Vehicle Parking Research Articles

Investigating factors of pedestrian safety using ordinal logistic regression in Addis Ababa City roads

Pedestrians are the most victimized group in traffic accidents, and this has raised concerns about pedestrian safety in urban Ethiopia. The aim of this study is to determine the factors that affect pedestrian safety in Addis Ababa city Roads. This study employed a concurrent mixed-methods research method and an explanatory research design. Perception-based pedestrian safety data was collected from respondents’ key informants and personal observation. Exploratory factor analysis was employed to identify significant variables. Besides, the fitness of each variable was evaluated under the assumption of ordinal logistic regression, and the effect size of significant variables was determined using the odds ratio. The result indicates pedestrians are 0.065, 0.181, 0.296, 0.324, 0.289, 0.306, 0.038, and 0.193 times less likely to be safe due to narrow sidewalk width, poor sidewalk and footpath pavement comfort, inclusivity problems of sidewalks and footpaths, illegal vehicle parking, street vending, fast vehicle speed, and absence of traffic signs and lights, respectively. Consequently, the use of ordinal logistic regression offers a practical and effective means of determining pedestrian safety factors. Better pedestrian facilities should be constructed by considering pedestrian flow and diversity. Besides, the concerned body should provide spaces for street vendors and car parking and enforce traffic rules in the appropriate system to control vehicle speed.

Number Plate Recognition Smart Parking Management System Using IoT

This study aims to address the urban vehicle parking issues by proposing a solution using Automatic Number Plate Recognition (ANPR) through image processing and a sensor-based hardware system. Integrating these technologies forms a Smart Parking Management System (SPMS) to automate parking processes and enhance the parking experience. The study aims to create an efficient system that eliminates manual vehicle registration and optimizes space utilization. ANPR and IoT-based sensors help users identify the available slots and pay only for the actual parking duration, which will help to minimize the fixed billing rates. The proposed ANPR system processes vehicle number plates at entry, ensuring seamless identification and eliminating manual registration. IoT sensors monitor real-time slot occupancy, transmitting data to a web admin panel. This panel provides insights such as entry and exit times, total parking duration, and billing costs, facilitating efficient management and remote monitoring. The ANPR-based SPMS reduces reliance on manual processes, streamlining entry procedures. By dynamically assessing slot availability through IoT sensors, users can locate unoccupied spaces quickly, which enhances user convenience. The web admin panel allows administrators to monitor the system remotely, ensuring smooth operations and maintaining accurate records. This study introduces a comprehensive solution to urban parking challenges by integrating ANPR and IoT technologies. The SPMS improves efficiency, reduces human resource needs, and enhances user experience with flexible billing based on actual duration. The combination of hardware and software provides a foundation for effective urban parking management.

Numerical investigation of the influence of thermal runaway modelling on car park fire hazard and application to a Lithium-ion Manganese Oxide battery

This article presents numerical simulations of a Nissan LEAF 2011 electric car fire inside a concrete parking facility. Variations in the thermo-chemical properties of thermal runaway are analysed, and the way they affect the heat received by the concrete structure and a nearby parked vehicle is evaluated. Three key parameters are identified: the composition of the gas flowing through the pressure vent, the associated flow rate, and the peak heat release rate. These parameters are established independently, and the model is closed by adjusting the stoichiometry of the combustion reaction of the vented gas. Four simulations are conducted to capture the uncertainty. The net heat flux and surface temperature on the concrete and on a neighbouring parked car are monitored during each simulation. The study includes a sensitivity analysis of the impact of input variables on the net heat fluxes and surface temperatures, and investigations are carried out to understand the role of internal heat release. Variations in the gaseous mixture composition, heat release rate, and internal heat release have little impact on the resulting thermal conditions around the burning car because the combustion of the polymers in the passenger cabin drives the total heat release rate.

