Vehicular ad hoc networks (VANETs) are characterized by high mobility of nodes and frequent changes in the network topology, which significantly complicates the process of routing data packets.It has been shown that traditional routing protocols are unable to promptly follow these changes and cannot be efficiently used in VANETs for vehicle to vehicle (V2V) communications.This is the reason why protocols based on reinforcement learning (RL) have been developed.These protocols enable constant monitoring of changes in the network environment, and adaptation of the routing process to those changes.In this paper, an analysis and comparison of the traditional and RL based routing protocols are performed in VANET scenario.The Ad hoc on-demand distance vector routing protocol (AODV) and AODV with Expected transmission count (ETX) metric are chosen as the representatives of traditional routing protocols, while the Adaptive routing protocol based on reinforcement learning (ARPRL) is chosen as the representative of routing protocols based on RL.The simulation results show that the ARPRL protocol has significantly better network performance in terms of packet loss ratio (PLR) and end-to-end delay (E2ED) in urban VANET scenario.
The needs of users of postal services are becoming more and more demanding for postal operators day by day.The environment in which the postal sector develops is constantly changing.Achieving quality standards, keeping pace with technological solutions, and developing new services and business models are real challenges for postal service operators.Within this paper, an overview of the current state of the postal services market, both at the global level and in the Republic of Serbia, is given.Also, following the conclusions of the Report of the Universal Postal Union on the development of postal traffic for the year 2022, a presentation of possible directions for the development of postal services through two advanced services is given: the sharing economy and sustainable logistics.
The growth of available information on the Internet and enormous diversity in user's behaviour indicate the exceptional importance of service personalization.Creating of the individual user profile is a key activity that precedes service personalization.Forming an automated user profile is the main challenge in development of the personalized applications that fully meet needs of the user.This research includes the information that needs to be modelled to represent different user profiles, how the information is collected, how to construct the user profile and finally how the user profile is used to deliver a personalized service.The proposed user profiling process includes three basic activities: data collection, user profile construction and personalization.Paper gives the comparison of the user profile methods and techniques.The findings showed that proposed user profiling process improves construction of the accurate user profile for effective service personalization.
Road safety key performance indicators (KPI) are the indicators reflecting those operational conditions of the road traffic system that are influencing the system's safety performance.The automated process of KPIs data collection, accompanied by advanced smart solutions in urban areas, smart in-car solutions, etc. is expected in the near future.The European Commission developed a set of common methodological guidelines for the data collection and estimation of the KPIs in the European Union countries.Internet of Vehicles is an emerging technology approach that can be expected to become a promising solution to overcome serious traffic issues.The objective of this paper is to explore the process of road safety KPIs data collection and sharing using Internet of Vehicles networking.In that context, a star rating of driver's behavior could be done, and such data could be shared aiming to better improve drivers' safety behavior.
The number and locations of facilities represent the most important decisions when modeling service networks.The facility location problem in the context of service networks is predetermined by the investment costs and/or achieving a certain standard of satisfying users' demand.Systems designed in this way are based on the idea that they will function in regular exploitation conditions, without any interference.However, various adverse events caused by intent, unintentional human activities, technological disasters or natural disasters can lead to a partial or complete cessation of the service networks.For the first time, this paper highlights the importance of the impact assessment of disruption events on the service networks where the r-interdiction median location model is presented as a potential solution approach in a case when these events occur.Also, an extensive overview of the state-of-the-art literature is provided.Finally, a numerical example of the determination of the most vulnerable points of service networks is given to illustrate the effects of potential disruptions, as well as appropriate preventive actions that eliminate or at least mitigate those situations.
The trend of depopulation of rural areas affects the reduction of the number of local facilities such as schools, post offices, and shops.There is often a fear that the closure of a local facility will negatively affect the availability of certain services and amenities of rural life.The concept of postal service has changed in parallel with the development and progress of human society.Today, this term goes beyond its primary role of connecting at all levels of society and becomes a service through which broader social goals are achieved.Due to its importance, which is reflected in the specific social value for both individuals and legal entities and the social role in the achievement of Sustainable Development Goals, positive impact on the environment, traditional cooperation with other state bodies, strengthening of patriotism, safety, and security, there is a need to this humane concept is protected, developed, diversified and maintained especially in underdeveloped and devastated areas and especially for the most sensitive population groups.
The entire telecom industry is going through a change that can be only compared to the change that data centers went through in the 2000s, both driven by Moore's Law.Open RAN is a crucial enabler of this transformation, allowing building networks to use a fully programmable software-defined RAN solution based on open interfaces that run on commercial, off-the-shelf hardware.This paper aims to present the O-RAN from a theoretical perspective, the pros, and cons of the O-RAN for mobile network operators and try to answer if the future of the RAN is going to be open.
