Parking Research Articles

Implementasi Peraturan Walikota Nomor 16 Tahun 2021 Tentang Tarif Retribusi Parkir di Tepi Jalan Umum

Ambon City residents, who park their vehicles at Amplaz, are subject to parking fees in accordance with Ambon Mayor Regulation Number 16 of 2021 concerning Parking Retribution Tariffs on Public Roads. Amplaz is subject to progressive parking rates, as it is a zone. So that the tariff for four-wheeled vehicles is no longer RP3000, and two-wheeled vehicles are no longer Rp2000 as in the implementation of the previous Ambon Mayor Regulation. The party who manages parking at Amplaz always urges Ambon City residents to have awareness in paying parking rates according to Ambon Mayor Regulation Number 16 of 2021 concerning Parking Retribution Tariffs on Public Roads. There are many cases when Ambon City residents pay less retribution, arguing that there is no small money and only big money. Even reluctant to pay at all. However, it is advisable to have awareness in paying parking fees. The party who manages parking at Amplaz prioritizes parking service satisfaction. This is done by providing optimal services, namely; directing vehicles in an orderly manner into and out of the parking area, protecting the vehicle from loss of goods, damage due to bumps, and theft of spare parts. Likewise, the friendly behavior of the parking employees. As a result, Ambon City residents cooperatively pay parking fees, according to Ambon Mayor Regulation Number 16 of 2021 concerning Parking Retribution Tariffs on Public Roads.

Operational uptime and other measures of performance of an open car park in fire

192 coupled wind and fire CFD simulations were performed using ANSYS Fluent to study the wind and fire interaction in an open car park. The natural ventilation was insufficient for removal of smoke and heat for the majority of investigated fires. Blockage effect was observed for wind directions parallel to the open walls, which resulted in reduced smoke removal and higher smoke temperatures. With known probabilities of all the investigated wind speed and directions, we have estimated the percentage of time in which fire outcomes are acceptable. This value was coined as the car park operational uptime, and was 84.9 %–92.8 % in relation to the fire with HRR = 1.4 MW; 36.5 %–56.1 % at 4.0 MW; 34.1 %–54.4 % at 6.0 MW and 12.13–25.5 % at 8.8 MW. In 6.22 % of wind cases, the velocity inside the car park exceeded 3.0 m/s, which could potentially contribute to the growth of the fire. Limitations of the study include the assumed wind probability distribution relevant to the Warsaw region, the single location of the fire used in the assessment and the implicit modelling of topography and architecture through an introduced wind profile and terrain roughness model.

ANALYSIS OF REGULATORY AND LEGAL SUPPORT FOR THE LEASE OF FREIGHT CARS

At the current stage of the implementation of deep socio-economic transformations aimed at the integration of Ukraine into the European Community, the lease of state and communal property plays an important role, first of all, in ensuring the development of the country's entrepreneurship. In addition, the rental of property is an important source of revenue for Ukrzaliznytsia and contributes to the maintenance of said property in proper condition. However, recently, due to unfavorable economic conditions, renting a car park for entrepreneurs is unattractive and not competitive compared to renting real estate in the private sector. One of the objective factors that have a negative impact on competitiveness and, as a result, on the reduction of rental volumes, is the complicated procedure for transferring wagons for rent, in particular, the long term of its implementation, etc. The solution of the mentioned problem requires appropriate adaptation of the legislative and regulatory framework, which regulates the issue of rent primarily by the Law of Ukraine «On Leasing of State and Communal Property», to modern market requirements. In the regulatory and legal acts of Ukrzaliznytsia, in fact, the relationship of leasing wagons is still regulated by the law adopted back in 1992 (the Law of Ukraine «On Leasing the Property of State Enterprises and Organizations. Currently», there is a need to create a fundamentally new legal framework for Ukrzaliznytsia, which will be based on the following principles: experience, competitiveness, responsibility, openness, responsiveness and integration into the web environment.The article analyzes the normative and legal support for the transfer of Ukrzaliznytsia's car park for rent. Considered the issue of the need for urgent development of local normative legal acts for the transfer of Ukrzaliznytsia's own wagons for lease in the context of changes in the current legislation of Ukraine. An analysis of the change in income from the sale of services for the use of Ukrzaliznytsia's own wagons for the period 2022-2023 was carried out and the beginning of 2024 through the electronic auction system PROZORRO. SALES.

