Participatory Technique Supporting Environmental Management: A Systematic and Bibliometric Review

The increasing need to manage natural resources sustainably, driven by population growth, requires the simultaneous use of Participatory Techniques (PT) and landscape planning for structured decision-making. We conducted a bibliometric and systematic review to provide an overview of PT usage, identifying evolution in scientific production. We considered the number of publications and citations, prominent journals, and highly cited articles on scientific papers published in the Web of Science database between 1993 and 2023. A total of 415 articles related to PT were identified. After content evaluation, 19 critical articles were selected that underpin the growing combined use of models and indices with PT, enhancing the robustness and credibility of decision-making processes.

A Trailblazing Framework of Security Assessment for Traffic Data Management

Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior.

Methodology for Automatically Setting Camera View to Mile Marker for Traffic Incident Management

Traffic incident management (TIM) is a FHWA Every Day Counts initiative with the objective of reducing secondary crashes, improving travel reliability, and ensuring safety of responders. Agency roadside cameras play a critical role in TIM by helping dispatchers quickly identify the precise location of incidents when receiving reports from motorists with varying levels of spatial accuracy. Reconciling position reports that are often mile marker based, with cameras that operate in a Pan-Tilt-Zoom coordinate system relies on dispatchers having detailed knowledge for hundreds of cameras and perhaps some presets. During real-time incident dispatching, reducing the time it takes to identify the most relevant cameras and setting their view on the incident is an important opportunity to improve incident management dispatch times. This research develops a camera-to-mile marker mapping technique that automatically sets the camera view to a specified mile marker within the field-of-view of the camera. Over 350 traffic cameras along Indiana’s 2250 directional miles of interstate were mapped to approximately 5000 discrete locations that correspond to approximately 780 directional miles (~35% of interstate) of camera coverage. This newly developed technique will allow operators to quickly identify the nearest camera and set them to the reported location. This research also identifies segments on the interstate system with limited or no camera coverage for decision makers to prioritize future capital investments. This paper concludes with brief discussion on future research to automate the mapping using LiDAR data and to set the cameras after automatically detecting the events using connected vehicle trajectory data.

Traffic Incident Management Performance Measures: Ranking Agencies on Roadway Clearance Time

This study develops a procedure to rank agencies based on their incident responses using roadway clearance times for crashes. This analysis is not intended to grade agencies but to assist in identifying agencies requiring more training or resources for incident management. Previous NCHRP reports discussed usage of different factors including incident severity, roadway characteristics, number of lanes involved and time of incident separately for estimating the performance. However, it does not tell us how to incorporate all the factors at the same time. Thus, this study aims to account for multiple factors to ensure fair comparisons. This study used 149,174 crashes from Iowa that occurred from 2018 to 2021. A Tobit regression model was used to find the effect of different variables on roadway clearance time. Variables that cannot be controlled directly by agencies such as crash severity, roadway type, weather conditions, lighting conditions, etc., were included in the analysis as it helps to reduce bias in the ranking procedure. Then clearance time of each crash is normalized into a base condition using the regression coefficients. The normalization makes the process more efficient as the effect of uncontrollable factors has already been mitigated. Finally, the agencies were ranked by their average normalized roadway clearance time. This ranking process allows agencies to track their performance of previous crashes, can be used in identifying low performing agencies that could use additional resources and training, and can be used to identify high performing agencies to recognize for their efforts and performance.

Evolution of Air Traffic Management Concept of Operations and Its Impact on the System Architecture

The air traffic management system(ATM)has the task of ensuring safe,orderly and expeditious flow of air traffic.The ATM system architecture is very much dependent on the concept of operations(ConOps).Over the years the evolution in ConOps has resulted in changes in the ATM′s physical architecture,improving its physical infrastructure,increasing the levels of automation and making operational changes to improve air traffic flow,to cope with increasing demand for air travel.However,what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture.This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions.This paper reviews the changes in the ConOps over the years,proposes a temporally invariant ATM functional model,and discusses some of the main key technologies expected to make significant improvements to the ATM system.

