leveraging computer vision techniques implemented via Open CV and machine learning algorithms from the Scikit-learn library, the system captures video feed from a webcam to detect and quantify the number of empty parking spaces in a designated area. Upon receiving a request from the user, the system processes the video feed to analyse the occupancy status of parking slots, utilising advanced image processing techniques to accurately identify empty spaces along with mask image of the parking lot. The model built using Scikit-learn efficiently categorises the available slots, enabling the system to relay the precise number of open spaces to the user's smartphone. Furthermore, the Smart Parking Assistant incorporates geo-spatial functionalities to enhance user experience. By integrating the Haversine distance formula, the system calculates the distances between the user's location and nearby parking areas. This information is then displayed to the user, allowing them to conveniently locate and navigate to the nearest available parking facility. The proposed system offers a comprehensive solution to address the challenges associated with parking management in urban environments. By harnessing the power of computer vision, machine learning, and geo-spatial technologies, it provides users with timely and accurate information regarding parking space availability, ultimately improving efficiency and convenience in urban parking scenarios.

Review of Research on Vision-Based Parking Space Detection Method

Parking space detection is an important part of the automatic parking assistance system. How to use existing sensors to accurately and effectively detect parking spaces is the key problem that has not been solved in the automatic parking system. Advances in Artificial Intelligence and sensing technologies have motivated significant research and development in parking space detection in the automotive field. Firstly, based on extensive investigation of a lot of literature and the latest re-search results, this paper divides parking space detection methods into methods based on traditional visual features and those methods based on deep learning and introduces them separately. Secondly, the advantages and disadvantages of each parking space detection method are analyzed, compared, and summarized. And the benchmark datasets and algorithm evaluation standards commonly used in parking space detection methods are introduced. Finally, the vision-based parking space detection method is summarized, and the future development trend is prospected.

Voice Controlled Comparator Improvement Based on Resource Utilization in SoC Ecosystem for Parking Assist System

This paper introduces the voice controlled comparator improvement for maneuvering a miniature electric vehicle based on the resource utilization in the system-on-chip (SoC) ecosystem. An intelligent parking assist is to support the driver outside a car while parking in the crowded locations. Voice controlled improvement based on the resource utilization on the SoC ecosystem is modified to command for moving vehicle. The normalized cross correlation (NCC) technique is proposed for voice controlled system with low utilization on the SoC ecosystem. Hardware and software co-design by the Xilinx VIVADO and Vitis software are used to design on an ARM multicore processor and field programmable gate array (FPGA) system inside a ‘Zedboard’ development board. We perform the experiments for Thai command word recognition via Bluetooth using the proposed NCC method to identify the basic command stored on SD card in Zedboard. Empirical results show the voice controlled improvement based on the Pearson’s correlation coefficient (PCC), modified PCC and proposed NCC methods on a Zedboard. The resource utilization on Zedboard are less than as 17.57% in look-up table (LUT), 29.12% in look-up table random access memory (LUTRAM), 6.44% in flip-flop (FF) and 2.38% in input/output (I/O) as compared with a ZYBO system. An average execution time of Zedboard using proposed NCC method is less than PCC and modified PCC as 5.12%, 1%, respectively. Results of proposed NCC of Thai voice command controlled show the validate workability at average percentage accuracy at 90% in the outdoor environments.

A Hybrid Fog Architecture: Improving the Efficiency in IoT-Based Smart Parking Systems

Background: The abundant use of personal vehicles has raised the challenge of parking the vehicle in crowded places such as shopping malls. To help the driver with efficient and troublefree parking, a smart and innovative parking assistance system is required. In addition to discussing the basics of smart parking, Internet of Things (IoT), Cloud computing, and Fog computing, this chapter proposes an IoT-based smart parking system for shopping malls. Methods: To process the IoT data, a hybrid Fog architecture is adopted in order to reduce the latency, where the Fog nodes are connected across the hierarchy. The advantages of this auxiliary connection are discussed critically by comparing with other Fog architectures (hierarchical and P2P). An algorithm is defined to support the proposed architecture and is implemented on two real- world use-cases having requirements of identifying the nearest free car parking slot. The implementation is simulated for a single mall scenario as well as for a campus with multiple malls with parking areas spread across them. Results: The simulation results have proved that our proposed architecture shows lower latency as compared to the traditional smart parking systems that use Cloud architecture. Conclusion: The hybrid Fog architecture minimizes communication latency significantly. Hence, the proposed architecture can suitably be applied for other IoT-based real-time applications.

