Operation Of Parks Research Articles

Key Sensing Systems in Autonomous Driving

With the rapid and dynamic evolution of autonomous driving technology. The escalating demand for transportation that is not only safer but also more efficient has spurred an intense exploration of advanced sensing technologies. This article centers on the sensor system within the domain of autonomous driving. The principal methods encompass an in-depth study of various distinct sensors such as lidar, cameras, radar, and ultrasonic sensors. The research findings reveal that these sensor systems can synergistically collaborate to furnish highly precise environmental perception. Specifically, lidar offers elaborate 3D depictions, granting vehicles a comprehensive understanding of the surrounding landscape. Cameras capture essential visual cues, providing detailed information regarding road signs, traffic conditions, and the presence of pedestrians or other vehicles. Radar effectively detects the velocity and distance of objects, significantly enhancing the vehicle's capacity to anticipate potential hazards. Moreover, ultrasonic sensors play a critical role in short-range detection, ensuring safety during parking and low-speed operations. The conclusion is that the seamless cooperation and continuous refinement of these sensor systems are of utmost significance for successfully realizing autonomous driving. This not only elevates traffic safety to a higher level but also holds profound implications for enhancing efficiency and convenience on the roads.

Optimized energy storage configuration considering joint operation of multiple parks

Abstract The park’s growing reliance on photovoltaic and wind power faces challenges due to their intermittent and peak-opposite nature, causing a mismatch with load demand and highlighting the issue of energy consumption. This paper addresses this by proposing an optimized energy storage configuration method for multi-park joint operation, considering demand differences. It involves designing a joint operation mode with energy storage and an operation method for energy storage under joint demand. An optimization model is developed to minimize configuration costs while adhering to system and energy storage constraints. The paper’s method is validated through case studies.

IOT Based Parking Lot for Smart City

Abstract: This project presents an intelligent parking lot system using infrared sensors to detect available parking spaces in realtime. The system improves user convenience and reduces traffic congestion by providing accurate parking availability data. Infrared sensors, chosen for their reliability and low power consumption, are installed in each parking slot. The sensor data is processed centrally and shared via thingspeak website and digital displays. The system will be piloted in a section of the parking lot, with calibration ensuring accuracy. Results show reduced time searching for parking and decreased congestion. The system's scalability, energy efficiency, and real-time capabilities enhance user experience and optimize parking operations. Future developments include predictive analytics and expansion to other hightraffic areas.

Economic analysis of parking, vehicle charging and vehicle-to-grid services in the era of electric vehicles

Economic analysis of parking, vehicle charging and vehicle-to-grid services in the era of electric vehicles

Employer-provided parking: Departure time choice, investment decision, and welfare effects

Employer-provided parking: Departure time choice, investment decision, and welfare effects

Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems

Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems

Predicting and explaining parking space sharing behaviors using LightGBM and SHAP with individual heterogeneity considered

ABSTRACT Shared parking plays a crucial role in alleviating parking pressure, but the heterogeneity of potential suppliers’ intentions was often ignored. This study addresses this gap by adopting an interpretable Machine Learning (ML) framework to investigate parking space sharing intentions, considering individual differences. A survey with 383 respondents from mainland China was conducted, and a Latent Class Model (LCM) identified three distinct groups of potential suppliers. The Light Gradient Boosting Machine (LightGBM), outperforming other ML models, was used to quantify factors influencing sharing behaviors. The SHapley Additive exPlanation (SHAP) approach revealed that influential factors vary across different latent classes. These findings provide insights for shared parking operators to encourage potential suppliers’ participation in shared parking.