A simulation study of using active traffic management strategies on congested freeways

The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were selected to evaluate the impacts of ATM such as speed harmonization, shoulder utilization, and ramp metering. Test beds used in this study were at places where an ATM is either proposed or previously implemented, i.e., where data exists for condi- tions prior to and after the implementation of ATM. Data collected from the test beds were used in a simulation model to evaluate the impacts of each ATM strategy on speed, travel time, and crash rates. Simulation results indicated that the implementation of speed harmonization on US 90 showed a 14% reduction in crashes and a 2%-3% increase in freeway speed; the implementation of hard shoulders on US 90 showed a 39% increase in travel time, 22% increase in freeway capacity and 60% decrease in delays; and the implementation of ramp metering on US 59 between Bissonnet St. and Fondern road showed a decrease of 23 % in freeway travel time, a 14% increase in freeway speed and 11% decrease in accident rates.

SESAR:The Past,Present,and Future of European Air Traffic Management Research

The Single European Sky Air Traffic management(ATM)Research(SESAR)project is the technological pillar of the European Commission’s Single European Sky Initiative to modernize ATM.Here,we describe the process of establishing SESAR and the main parts of the project:the research and development(R&D)part,which is led by the SESAR Joint Undertaking;the deployment part,which is managed by the SESAR Deployment Manager;and the European ATM Master Plan,which collects and lays out both the R&D and deployment needs.The latest European ATM Master Plan was adopted just prior to the current pandemic.The huge loss in air traffic due to the pandemic,and the speed of the recovery of the aviation industry will require reprioritization,but the main elements that have been established-particularly those in support of the environment-remain valid.

Base Station Energy Management in 5G Networks Using Wide Range Control Optimization

The traffic activity offifth generation(5G)networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation(4G)network technologies that demand always for varied control and data signalling based on control base station(CBS)and data base station(DBS).Hence,this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network.As the new radio(NR)based 5G network is configured to transmit signal blocks for every 20 ms,the proposed algorithm implements withstanding capacity of on or off based energy switching,which in-turn operates in wide range control by carrying out reduced computational complexity.The proposed Wide range of control for base station in green cellular network using sleep mode for switch(WGCNS)algorithm toon and off the base station will work in heavy load with neighbouring base station.For reducing the overhead duration in air,heuristic versions of the algorithm are proposed at the base station.The algorithm operates based on the specification with suggested protocol-level to give best amount of energy savings.The proposed algorithm reduces 40%to 83%of residual energy based on the traffic pattern of the urban scenario.

Review on artificial intelligence techniques for improving representative air traffic management capability

The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.

A Framework for Intelligent Decision Support System for Traffic Congestion Management System

Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.

Traffic Characteristics Based Dynamic Radio Resource Management in Heterogeneous Wireless Networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

Traffic Management Mechanism in IN and Its Implementation

This paper presents the design of traffic management mechanism in BUPT--IN system.Three function entities, SMF, SCF and SSF, cooperate to complete the traffic management function. The superiorities of this mechanism and the trend of network management in iN (intelligent network) are also discussed.

Sustainable Energy Management with Traffic Prediction Strategy for Autonomous Vehicle Systems

Recent advancements of the intelligent transportation system(ITS)provide an effective way of improving the overall efficiency of the energy management strategy(EMSs)for autonomous vehicles(AVs).The use of AVs possesses many advantages such as congestion control,accident prevention,and etc.However,energy management and traffic flow prediction(TFP)still remains a challenging problem in AVs.The complexity and uncertainties of driving situations adequately affect the outcome of the designed EMSs.In this view,this paper presents novel sustainable energy management with traffic flow prediction strategy(SEM-TPS)for AVs.The SEM-TPS technique applies type II fuzzy logic system(T2FLS)energy management scheme to accomplish the desired engine torque based on distinct parameters.In addition,the membership functions of the T2FLS scheme are chosen optimally using the barnacles mating optimizer(BMO).For accurate TFP,the bidirectional gated recurrent neural network(Bi-GRNN)model is used in AVs.A comprehensive experimental validation process is performed and the results are inspected with respect to several evaluation metrics.The experimental outcomes highlighted the supreme performance of the SEM-TPS technique over the recent state of art approaches.