Supporting User Onboarding in Automated Vehicles through Multimodal Augmented Reality Tutorials

Misconceptions of vehicle automation functionalities lead to either non-use or dangerous misuse of assistant systems, harming the users’ experience by reducing potential comfort or compromise safety. Thus, users must understand how and when to use an assistant system. In a preliminary online survey, we examined the use, trust, and the perceived understanding of modern vehicle assistant systems. Despite remaining incomprehensibility (36–64%), experienced misunderstandings (up to 9%), and the need for training (around 30%), users reported high trust in the systems. In the following study with first-time users, we examine the effect of different User Onboarding approaches for an automated parking assistant system in a Tesla and compare the traditional text-based manual with a multimodal augmented reality (AR) smartphone application in means of user acceptance, UX, trust, understanding, and task performance. While the User Onboarding experience for both approaches shows high pragmatic quality, the hedonic quality was perceived significantly higher in AR. For the automated parking process, reported hedonic and pragmatic user experience, trust, automation understanding, and acceptance do not differ, yet the observed task performance was higher in the AR condition. Overall, AR might help motivate proper User Onboarding and better communicate how to operate the system for inexperienced users.

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.

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.

Research on subjective evaluation method of intelligent parking assist system based on typical parking scenario

With the rapid development of intelligent driving technology, Intelligent Parking Assist systems have been widely used. Through analyzing the technical characteristics of the Intelligent Parking Assist system, this article brings up subjective evaluation indicators of Intelligent Parking Assist system from the perspective of consumers' daily use; Practical verification is carried out for three typical parking scenarios including parallel parking spaces, vertical parking spaces and inclined train spaces, thus a set of subjective evaluation methods suitable for Intelligent Parking Assist systems for passenger cars is summarized.

Vacant Parking Slot Recognition Method for Practical Autonomous Valet Parking System Using around View Image

The parking assist system (PAS) provides information of parking slots around the vehicle. As the demand for an autonomous system is increasing, intelligent PAS has been developed to park the vehicle without the driver’s intervention. To locate parking slots, most existing methods detect slot markings on the ground using an around-view monitoring (AVM) image. There are many types of parking slots of different shapes in the real world. Due to this fact, these methods either limit their target types or use predefined slot information of different types to cover the types. However, the approach using predefined slot information cannot handle more complex cases where the slot markings are connected to other line markings and the angle between slot marking is slightly different from the predefined settings. To overcome this problem, we propose a method to detect parking slots of various shapes without predefined type information. The proposed method is the first to introduce a free junction type feature to represent the structure of parking slot junction. Since the parking slot has a modular or repeated junction pattern at both sides, junction pair consisting of one parking slot can be detected using the free junction type feature. In this process, the geometrically symmetric characteristic of the junction pair is crucial to find each junction pair. The entrance of parking slot is reconstructed according to the structure of junction pair. Then, the vacancy of the parking slot is determined by a support vector machine. The Kalman tracker is applied for each detected parking slot to ensure stability of the detection in consecutive frames. We evaluate the performance of the proposed method by using manually collected datasets, captured in different parking environments. The experimental results show that the proposed method successfully detects various types of parking slots without predefined slot type information in different environments.

Exterior Car Parking Assistance Algorithm Based on Reconfigurable System for Future Industry

A car accident while parking the car is caused by the car driver, who is invisible around the car. However, there are no solutions for parking assistance when the driver is outside the car. The objective of this paper is to propose a reconfigurable embedded system design by voice controlled parking assistance system for a prototype electric vehicle connected to a smartphone via Bluetooth. Hardware and software co-design using the Xilinx VIVADO as a software design tool is introduced. We design the hardware and software on an ARM multicore processor and the reconfigurable system board model ZYBO: XC7Z010 by considering it as hardware accelerator. The hardware of the proposed voice controlled exterior car parking assistance system is installed on the miniature electric vehicle. The experiments are tested successfully at the parking area for both reverse parking and reverse parallel parking. This proposed system is better suited for users so that they can control their car comfortably while parking safely.