Flexibility modeling for parking lots with multiple EV charging stations

The paper proposes an aggregated model that represents the flexibility potential of car parks equipped with multiple electric vehicle (EV) charging stations. The model is used in a stochastic optimization procedure to estimate in advance the maximum flexibility margins of the parking lot. The EV aggregator responsible for the charging stations offers intra-day ancillary services to the grid by specifying the possible margins within which the absorbed power can be varied, either up or down. These adjustments are made at the request of the distribution system operator, ensuring an appropriate level of EV charging. The effectiveness of the model is evaluated for parking lots with different numbers of charging stations and different daily profile forecasts of the number of EV arrivals and departures.

Implementation of Convolutional Neural Network Algorithm for Detecting Empty Parking Area Based on Raspberry Pi

Implementation of Convolutional Neural Network Algorithm for Detecting Empty Parking Area Based on Raspberry Pi

Potential-based dynamic parking navigation for autonomous vehicles: Near-priority vs. distant-priority

We aim to enhance the parking efficiency for a group of autonomous vehicles in a large parking lot during peak hours. Two parking principles, i.e. the near-priority (NP) and distant-priority (DP) principles, are proposed and quantitatively examined. The NP principle characterizes individual parking behavior, where autonomous vehicles tend to select available parking spaces that are closer in proximity. Conversely, the DP principle is proposed from the perspective of the entire parking system, prioritizing the allocation of more distant parking spaces within a certain range around each entrance. Two time indicators, including the overall parking time and the average parking time, are adopted to evaluate the performance of the two principles. A potential-based cellular automata (CA) model is proposed to formulate the dynamic parking process of vehicles in a two-dimensional space, where vehicle navigation is driven by a so-called potential field. Then, two dynamic navigation algorithms are developed for parking navigation under the NP and DP principles. Furthermore, by conducting a set of comparative simulation experiments, we have obtained some management insights into peak parking management in the era of autonomous driving.

A two-stage framework for parking search behavior prediction through adversarial inverse reinforcement learning and transformer

Parking scenarios are spatially dense and have a lot of interactions, making predicting vehicles’ search behavior crucial and challenging for autonomous driving. Existing data-driven prediction methods struggle to determine vehicles’ intents and consider the surrounding environment accurately. This study proposes a novel two-stage framework for parking search behavior prediction, involving parking intent and vehicle trajectory predictions based on imitation learning and deep learning. First, we develop an adversarial inverse reinforcement learning model for parking search intent (PSI-AIRL) learning from measured trajectory data in an actual parking lot. Then, we design an integrated convolutional neural network (CNN) and transformer model to forecast vehicle trajectory using historical observations and the predicted parking search intents. This two-stage framework achieves parking search intent prediction by applying global information about the parking lot while improving vehicle trajectory prediction’s accuracy and robustness. Finally, the experiments are conducted on the Dragon Lake Parking (DLP) dataset to compare our framework with state-of-the-art models. The results show that our model outperforms other baseline models in accuracy for parking intent and vehicle trajectory predictions. Moreover, our model shows exceptional accuracy and robustness in predicting across diverse parking scenarios.

Psychological Impacts of Urban Environmental Settings: A Micro-Scale Study on a University Campus

The environment’s psychological impacts on humans have been long studied, but many questions remain unanswered. We conducted a micro-scale study to examine the relationships among the objective characteristics of urban environmental settings, people’s subjective perception of such settings, and the related psychological responses. We employed a geo-enabled survey tool to gather data on individuals’ perceptions of the immediate environment within their daily activity space. The psychological processes assessed included emotional and affective states such as perceived stress and happiness. The data points were mapped on a high-resolution aerial image, which was classified to derive quantitative properties to examine the dose-response relationship between environmental exposure and psychological responses. Our results showed negative correlations between the momentary stress level and the amount of environmental elements such as water, trees, and grass. Positive correlations were detected between stress level and the amount of parking lot and barren land, as well as the distance to buildings. In terms of perceived happiness, positive environmental factors included water, trees, and artificial surfaces, with all other elements having negative correlations. Most of the correlations examined were not strong correlations. This could be due to the significant differences in how individuals respond to environmental stimuli.

Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach

The problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the increase in the number of vehicles in Indonesia, particularly in big cities, resulting in difficulties in finding parking spaces during peak hours. In this condition, drivers often have to compete for parking spaces. This research aims to develop a smart parking system that integrates YOLOv5 and OpenCV algorithms. This approach thoroughly combines both algorithms to identify parking spaces and detect vehicles in real time in various parking scenarios. It is carried out in an open area with reference to parking conditions at the BRIN Bandung office. This study collected data from three different parking lot conditions, namely empty, partially occupied, and full. In each condition, the system successfully detected the parking lots and vehicles accurately. The novel contribution of this research is the development of a smart parking system that uses an integrated approach, providing an effective solution to the challenges of parking lot availability and vehicle detection. Using the advantages of both algorithms, we successfully created a system that can identify parking spaces and detect vehicles accurately and efficiently under various parking circumstances. Therefore, this research makes a significant contribution to the development of smart and adaptive parking management technology.

RESISTANCE OF STRUCTURAL ELEMENTS OF CIVIL PROTECTION BUILDINGS AND STRUCTURES TO THE IMPACT OF AN EXPLOSION

The article presents the results of a comparison of the stability of the structural elements of the underground parking lot of an erected multistory civil building. The results of calculation of structural load-bearing elements (monolithic floor slab and pylons) to the impact of an explosion in the Lira CAD software with consideration of the requirements of the state Building standards of Ukraine are presented. It is shown that an increase in the instantaneous load of explosive pressure from 20 kPa (DBN B.2.2-5-97) to 100 kPa (DBN B.2.2-5:2023) will increase the maximum displacement of a monolithic floor slab by 11.9 times and the maximum reinforcement section by 5.8 times. This creates a real opportunity to develop new approaches to the planning of civil protection buildings and structures to ensure their operational reliability and resistance to the effects of an explosion.

Asphalt for underground and multi-storey car parks

Underground car parks and multi-storey car parks are not ordinary buildings, but demanding engineering structures that require special knowledge of those involved in the construction in planning, execution and monitoring. Car parks and underground garages require a permanent seal or a functioning surface protection system to protect against damage from moisture, chloride-containing de-icing agents and dynamic loads. The mastic asphalts used meet all the requirements placed on the surfaces of underground car parks and multi-storey car parks, but the asphalt concrete layers used in special construction methods can also meet these requirements.

Analysis of the current situation and a proposal to solve the parking problem in the center of the city of Banja Luka by introducing new street parking spaces

In the course of 2023, due to the expansion of the infrastructure, the center of the city of Banja Luka was left without four off-street to one street parking lots, which resulted in the loss of a total of 442 public parking spaces. Given that there is less and less free space on which new off-street parking lots could be built, the goal of the work is to find new locations suitable for the introduction of street parking spaces in the narrow and wider city center. As one of the solutions, Kralja Petra I Karađorđevića street and Vidovdanska street proved to be the best. In part of these streets, one-way traffic takes place on a road with three traffic lanes, and in terms of dimensions, it is possible to introduce street parking lots without causing traffic congestion. In this way, 2.2 kilometers of road would be obtained on which 220 new street parking spaces could be built, which fully correspond to the location, and provide safety and easy access to the parking space.

Traffic Management on The Cikereteg-Pancawati Road in The Caringin District Tourism Area Bogor District

Traffic as part of transportation planning is a vital indicator of tourism development. Bogor Regency is one of the favorite tourist destinations in Jabodetabek. One of the tourist attractions in Bogor Regency is natural tourism around the Puncak Bogor area. This study aims to analyze land use around Jalan Cikereteg-Pancawati, analyze the performance and level of traffic service on the road, and conduct a SWOT analysis for traffic management strategies. The study used GIS to analyze changes in land use and analyzed the level of road service on Jalan Cikereteg-Pancawati. The traffic performance analysis was conducted by analyzing the volume values and degrees of saturation on Sundays and Thursdays. The land use analysis showed that the area is dominated by forests, plantations, and rice fields, indicating great potential as a tourist area. The traffic performance analysis revealed that Sundays have higher volume values and degrees of saturation than Thursdays, with the highest degree of saturation occurring on Sunday segment 3. The study concludes that the traffic management strategy for Jalan Cikereteg-Pancawati should focus on managing pavement repairs and road widening, providing bus and car parking, and utilizing available human resources and supporting regulations for the development of Bogor Regency as a natural tourism area. The study's findings suggest that effective traffic management is crucial for the sustainable development of natural tourism in Bogor Regency. The proposed traffic management strategies can help alleviate traffic congestion and improve the overall tourist experience, ultimately contributing to the region's economic growth and social well-being.