IoT Based Vehicle Accident Detection, Prevention and Parking System

IoT Based Vehicle Accident Detection, Prevention and Parking System

Eco-power management system with operation and voltage security objectives of distribution system operator considering networked virtual power plants with electric vehicles parking lot and price-based demand response

In the energy management of a network, it is expected that by extracting the optimal performance for the power sources, storage equipment, and responsive demand, a favorable economic and technology situation is achievable for the network and the mentioned elements. Virtual power plants, as a unit aggregating resources, storage, and responsive loads, can create more favorable conditions in network energy management. So, it is expected that the positive effect of the virtual power plant format on the economic and technical situation of the distribution system is far more than those of managing individual elements mentioned in the network. Consequently, the distribution network operator's economic, environmental, and technical goals are met through the concurrent administration of reactive and active power in the smart distribution network that is equipped with a flexible-sustainable virtual power plant. The system operator is accountable for reducing the weighted sum of the voltage security index, energy loss, and energy cost of the distribution network. This problem is associated with the optimal power flow formulation, which considers the environmental limits and security of voltage in the distribution network, the renewable resource operation model and flexibility in the form of a virtual power plant, and the system's flexibility constraints. Flexibility resources considered in the present study are price-based demand response and electric vehicle parking lots. Stochastic optimization relying on the Unscented Transform assists in providing a suitable model for uncertain quantities resulting from the amount of load, electric vehicles, renewable power, and price of energy and eventually shortens the computing time and accurately computes the flexibility index. The optimal compromise solution amongst various objective functions can be found through fuzzy decision-making. Some innovations of this research include concurrent administration of active and reactive power in virtual power plant, concurrent modeling of economic, operational, environmental, voltage security, and flexibility indicators in the distribution network, utilization of electric vehicles, and demand response as a source of flexibility, use of Unscented transform for modeling the uncertainties corresponding to the exact calculation of flexibility. The suggested method was simulated in the IEEE 69-bus radial smart distribution system. Regarding the numerical report obtained, the optimal performance of each of the renewable generation, demand response, and parking of electric vehicles can significantly impact the economic and technical condition of the distribution network. However, the best condition was obtained when the mentioned elements were placed in the form of a virtual power plant. So, in such a situation, the energy cost is around $1862 for the said network. The lowest value for the worst security index in this network is around 0.933 p.u. Energy loss, maximum voltage drop, and peak load carrying capability are equal to 1.902 MWh, 0.047 p.u., and 5.624 MW, respectively. As a result, and based on numerical findings, the method can attain sustainable social welfare. The optimal power scheduling of sustainable systems can enhance the economic, security of voltage, and operational, conditions of the network by roughly 43 %, 26.9 %, and 47 %-62 %, respectively, compared to power flow studies. Furthermore, the ideal administration of virtual power plants enables the proposed plan to achieve 100 % flexibility. Additionally, it can substantially diminish the degree of contamination within the distribution network.

Enhancing cyclist safety in cyclist-vehicle interactions through early hazard notifications: a comparison of bi-modal cues at head level

Cyclists frequently face numerous hazards on the road. Often those hazards are posed by motorised vehicles. Advanced support systems that alert cyclists to potential dangers could enhance their safety. However, research in this area, particularly regarding hazard notifications for cyclists, remains sparse. This work assesses bi-modal early hazard notification concepts (combining visual cues with either auditory or tactile feedback) provided at head level (smart glasses with speakers, tactile headband). They are detailing the nature of the hazard, its direction relative to the cyclist, and the timing of exposure. This work investigates cyclists' preference and perception of the proposed concepts for two hazardous situations originating from interactions with vehicles: ‘dooring’, the hazard of a potential collision with an opening door of a parked vehicle (evaluated through a test track study, N = 32) and ‘being overtaken’ which poses the hazard of being cut off or hit by the overtaking vehicle (assessed in a bicycle simulator study, N = 21). The study involved comparisons of supported and unsupported rides, focusing on their impact on usability, intuitiveness, workload, and perceived safety. Our findings reveal varied preferences for the supporting feedback modality, with 56% favouring visual-auditory and 31% visual-tactile. The participants rated user experience, intuitiveness and perceived safety for the use of both concepts quite high. Further, the workload for assisted rides was rated as equally low as for unassisted rides.