Organizational Life Cycle Assessment of a wildlife park in northern Germany

PurposeOrganizational Life Cycle Assessment (O-LCA) quantifies environmental impacts and identifies key environmental hotspots within a company’s value chain. Assessment of environmental impacts from animals has been carried out for livestock production, pet keeping, and hunting. One not yet considered application relates to touristic activities that involve animal husbandry, such as zoos or animal parks. Thus, the aim of this paper is to conduct the first O-LCA for a wildlife park and identify related hotspots.MethodO-LCA was applied in the context of a wildlife park in northern Germany from a cradle-to-gate perspective for the reference period of 2022 considering the impact categories climate change (GWP), acidification (AP), eutrophication (EP), and photochemical ozone formation (POCP). The number of visitors (437,049 people) and animals of 16 different animal groups (787 animals of more than 100 species (e.g., wolves and birds)) was set as reference flow as the organizations’ activities are focused on tourism and animal species conservation. Information on animal feed, litter, suppliers, and transportation was derived from the animal care department's data, complemented by interviews with park experts and analysis of relevant documents and invoices.Results and discussionThe organization had emissions of around 3,176 t CO2-eq. (GWP), 15 t SO2-eq. (AP), 6.5 t PO43- eq. (EP), and 7.2 t NOX-eq. (POCP) in 2022. Transportation of visitors being the main hotspot across all impact categories (e.g., 57.5% of GWP). Methane from ruminant respiration additionally accounts for 16 t CO2-eq. (0.5% of total GWP). For AP and EP, feed and food for Animal Care show high impacts with 23–27%, respectively. The lowest impacts show Electricity & Heat and End of Life of waste generated on site with around 1–8%. Carrying out a sensitivity analysis for the main hotspot transportation of visitors shows a 40% potential reduction for GWP, when visitors from Hamburg (90%) would use public transport exclusively.ConclusionThis paper is the first to apply O-LCA to a wildlife park, identifying environmental hotspots and filling a gap in the assessment of tourism-related impacts on animals. This study pioneers the application of O-LCA to wildlife parks, identifying environmental hotspots in a tourism context. By analyzing multiple impact categories and park operations, we have gained a comprehensive understanding of the environmental footprint of wildlife parks.

Fuzzy Logic Algorithm Optimization for Safe Distance Control on Arduino-Based Reverse Parking System and SRF04 Sensor

This research aims to develop a smart parking system that can accurately control the distance between vehicles and obstacles during reverse parking maneuvers. By integrating fuzzy logic algorithms into the system, this study seeks to improve the precision and reliability of distance control, thereby improving the overall safety of parking operations. The utilization of the Arduino platform and the SRF04 sensor allows real-time data processing and accurate distance measurement, i.e. this research contributes to the effectiveness of the proposed system. The application of fuzzy logic optimization in this context is expected to provide a powerful solution for safe reverse parking, offering potential benefits in terms of comfort and accident prevention in parking scenarios, especially for cars that still do not have obstacle detection sensors at the rear of the car

Coordinated Multi-Scenario Optimization Strategy for Park Photovoltaic Storage Based on Master-Slave Game.

Optimizing the operation of photovoltaic (PV) storage systems is crucial for meeting the load demands of parks while minimizing curtailment and enhancing economic efficiency. This paper proposes a multi-scenario collaborative optimization strategy for PV storage systems based on a master-slave game model. Three types of energy storage system (ESS) application scenarios are designed to comprehensively stabilize PV fluctuations, compensate for load transfers, and participate in the frequency regulation (FR) market, thereby optimizing the overall operational strategy of PV storage systems in parks. The upper-level objective is to maximize the park operators' profit, while the lower-level objective is to minimize the user's power supply costs. Case studies demonstrate that this strategy can significantly increase the economic benefits for park operators by 25.8%, reduce user electricity expenditures by 5.27%, and lower curtailment through a load response mechanism, thereby promoting the development and construction of PV storage parks.

The nexus between visitor satisfaction and expenditure behaviour in national parks: The case of Dragon Palace National Park, Guizhou, China

The nexus between visitor satisfaction and expenditure behaviour in national parks: The case of Dragon Palace National Park, Guizhou, China

“We struggle to survive”: Exploring the whole systems energy injustices of solar photovoltaics in India

“We struggle to survive”: Exploring the whole systems energy injustices of solar photovoltaics in India

High-tech industry development: selection of technology parks operation model elements in the field of high technology

The article presents the justification of model elements choice for technology parks work in the sphere of high technologies in Russia. The methodology for creating the model, which was built on the position of borrowing the best practices of existing models of innovation infrastructure facilities operation and functioning in the country, has been given. It has been proposed to form a rating among operating technology parks, within the framework of which a comprehensive assessment of technology park management companies’ performance has been carried out according to four groups of indicators (sub-indexes) such as subjects investment attractiveness, information openness, technology parks internal ecosystem, and management company efficiency. Based on the rating results, the leaders among technology parks have been identified, and their behavioral models adopted as reference metrics for the model to be developed. Based on the leaders’ position, it has been proposed to choose the best technology parks model in the field of high technologies in terms of their interaction with residents. Recommendations have been presented for the technology parks infrastructural model as the most promising for private companies, while investment projects should be developed considering federal requirements and standards to ensure their successful implementation and achievement of the set goals. Technology parks in the sphere of high technologies play a key role in Russian economy development. They contribute to the development of innovations, new technologies, high-tech industries, and knowledge-intensive business. It is important that such technology parks development is optimally organized with due regard to modern requirements and regulatory measures.