Constraint Optimization Model for Dynamic Parking Space Allocation.

Managing car parking systems is a complex process because multiple constraints must be considered; these include organizational and operational constraints. In this paper, a constraint optimization model for dynamic parking space allocation is introduced. An ad hoc algorithm is proposed, presented, and explained to achieve the goal of our proposed model. This paper makes research contributions by providing an intelligent prioritization mechanism, considering user schedule shifts and parking constraints, and assigning suitable parking slots based on a dynamic distribution. The proposed model is implemented to demonstrate the applicability of our approach. A benchmark is constructed based on well-defined metrics to validate our proposed model and the results achieved.

“There’s nothing left to tax”: the effects of automobility on the downtowns of America’s mid-size cities 1913–2013

ABSTRACT This article uses digitized Sanborn fire insurance maps and property tax data to assess the combined effects of highway construction and the increase in parking in downtown Bridgeport, CT. We find that between 1913 and 2013, Bridgeport lost nearly 1.9 million square feet of taxed effective square feet to interstate construction and devoted another roughly 2.2 million square feet to surface parking. Using 2013 tax rates, we find that property tax revenue shrank to just over a quarter of 1913 levels, from a projected $19 million (in 2013 dollars) in 1913 to $5 million in 2013. Land use also became less diverse and more concentrated, dominated by large commercial and tax-exempt parcels. The concentration and lower tax revenue reduced the resilience of downtown. This paper provides a new method to estimate the effects of highway construction and develop predictions for the effects of highway removal. We estimate that $3 million in tax revenue could be restored by highway removal, and a further $2 million by building housing on surface parking lots, doubling the current tax base. Increasing residential uses downtown would be particularly useful in restoring the diversity of uses, supporting neighborhood retail, and providing citizen advocates for downtown.

Rainstorm-induced flood risk assessment in developed urban area using a data-driven approach with watershed units

Rainstorm flooding in developed urban areas has become a global focus. This study proposes a data-driven approach to urban rainstorm flood risk assessment. In contrast to the existing research, this study focuses on terrain watersheds as an assessment unit. Using Changsha as the study area, an inventory of 238 historical rainstorm flood locations was produced using automatic web crawling and literature data mining. Subsequently, an assessment model was developed based on a Bayesian algorithm and 16 influencing factors, and its accuracy was verified using a receiver operating characteristic curve. Because underground infrastructure is prone to backflow at its entrances and exits during rainstorms, the developed model was used to assess the backflow risk of two typical underground structures subjected to three rainstorm return periods: 5 (scenario 1), 10 (scenario 2), and 100 years (scenario 3). The conclusions are as follows: (1) The proposed method has a prediction accuracy of 88 % for flood risk. The most influential factors were H11 (proportion of impervious surface), H4 (mean elevation), and H1 (rainfall), contributing 52 %, 14.3 %, and 11.9 %, respectively. (2) Watersheds are classified into “Very Low,” “Low,” “High,” and “Very High” based on the degree of flooding impact, accounting for 83.6 %, 11.9 %, 3.9 %, and 0.7 %, respectively. Watersheds classified as “Very High” are mainly distributed in the central region. (3) A total of 48 subway stations (7.9 % of the total) and 148 underground parking lots (6.5 % of the total) in the study area are located in “Very High” risk areas. (4) Compared to that in scenario 1, the proportion of underground entrances and exits with a “Very high” protection level in scenario 3 increased by approximately 10 %. In conclusion, this framework can assist urban planners in understanding the risks of urban flooding and mitigating potential flooding impacts.

Can self-reliant societies be potential adopters of electric bicycles? Examining the role of sociopsychological influences among the university employees in India