Smart Park: Innovating the Future of Vehicle Parking

Effective parking solutions become increasingly important as urban areas increase because of wasted space, time-consuming searches, and traffic congestion. By utilizing cutting edge technologies to improve parking management and user experience, the Smart Vehicle Parking System (SVPS) tackles these issues. To deliver dynamic solutions, SVPS combines sophisticated algorithms, sensor networks, and real-time data. Parking space sensors track occupancy and transmit data to a central system, where machine learning maximizes space distribution and directs vehicles to open spaces. This smart parking system is software and hardware based. Different algorithms are used to find vacant slots using machine learning and deep learning. IR sensors, RFID, Servomotors and ESP 32 microcontrollers and Internet of things are useful to find vacant slots in real time signal processing. In traditional method it is difficult to search free space, and this method is time consuming, Smart parking system overcome this problem with new technology and improve parking management system. The SVPS not only improves urban mobility but also contributes to reducing vehicle emissions and enhanced overall efficiency. Keywords— smart parking, integration, secure payment,advanced technologies, convenient.

Manajemen Kebutuhan Ruang Parkir Sepeda Motor Sebagai Alternatif Penanganan Fasilitas Parkir Sepeda Motor di Kampus Universitas Muhammadiyah Magelang

The need for adequate parking space is one of the main challenges for the Muhammadiyah University Magelang Campus along with the increasing number of student and staff vehicles. The current parking facilities are not able to accommodate the volume of vehicles, especially on days with high campus activity. This condition demands an effective parking management solution to optimize the use of available land and meet future parking needs. This research aims to analyze the management of parking space requirements on the Muhammadiyah University Magelang Campus as an alternative in handling parking facilities. This study uses systematic research methods, starting from reviewing previous research, problem identification, surveys, data collection from written references, to data processing and drawing conclusions. The analysis results show that the need for vehicle parking spaces on campus is greatest on Wednesdays, with a total requirement of 1,293 SRP, while the currently available parking capacity is only 839 SRP. This indicates that the existing parking capacity is not sufficient for the needs of vehicles parked on campus. Projections for the next five years show the need for parking spaces of 1,600 SRP in 2025, 1,468 SRP in 2026, 1,462 SRP in 2027, 1,383 SRP in 2028, and 1,348 SRP in 2029. Based on these data, it can be concluded that this will happen parking shortage on campus in the next five years. As a solution, this research recommends increasing parking capacity through the construction of new parking lots by increasing the number of parking floors on campus. In particular, it is planned to build a multi-storey parking building for motorbikes and additional parking spaces for cars with a more effective and efficient 60° angle parking pattern.

Research on Optimal Path Planning for Automatic Parking Systems

Abstract The issue of autonomous parking for self-driving vehicles is a critical problem in autonomous driving. With the rapid development of the automotive industry and the increasing number of vehicles, the issues of traffic congestion and parking space shortage have become more prominent, further exacerbating the difficulty of parking. Therefore, there is a growing demand for automatic parking functions. This paper focuses on the problem of self-driving vehicles automatically parking in complex conditions without colliding with other self-driving vehicles and obstacles. The main content includes establishing a vehicle parking kinematic model and solving the minimum turning radius based on the Ackermann vehicle model data. When the self-driving vehicle travels in a straight line, a route from the initial position to the parking space is designed, and an automatic parking model is established. The mathematical model is used to solve the self-driving vehicle’s starting position and end position, as well as the trajectory of the self-driving vehicle, and MATLAB is used to simulate and visualize the parking trajectory. The aim is to solve the problem of parking difficulties caused by factors such as insufficient parking spaces and congested parking scenes. To ensure the safe completion of automatic parking, the path planning algorithm in this paper can plan the optimal parking path.