Design and development of a motorized aircraft seat to substitute aisle wheelchairs

Purpose The solution described in this paper allows wheelchair users with reduced mobility or physical disabilities to move independently throughout an aircraft and to board and disembark autonomously. Materials and methods A motorized aircraft seat was developed to substitute current aircraft aisle wheelchairs. The real-scale functional prototype was evaluated in a focus group. The results show that the proposed solution is considered superior to current solutions in nine of twenty requirements and neutral in one of them. There was low agreement among the focus group participants in ten requirements, even though the focus group discussion brought interesting reflections, including positive feedback, critics, and suggestions for further research and development in the field. Results The design concept consists of a motorized wheelchair that becomes the seat of the aircraft when anchored on a docking platform attached to the aircraft fuselage via a seat track. The manoeuvring is allowed by a rotating mechanism, which solves a critical function that is to enable wheelchair manoeuvring in the narrow aisles of aircraft. A parking assistant system aids the control of the motorized wheelchair. Conclusions The main benefits of this solution are to reduce seat transfers during the flight experience and to provide more autonomy and comfort for passengers during flights. IMPLICATIONS FOR REHABILITATION A motorized aircraft seat was developed to replace traditional aircraft aisle wheelchairs. A real-scale functional prototype was built, tested in an aircraft mockup, and evaluated in a focus group. The main benefits of the proposed solution are to reduce the number of chair transfers during the flight experience and to provide more autonomy for passengers. Additional benefits are to allow the passengers to experience less physical and emotional stresses, to enter the aircraft corridor looking ahead, and to sit in any aisle position in the aircraft.

Auditory Assist Method to Indicate Steering Start Timing in Reverse Parking for Improvement of Driver Performance

The development of fully automating the operation of automobiles is rapidly progressing. However, challenges related to driving skill improvement of drivers exist because of the necessity of manual operation, and these are expected to continue in the future. Despite the fact that maintaining and improving manual driving performance will be indispensable in the near future, there are few studies on parking assistance systems aimed at improving the skills of the drivers. Therefore, we focused on steering timing as a candidate factor for skill improvement in reverse parking. In this article, we developed an assist method based on auditory presentation that indicates the timing for starting of steering in order to follow the target trajectory during reverse parking. From the results of verification tests of the assistance using the driving simulator, various effects such as improvement of driver's parking accuracy and reduction of workload were confirmed.

An IMPC Based Parking Assistance System

<div class="section abstract"><div class="htmlview paragraph">This paper summarizes progress and outcome from our research projects on adaptive model predictive control based parking management system, including parking motion planning and control strategy, as well as a localization strategy for parking spot. IMPC here refers to interactive model predictive control regime, which is characterized in that multiple agents implementing separate MPC strategy are incorporating information about their state, objective, and constraints. To predict future parking parameters, we proposed a practical framework which integrates anticipatory techniques with a model predictive approach that robustly models the uncertainty intrinsic of parking environment. The control regime puts comprehensive consideration into the interactions between vehicle subsystems, thus capable of optimizing trajectory under complex input disturbances under real-world driving scenarios. Moreover, Adaptive model predictive control is utilized to optimally minimize a cost function regarding time elapse, peripheral convenience and vehicle dynamics correspondent with surrounding vehicle states. The objective function is solved by dynamic programming under calibrated constraints in terms of velocity and steering accuracy, which yielded superior performance in comparison with convex programming. A dedicated guidance system was developed for navigating user to the parking spot for ease of locating parking location, which is characterized in that swift location and path are generated by BLE-based sensor fusion. Upon parking action finalization, the BLE sensor transmits the parking location to preferred communication equipment of user, which serves as goal of parking retrieve assignment. Simulation results show promising expected cost minimization in typical parking environments under consideration of numbers of trials, parking time and distance to destination. The achieved accuracy of MPC-led parking management strategy is able to improve the precision up to 0.3 meter, within the simulated highly disorganized parking environment. Meanwhile, the state of art park spot search module is able to shorten the time for drivers to locate their vehicle with positioning error of less than 1.2 meter.</div></div>