Waiting for the next new ride at Disney world? Understanding the determinants of capital expenditures among theme parks

PurposeThe purpose of this paper is to investigate the determinants of capital expenditures (CAPEX) in the theme park industry, particularly following the financial stresses induced by the COVID-19 pandemic. CAPEX drivers are poorly understood due to the idiosyncratic nature of this industry, which is dominated by a few large players. It also aims to identify the variables influencing both the growth and maintenance components of CAPEX among U.S. theme park operators.Design/methodology/approachThe paper uses contingency theory to analyze both financial and nonfinancial data from U.S. theme park operators between 2009 and 2021. The paper also uses partial least squares structural equation modeling to manage issues of multicollinearity and to ensure robustness in the findings.FindingsThe analysis identifies several key determinants of CAPEX. Resources and the presence of competing theme parks in proximity to an operator’s parks positively affect CAPEX. Conversely, higher leverage, dividend payouts, intellectual property (IP) dominance and population density in areas with their active parks correlate with reduced CAPEX. The paper also notes distinct trends in maintenance versus growth CAPEX post-COVID-19, with maintenance CAPEX increasing as operators invest in existing assets while growth CAPEX trending downwards.Research limitations/implicationsThe study’s scope is confined to U.S.-based theme park operators, limiting the generalizability of the findings internationally. Moreover, data limitations restrict the sample size due to the consolidation of the industry players, potentially affecting the statistical power of the analysis.Practical implicationsThis research offers significant insights for theme park operators, industry analysts and policymakers. Understanding the factors influencing CAPEX can aid operators in strategic planning and investment decisions, especially in a post-pandemic economic environment where efficient capital allocation will be crucial for recovery and growth. A major contribution of this research is the development of a new measure for IP dominance, which allows theme park operators to quantify the impact of IP on their investment strategies.Originality/valueThis study contributes uniquely by incorporating both financial and nonfinancial determinants in analyzing CAPEX within the theme park industry, a sector significantly impacted by the pandemic. It introduces novel metrics for assessing the impact of IP on CAPEX and differentiates between the factors driving maintenance and growth expenditures. The findings enrich the existing literature on hospitality management and provide actionable insights that could guide the strategic financial decisions of theme park operators.

Does small mean unimportant? A review of pocket park values and associated factors

PurposeThis study aims to explore the value of pocket parks and associated factors, as well as the differences between pocket parks and other green spaces, and finally to identify the role of pocket parks in cities.Design/methodology/approachThis study adopts a systematic literature review method to identify 85 articles from the Web of Science and other sources. The Nvivo12plus software was employed to qualitatively analyse the value of pocket parks, and the key associated factors were visualised via the NVivo word cloud function.FindingsAs a result, pocket parks reflected high social, environmental ecological, cultural aesthetic values but low economic value. Compared to other large-scale green spaces, the particularity of pocket parks lies in their ambiguity and temporality of space and high reliance on the surrounding environment. Small and scattered pocket parks in the city are like “convenience stores” and “green magnets”, and connectivity should be strengthened to promote urban regeneration.Originality/valueCompared with previous studies that mostly focused on large urban green spaces, the originality of this study is that it elaborates on the importance and values of pocket parks and proposes the particularity and roles of pocket parks in cities, which enriches the theoretical knowledge of pocket parks. In terms of practical applications, the proposed diverse values and associated factors contribute to guiding the planning, management and operation of pocket parks. Moreover, the roles of pocket parks help enhance park connectivity and establish a park network system.