Simulation of hydrogen leakage and diffusion in an enclosed garage of mixed parking of fuel-cell vehicles

The numerical simulation is used to investigate the spread and diffusion behaviors of hydrogen leaks during mixed parking of two different models of fuel cell vehicle in a closed garage. Simultaneously, the impact of different adjacent vehicle models on hydrogen diffusion behaviors is also investigated. It is shown that for vehicles with a higher chassis, hydrogen diffuses rapidly along the ground after striking it. Conversely, vehicle with a lower chassis exhibit slower diffusion of hydrogen along the ground, owing to the limitations imposed by the chassis height. The development of the flammable zones caused by hydrogen leakage can be clearly distinguished into three stages. Each stage is influenced by distinct factors, including the model of leaking vehicle, the model of adjacent vehicles, and the presence of larger vehicles nearby. Notably, the chassis height has a significant impact on the volume of flammable zones, with vehicles possessing lower chassis exhibiting larger volumes. For a given vehicle model, parking near a fuel cell vehicle of the same model facilitates hydrogen diffusion more effectively than parking near a vehicle of a different model.

Gis-Based assessment Of Traffic System In Osisioma Ngwa L.G.A,Abia State.

Geographic Information System (GIS) technology is a tool that was used to gather, store, analyze, and visualize data about the city's traffic flow, including information on roads in Osisioma Ngwa L.g.a. in Aba Abiastate.The objective is to make better decisions based on accurate and current information in order to increase the sustainability and efficiency of Osisiomatraffic flow. This could involve things like streamlining public transit lines, lowering traffic and pollution levels, and enhancing accessibility for all locals. An overview of the main GIS data models for traffic analysis is provided in this project effort. Based on that, a route database for the city of Osisioma is created in a GIS context. The GIS database displays all the elements involved in routing and analyzing traffic flow, including nearby land use in the city, various modes of transportation, and routes for these modes, the city's road network, and more. The most likely reasons of traffic congestion in Osisioma LGA were short road width, poor pavement, and indiscriminate parking of vehicles along the road corridors, mainly by commercial cab drivers, according to an analysis of the results and other performed queries. In conclusion, it was found that the Donald junction route. Mcc junction route and the Osisioma Flyover are the most crowded sections of the whole road networks evaluatedThis project shows how the application of GIS has helped in the proper assessment of the causes of traffic congestion in osisiomaNgwaL.g.a, provide Adequate policies and enforcement should be put in place so as to eradicate indiscriminate parking of vehicle on the road and reckless driving and not obeying the traffic light

Blockchain-based fast handover authentication protocol for Internet of Vehicles in small industrial parks

Autonomous vehicles safeguard the security and efficiency of Internet of Vehicles systems in small industrial parks by authenticating and exchanging real-time information with transportation infrastructure. Deploying a multi-server framework reduces the risk of message blocking and privacy information leakage from centralized services. However, in traditional handover authentication protocols, there are still potential security risks such as high-overhead performance issues and single point of failure attacks. Therefore, it is considered challenging to realize efficient authentication while protecting the privacy of vehicles. In this paper, we propose a secure and efficient handover authentication protocol for autonomous vehicles in a small industrial park to address the challenges. The protocol is based on blockchain and Pedersen verifiable secret sharing scheme, which not only ensures lightweight real-time interactions between autonomous vehicles and edge servers in multi-server environments, but also strictly protects the security and privacy of both vehicles and edge servers. We prove the semantic security of the protocol under the Real-Or-Random model and perform a informal analysis of its security attributes to show that it can withstand a wide range of malicious attacks. Performance evaluation shows that the proposed protocol satisfies more security requirements and has better computational efficiency and communication cost than other related protocols.

Правовые проблемы признания и реализации права собственности на гаражи (по результатам социологических исследований)

The article studies the problems of registration of ownership of garages, the actualization of which is associated with the adoption of new normative legal acts in this area. Special attention is paid to the cities of federal status, in which the implementation of the «garage amnesty» is particularly difficult. Based on the results of the sociological research conducted by the author, analysis of legislation and law enforcement practice, the author formulates both the main problems present in the studied area and the factors (reasons) contributing to their emergence. The author has developed proposals to improve the legislation, including clarification of the status of garages, elimination of conflicts of legal norms, optimization of public policy in the field of storage (parking) of vehicles.