Application and Development of Systems Engineering in Road Traffic Management

Traffic management is an important contribution in the sustainable development of urban traffic.The complexity of traffic problems determines the difficulty of traffic management.Therefore,traffic management needs the guidance of scientific theories.This paper explores traffic management systems engineering for management road traffic.First,the paper looks at the contents of road traffic management from a systems perspective.Second,the paper briefly describes systems engineering,and explains the necessity and feasibility of the combination of the traffic management and systems engineering.At last,the paper puts forward the concept of traffic management systems engineering using a systems framework.

Integration Theory and Optimal Application of the Traffic Accident Management System

With the development of the social economy,the traditional transportation mode will be replaced by the new mode which emphasizes the integration and cooperation between the transportation modes.The advent of automobilization in China has further intensified the pressure of the road traffic.The traffic jam alarm caused by the traffic accidents is increasing year by year.The minor accidents that can be dealt with quickly account for more than 70%of the traffic accidents.Traditionally,when dealing with the minor accidents,car owners often choose to stay on the spot and wait for the traffic police to deal with them.It is easy to cause"minor accidents and big traffic jams",which lead to the congestion of a road,a bridge and even a block.

Ontology-Based Approach for Human Competency Gap Analysis in Air Traffic Management:A Case Study of Georgia

The Global Air Navigation Plan is a flexible global engineering approach that allows all States to advance their Air Navigation capacities based on their specific operational requirements.Aviation professionals have an essential role in the transition to,and successful implementation of the GANP.The research work is focused on the creation of methodology for the partial automation of the comparison competences of Air Traffic Management(ATM)personal and synthesis of training courses and modules,using a formal,ontology-based approach as a tool to solve these problems.One of the problems in the implementation of the GANP is that,on the one hand,there are currently no unified requirements for all categories of ATM personnel,and on the other hand,the development of ATM technologies is far ahead of the pace of training of personnel of appropriate qualifications.This problem becomes even more noticeable in countries that have just started an active modernization of ATC systems and do not have enough experience in this field.The paper describes the general methodological approach based on the education ontology modelling for human competency gap analysis in ATM and for gap analysis between the university curricula outcomes and the ATM requirements.The ontology of key personnel competencies issues for the design and integration of large-scale future ATM programmes is proposed.

Human Resource Management:A Case Study of the Air Traffic Controller Strike in 1981

The article discusses several hemispheres of human resource management based on a typical case review. The study presents the main problems of the case from both employees and organizations; the issued problems involve compensations and benefits,restructuring,job design,and training. Based on the analysis of the case,two alternative solutions state that the potential routes for the organizations to avoid serious negative results. The study introduces a number of recommendations that can be used as a reference for other organizations to avoid similar risks.

Is the feminization of labor harmful to agricultural production? The decision-making and production control perspective

Even today,academics continue to debate the effect of feminization of agricultural labor force on agricultural output.By considering the dimensions of participation in decision-making and production,this study divides the various agricultural production models into three types:(i)the traditional model of decisions made either jointly by men and women or by men alone while both genders participate in production,(ii)complete feminization of agricultural decision-making and the production labor force,and(iii)feminization of the agricultural production labor force only.This study investigates the effects of combining or separating decision-making and production in regard to agricultural development in the context of feminization of the agricultural labor force.Using follow-up data collected from 2004–2008 by the Ministry of Agriculture of China,we built a comprehensive panel data model to test our hypotheses.Our research shows that in comparison to traditional agricultural households and fully feminized agricultural labor forces,partially feminized production resulted in lower grain yield and technological advancement.The feminization of agricultural labor does not necessarily have a negative impact on agricultural output,especially since heavy manual labor is being increasingly replaced by agricultural machinery and outsourcing of tasks.The degree of feminization of the decision-making and production processes should be an important consideration when evaluating the purported negative effects of the feminization of agricultural labor.