Electric bicycles (e-bikes) are gaining popularity globally as green and active modes of transport. Research on e-bike adoption to date has predominantly investigated various extrinsic motivations to use an e-bike, and little is known about the psychological influences. Examining the influence of psychological determinants is crucial to comprehend the unobserved individual and social factors affecting e-bike adoption. This study aims to determine the sociopsychological influences associated with e-bike use among the daily commuters (employees) of two university campuses in India which represent self-reliant societies. The study extends the classic Theory of Planned Behaviour (TPB) framework to account for influences like personal norms, knowledge of e-bikes, and parking anxiety, in addition to fundamental TPB constructs (attitudes, subjective norms, and perceived behavioural control). Results are constructed by a structural equation model (SEM) for a sample of 347 non-users of e-bikes. SEM model indicates that among all TPB constructs, subjective norms are the strongest predictors of intentions to use e-bikes. Both subjective norms and attitudes have a significant positive effect on adoption intentions, whereas perceived behavioural control has a significant negative effect. Personal norms had significant indirect positive effects on e-bike use intentions with fundamental TPB constructs as mediators. Interestingly, parking anxiety (anxiety from missing the car parking spaces) positively, and knowledge of e-bikes negatively influence the e-bike adoption intentions. Further, comparison by psychological influences reveals that a significant difference exists between the perceptions of the two university commuters towards e-bike use, possibly due to the distinct terrain and climate characteristics of the universities. The study findings have implications for designing effective e-bike interventions and awareness programs seeking to promote e-bike adoption, particularly in self-reliant communities.

Application of Mesoporous Silicas for Adsorption of Organic and Inorganic Pollutants from Rainwater.

Precipitation is an important factor that influences the quality of surface water in many regions of the world. The pollution of stormwater runoff from roads and parking lots is an understudied area in water quality research. Therefore, a comprehensive analysis of the physicochemical properties of rainwater flowing from parking lots was carried out, considering heavy metals and organic micropollutants. High concentrations of zinc were observed in rainwater, in addition to alkanes, e.g., tetradecane, hexadecane, octadecane, 2,6,10-trimethyldodecane, 2-methyldodecane; phenolic derivatives, such as 2,6-dimethoxyphenol and 2,4-di-tertbutylphenol; and compounds such as benzothiazole. To remove the contaminants present in rainwater, adsorption using silica carriers of the MCF (Mesostructured Cellular Foams) type was performed. Three groups of modified carriers were prepared, i.e., (1) SH (thiol), (2) NH2 (amino), and (3) NH2/SH (amine and thiol functional groups). The research problem, which is addressed in the presented article, is concerned with the silica carrier influence of the functional group on the adsorption efficiency of micropollutants. The study included an evaluation of the effects of adsorption dose and time on the efficiency of the contaminant removal process, as well as an analysis of adsorption isotherms and reaction kinetics. The colour adsorption from rainwater was 94-95% for MCF-NH2 and MCF-NH2/SH. Zinc adsorbance was at a level of 90% for MCF-NH2, and for MCF-NH2/SH, 52%. Studies have shown the high efficacy (100%) of MCF-NH2 in removing organic micropollutants, especially phenolic compounds and benzothiazole. On the other hand, octadecane was the least susceptible to adsorption in each case. It was found that the highest efficiency of removal of organic micropollutants and zinc ions was obtained through the use of functionalized silica NH2.

Field experiment examining condensation reduction methods based on underground parking lot types

ABSTRACT In this study, condensation reduction methods with high field applicability to various types of underground parking lots in apartment buildings were selected and tested. The selected methods included floor-insulating drainage plates, induction fans with heating wires, and an automatic control ventilation system based on indoor and outdoor temperatures and humidity. The effectiveness of these methods was evaluated via real-world field experiments. The results indicated that while the insulating drainage plates initially blocked the cold, their long-term effectiveness matched that of normal drainage plates (difference 0.1°C). The induction fan with a heating wire showed average increases of 0.8°C and 2.7°C in wall surface temperature after one and three months, compared to normal induction fans. The absolute humidity of the automatic control ventilation decreased by 1.8 g/kg after 10 h of operation during rainy weather, whereas the manual control ventilation system increased by 0.6 g/kg under the same conditions. This study offers insights into the most effective application of these methods for various parking lot configurations.

A deep reinforcement learning traffic control model for Pedestrian and vehicle evacuation in the parking lot

As a necessary component of connecting the building interior and urban road network for evacuation, the evacuation of parking lots significantly impacts overall evacuation efficiency. However, existing emergency evacuation studies have ignored the control of pedestrian-vehicle mixed flow in parking lot environments, leading to underestimated evacuation time estimates. Therefore, this paper proposes a pedestrian-vehicle mixed-flow model to simulate the parking lot evacuation process at the microscopic level. Moreover, a deep reinforcement learning (DRL)-based evacuation control model is developed to control pedestrian evacuation speed. The numerical study shows that this control model can effectively reduce evacuation clearance time by 7.75 % when faced with enormous evacuation demands.