Location and Size Planning of Charging Parking Lots Based on EV Charging Demand Prediction and Fuzzy Bi-Objective Optimization

The market share of electric vehicles (EVs) is growing rapidly. However, given the huge demand for parking and charging of electric vehicles, supporting facilities generally have problems such as insufficient quantity, low utilization efficiency, and mismatch between supply and demand. In this study, based on the actual EV operation data, we propose a driver travel-charging demand prediction method and a fuzzy bi-objective optimization method for location and size planning of charging parking lots (CPLs) based on existing parking facilities, aiming to reduce the charging waiting time of EV users while ensuring the maximal profit of CPL operators. First, the Monte Carlo method is used to construct a driver travel-charging behavior chain and a user spatiotemporal activity transfer model. Then, a user charging decision-making method based on fuzzy logic inference is proposed, which uses the fuzzy membership degree of influencing factors to calculate the charging probability of users at each road node. The travel and charging behavior of large-scale users are then simulated to predict the spatiotemporal distribution of charging demand. Finally, taking the predicted charging demand distribution as an input and the number of CPLs and charging parking spaces as constraints, a bi-objective optimization model for simultaneous location and size planning of CPLs is constructed, and solved using the fuzzy genetic algorithm. The results from a case study indicate that the planning scheme generated from the proposed methods not only reduces the travelling and waiting time of EV users for charging in most of the time, but also controls the upper limit of the number of charging piles to save construction costs and increase the total profit. The research results can provide theoretical support and decision-making reference for the planning of electric vehicle charging facilities and the intelligent management of charging parking lots.

Research and Design of Intelligent Parking Management System based on the YOLO Algorithm

Given the difficulty in managing parking lots and inefficient utilization of parking spaces at university and college campuses, this paper designs an intelligent campus parking management system with functions such as license plate recognition (LPR), online parking space reservations, campus parking navigation, and mobile app payment through the parking space detection technology based on You Only Look Once (YOLO) algorithm, Internet of Things (IoT) technology, and cloud platform technology. This system obtains information relating to license plates, parking spaces, etc. from sensing nodes with the IoT technology and transmits the collected information through NB-IoT technology to a cloud platform for storage and management to facilitate information exchange between hardware and software. This paper describes the architecture of the intelligent parking management system, parking space detection technology based on the YOLOv4 algorithm, and hardware and software design of the system. The paper proposes an effective solution to parking problems facing colleges and universities. The paper concludes that the intelligent campus parking management system based on the YOLOv4 algorithm can prevent the haphazard parking of vehicles and traffic congestion at open campuses and therefore has important value for application and popularization.

Optimization Method for Allocating Peak-Period Parking Demand in Hub Parking Lot Clusters

With the expansion of urban scale and the popularization of multi-modal transportation, transportation hubs, as the link of multi-modal travel, are becoming increasingly important in urban development and residents’ lives. In situations of high parking demand, the increase in road traffic volume and parking search delays exacerbates the service pressure on hub parking lots and the traffic congestion on surrounding roads. Therefore, reasonable parking demand allocation is one of the key solutions to this problem. Based on the analysis of the vehicle parking search process, this paper constructs a model for estimating parking search delay on roads outside hub parking lots and proposes an optimization model for parking demand allocation aimed at minimizing the total parking search delay of vehicles. Finally, taking a major transportation hub in Nanjing as a case study, data were obtained through field investigations and simulation experiments to identify peak parking demand periods and calibrate the model parameters. The results show that the average vehicle delay was reduced by 4.5%, with a total reduction of 13,860 s in vehicle delay for parking demands at the hub within one hour. Therefore, by optimizing the allocation of parking demand, the average delay for vehicles searching for parking can be reduced to a certain extent.