Two-Carrier Cooperative Parking Robot: Design and Implementation

Abstract Parking robots have been designed to alleviate parking stress in crowded areas. Existing models occupy large spaces and have limited adaptability to uneven ground. This paper aims to enhance the performance of parking robots by proposing a leader-follower-control based two-carrier Cooperative Parking Robot (CPR). In this system, two omnidirectional carriers operate on a tight cooperative transporting algorithm to achieve steady motion in their collaborative handling and transportation of the target car into the designated parking space. The novel CPR was designed, modeled, and implemented. The results indicate that the proposed CPR approached the targeted car and maintained a consistent position and heading angle in its cooperative parking operation at the speed of 0.6 m/s. The parking robot exhibited significant improvement in its adaptability to cars and uneven ground, and its compact configuration reduced its space occupation. Therefore, the proposed CPR has been proven robust for autonomous cooperative parking operations.

A smart parking system combining IoT and AI to address improper parking

The world is entering a new era of intelligent parking, with researchers exploring innovative solutions to enhance the parking experience. These solutions aim to simplify parking challenges for drivers, reducing stress caused by traffic congestion and the search for available spaces. This study presents an intelligent parking system driven by artificial intelligence (AI). It addresses inefficient and improper parking, providing drivers with detailed information about available spaces and improving their management. This approach empowers drivers with insights into parking availability, reducing time and fuel consumption. The system streamlines parking operations, ensures accurate spot availability information, and enhances overall efficiency and user satisfaction. The effectiveness of this proposed system is evidenced by a range of outcomes, including significant reductions in the time spent searching for parking and decreased fuel consumption along comparable travel routes.

The Parking Management System

This Parking Management System (PMS) is a comprehensive solution designed to streamline and enhance the efficiency of parking operations. Leveraging advanced technology, the system optimizes the utilization of parking spaces, reduces congestion, and improves overall user experience. Key features include real-time occupancy monitoring, automated payment processing, and smart allocation of available spaces. PMS not only ensures seamless entry and exit for vehicles but also integrates with mobile applications for convenient reservation and navigation. With a focus on sustainability, the system promotes eco-friendly practices by encouraging the use of electric vehicle charging stations and implementing intelligent traffic flow management.In summary, the Parking Management System represents a modern, user-friendly approach to address the challenges associated with urban parking, promoting a more organized and environmentally conscious urban environment. Keywords—Real-time Occupancy Monitoring, Automated Payment Processing

US National Park Service and concession staff perceptions regarding waste management in Yosemite, Grand Teton, and Denali National Parks

Each year, over 45,000 metric tons of waste are generated in US national parks through a variety of means, including park operations, visitation, and other sources. In an effort to address these impacts, the National Park Service (NPS) has partnered with commercial and non-profit organizations to implement the Zero Landfill Initiative (ZLI). The goal of the ZLI is to realize a steady decrease in waste generated in parks, and an increase in materials being sent for recycling. Through this initiative and aligning research, efforts to mitigate waste and recycling issues with visitors is underway; however, to date there have been no attempts to understand the perspectives of those individuals who manage these parks on a daily basis. This study explored Theory of Planned Behavior-based constructs regarding disposal of waste and recycling using surveys with NPS employees and park concession staff in Yosemite, Grand Teton, and Denali National Parks. Results indicate that perceived difficulty and moral norms related to disposal of waste and recycling are significant drivers of self-reported behavior and intent with NPS and concession staff. Generally, concession staff perceptions align with the goals of ZLI more than those of NPS staff. This research adds to the limited understanding of land mana­ger perceptions, and results provide justification for future messaging and trainings that could improve sustainable management of these and other NPS units in the future. Keywords: Park Management; Visitor Use; Recycling; Waste Management; Communication; Human Behavior; Leave No Trace

Optimal Parking Space Selection and Vehicle Driving Decision for Autonomous Parking System Based on Multi-Attribute Decision

Autonomous parking systems (APSs) can help drivers complete the task of finding a parking space and the parking operation, which improves driving comfort. Current research on APSs focus on the perception, localization, planning, and control modules, while few pay attention to the decision modules. This paper proposes a method for optimal parking space selection and vehicle driving decisions. In terms of selecting the optimal parking space, a multi-attribute decision method is designed considering the type of parking space, walking distance, and other factors. In terms of vehicle driving decisions, we first predict the behavior and trajectory of the target vehicle in a specific scenario, and then use a combination of rule-based and learning-based decision methods for safe and comfortable vehicle driving behavior decisions. Simulation results show that the proposed methods can find the optimal parking space according to the parking lot map and improve the efficiency and smoothness of vehicle driving while ensuring driving safety.