A Distributed Markovian Parking Assist System

This paper proposes a congestion balancing parking guidance system that suggests to a driver a sequence of streets to follow around the desired destination with the aim to reduce the total distance that is travelled while searching for a free parking spot. The system requires only limited infrastructure information, and neither requires parking spaces to be instrumented, nor vehicles to communicate with each other. Specifically, the system utilizes parking vacancy information on each street. The system also accounts for the added cost of not finding a free space, which is typically expressed as the additional distance that needs to be travelled to find an available parking spot. To avoid local congestion, different drivers respond to different suggestions based on a probability distribution that considers the total distance that needs to be travelled. A mobility simulator is used to model the searching behaviors of vehicles for parking spaces with and without the smart parking algorithm and experimental results are provided using the road network of the city of Dublin, Ireland.

Probabilistic Occupancy Filter for Parking Slot Marker Detection in an Autonomous Parking System Using AVM

Many car makers have examined parking assistance systems and auto parking systems that automatically find free parking spaces and can park a car. The around view monitoring (AVM) can compensate for the disadvantages of distance-sensor-based detection because it can recognize parking spaces based on parking slot markers instead of empty spaces. However, in the case of AVM-based parking marker recognition, false-positive (FP) features can be detected from 3-D objects and shadows, and the parking slot marker is occluded by the vehicle on which the AVM camera is attached. In this paper, we propose a probabilistic occupancy filter to detect parking slot markers. This filter uses a series of AVM images and onboard sensors to improve the occlusion problem and reduce the FPs from other objects. Each pixel of an AVM image has an occupancy probability of parking slot marker features. The occupancy probability compensates for using vehicle motion and updates using the error model of the AVM system and the performance indicator of the feature extractor.

Real-world effects of rear cross-traffic alert on police-reported backing crashes

ObjectiveSeveral parking assistance systems are available to help drivers back up. Rear cross-traffic alert warns drivers when they are reversing and cross-traffic approaches the rear of their vehicle, as might happen when backing out of a perpendicular parking space in a lot. The goal of this study was to examine the effect of rear cross-traffic alert on backing crashes. MethodsNegative binomial regression was used to compare police-reported backing crash rates in 25 U.S. states per insured vehicle year between General Motors and Mazda vehicles with rear cross-traffic alert and the same vehicle models without the optional system, controlling for the presence of other parking assistance systems and additional factors that may affect crash risk. ResultsCrash involvement rates in backing crashes overall were 22% lower among vehicles with rear cross-traffic alert than among vehicles without the system when averaged between the two manufacturers. Rates were 32% lower among vehicles with the system than without in two-vehicle backing crashes where the vehicles were traveling in perpendicular directions. Both reductions were statistically significant. ConclusionsRearview cameras and rear automatic braking, which are designed to help drivers detect and brake for obstacles directly behind the vehicle, have been shown in previous research to be effective in reducing backing crashes reported to the police. Rear cross-traffic alert can complement these systems by preventing potential backing crashes that other parking assistance systems are not designed to detect. Manufacturers should equip vehicles with rear cross-traffic alert, in addition to other parking assistance systems like rear automatic braking, to maximize the number of backing crashes prevented.

Development and Usability Testing of a Novel Parking Assist System that Aids Other Drivers While Parking

Current parking assist systems are designed to aid the driver. This paper presents a new concept for a parking assist system that was designed to help other drivers. Sixteen participants participated in this usability study to evaluate the intuitiveness of the parking assist concept. The results showed that all of the participants understood the purpose of the system without any explanation. Participants provided valuable suggestions for future iterations. The majority of the participants would like to have this type of parking assist system on their own vehicle and would want to use it while parking. Future efforts are suggested prior to incorporating this concept on a production vehicle.

Automated Steering Control of Parking Assist System for Articulated Vehicles

Automated Steering Control of Parking Assist System for Articulated Vehicles