PERENCANAAN SIRKULASI RUANG PUSAT TERAPI HOLISTIK DI SAMARINDA

Samarinda is one of the most populous cities in East Kalimantan. Living in a densely populated urban area has a greater impact on the risk of mental health disorders. Poor mental health has an impact on physical health. One effort for health care is by conducting holistic health therapy as an alternative to healing overall health, starting from a person's physical, emotional, social, and spiritual health. The purpose of this planning is to produce a holistic therapy center building design in Samarinda with circulation planning that can facilitate building users in their activities in it. Through the analysis method by analyzing the area and building circulation. Analysis of area circulation is carried out by arranging vehicle lanes, parking and building positions. Analysis of building circulation is carried out by determining the pattern of vertical and horizontal space circulation. This planning produces a holistic therapy center in Samarinda that has a circulation space that can increase comfort and facilitate access for building users, so that this therapy center can meet the needs of urban physical and psychological health and become a place for a healthy environmental community

Multi-objective robust optimization for optimal operation of gas-electricity networks with the penetration of integrated P2G and electric vehicle parking lots

Energy is considered one of the most important human needs. Therefore, various energy resources are exploited to meet human needs. Among all available resources, electricity and natural gas have accounted for the largest share in meeting these needs. Accordingly, management of these resources is one of the most important issues in different societies. This paper presents a multi-objective optimization model for optimal management and operation of the power distribution network and natural gas network as well as reducing carbon emissions. In this modeling, the natural gas network and distribution power network are connected through two electric vehicle parking lots (EVPLs) and two gas-fired units (GFUs), and these two EVPLs and GFUs exchange energy with each other. The EVPLs are equipped with various facilities including power-to-gas (P2G) systems and natural gas storage that facilitate energy exchange between the two networks. The modeling presented in this article is based on mixed integer linear programming, so the nonlinear equations including power flow equations, the Weymouth equation and the cost functions of GFUs are also linearized using various methods. It should be noted that the price of purchased electricity poses uncertainty which is modeled using robust optimization techniques. The proposed model is tested on the 33-bus power distribution network and the 20-node natural gas network. The results show that the presence of EVPLs significantly reduces the operational costs of the natural gas network and power distribution network and carbon emissions.

The Influence of Vehicles Parking on the Roadside as Reduction of Lane Width on Traffic Performance

The city of Poso is experiencing rapid economic growth, attracting many newcomers and developing various commercial facilities along its streets. This study analyzes traffic performance on three road sections in Poso City: Jl. Pulau Irian Jaya (District Road), Jl. Pulau Sumatera (National Road), and Jl. Kasintuwu (Provincial Road), focusing on the impact of on-street parking as a side friction and lane width reduction on road capacity and degree of saturation (DS). The methods used are MKJI 1997 and PKJI 2023. The study results indicate that road capacity decreases and DS increases significantly when using the PKJI 2023 method compared to MKJI 1997. Jl. Pulau Irian Jaya experienced an increase in DS from 0.372 to 0.410 (side friction) and from 0.874 to 0.94 (lane width reduction). Jl. Pulau Sumatera showed an increase in DS from 0.716 to 0.776 (side friction) and from 0.75 to 0.84 (lane width reduction). Meanwhile, Jl. Kasintuwu showed an increase in DS from 0.114 to 0.118 (side friction) and from 0.20 to 0.21 (lane width reduction). These results suggest that the PKJI 2023 method provides a more conservative estimate, indicating a more significant decline in traffic performance compared to MKJI 1997.

Day-ahead electric vehicle charging behavior forecasting and schedulable capacity calculation for electric vehicle parking lot

The Electric Vehicle Parking Lot (EVPL) aims to address the growing demand for EV charging infrastructure. EVs connected to EVPLs have extended access times compared to those at public charging stations. Consequently, EVPL owners can aggregate the schedulable capacity of connected EVs to participate in day-ahead and ancillary service markets, thereby gaining economic benefits. However, achieving this objective is hindered by the lack of accurate day-ahead forecasts of EV charging behavior. To address this issue, this paper introduces a novel day-ahead forecasting method for EV charging behavior at EVPLs, alongside a strategy for calculating EV schedulable capacity based on these forecasts. Unlike existing methods, this paper presents a day-ahead time-of-use clustering forecasting strategy, which provides more detailed and accurate predictions of EV charging behavior, eliminating the need for numerous assumptions during schedulable capacity calculations. The study demonstrates that the proposed method, validated using actual historical data, enables precise forecasting of EV charging behavior. Furthermore, the proposed day-ahead schedulable capacity calculation strategy is shown to be both effective and practical.