The importance of efficient logistics processes in literature and practice has been recognized.In this paper, a new methodological approach for logistics process improvement, Logistics Field Audit (LFA) is proposed.The approach comprises seven interconnected steps: identification of needs and goals for LFA; priority definition of different LFA aspects for different subsystems; processes mapping, audit, and questionnaire preparation; implementation in each subsystem according to priorities; analysis and evaluation; the definition of preventive and corrective measures, continuous improvement and periodical audit.Basic aspects of LFA such as the operational, safety, environmental, and service quality aspect are identified.The approach is applicable in both logistics and non-logistics systems with special emphasis on logistics subsystems such as procurement, distribution, transport, warehouse, etc.The paper presents a case study of a warehouse system, with an emphasis on labor safety.Four types of warehouse workers were determined.The developed methodology provides the basis for future theoretical research and practical implementation.
Telekom Srbija is the first operator in the Western Balkan region with its own Internet of Things (IoT) ecosystem.The ecosystem is characterized by the following features: multitenant IoT platform; Long Range Wide Area Network (LoRaWAN) connectivity; technology proven through industry use cases with a large number of sensor devices and the associated application software; platform and application programming interfaces (APIs) for fast implementation and integration of new commercial use cases, and large capacity for fast network deployment.On that way, business partners are provided with a powerful environment for implementation of different use cases.The first use case based on this ecosystem referred to preventing theft of the company's underground telecommunication infrastructure.This article represented the state-of-the-art, the IoT ecosystem of Telekom Srbija, and the use case regarding protection of the underground cable infrastructure.
Delivery companies are trying to improve their business and thus respond to the increased number of requests due to the expansion of e-commerce.In addition, one of the basic parameters of the quality of the delivery service -availability, is increasingly difficult to maintain at an appropriate level due to the circumstances arising from the modern way of life and business.Users find it more and more difficult to use the services of shipments because their business and private obligations coincide with the working hours of delivery companies.One of the most modern solutions in the field of improving accessibility in this area is the application of mobile parcel lockers.The results of the analysis of their implementation by the AHP approach are presented in this paper.
This article presents our adaptation of the Ruin-and-Recreate (R&R) algorithm to solve the electric vehicle routing problem with time windows and multiple trips.We implement this adaptation in JSprit, an open-source vehicle routing problem solver.We showcase the framework for a case study in Lyon, France.In the case study, we assess the efficiency impact of adding charging constraints to a simulation of a fleet of autonomous delivery robots.The framework is tested on benchmark instances and compared with results from literature.
The transport system has always been closely linked to urban development.This study was motivated by the growing concerns over rising fuel prices, vehicle ownership and greenhouse-gas.There has been considerable interest on the effect of residential density on vehicle miles travelled (VMT).While this issue has been extensively researched, there remains uncertainty regarding how effective land-use planning might be used as an arsenal in reducing VMT.The study population was comprised of 530 668 households in Harare Metropolitan.Conferring to Krejcie and Morgan's (1970) formula the sample size for this study was 384 households at 95% confidence level.The study used stratified, convenience and purposive sampling.The researchers used a household survey to collect data from respondents.Exploratory factor analysis (EFA) was performed to test the validity of all the items used in the study.While the research hypothesis was tested using Structural Equation Modelling (SEM) in Amos version 21.The study concludes that residential density positively influences vehicle miles travelled.The fact that travel is a derived demand should encourage planners and policy-makers to consider residential development as an alternative approach to reducing vehicle miles travelled.
Transport policy represents a process of regulating and controlling the provision of transport services.In the past, the main emphasis was on the efficient transport connections and safety of drivers and other participants in transportation.These issues are still important and topical; however, due to the enormous increase of vehicles on the streets and harmful gas emissions, noise, congestions, and other negative effects of transportation, some other topics emerged that need to be considered in the design of sustainable development strategies, especially in big cities.This explanation leads to the conclusion that setting a transport policy represents a typical multi-criteria decision-making problem.There are usually certain alternative directions in the design of transport policy that should be assessed by more evaluation criteria, often opposed to each other.This is exactly the problem that is considered in this paper where three concepts of last-mile delivery of postal items are analyzed as the possible directions in the design of transport policy in cities.We applied three multi-criteria decision-making techniques: WASPAS, ARAS, and CoCoSo.The proposed methodology is tested and verified in a real-life case study considering the city of Niš.In the concrete case, the results showed that the best alternative in the design of last-mile delivery activities at the city level is the introduction of inner-city hubs.
Solving environmental problems caused by road transport, in particular problems of global warming and climate change is one of the biggest challenges today.Given that vehicles are significant sources of CO 2 emissions, many European countries have decided to speed up the transition from fossil fuel-powered vehicles to electric vehicles and thus contribute to the solution of these problems.Their experiences in this field can be very useful for other countries.For this reason, different financial incentives which are applied in European countries, as well as the effects of their implementation and therefore the ability to accelerate adoption of electric and other zero and low emissions vehicles are researched in this paper.Particular attention is given to financial incentives and their role in vehicle electrification policy in Norway, since it is the country with the most experience in this field in Europe as well as the country with large market share of electric vehicles.At the end of the paper, special attention is paid to financial incentives that favor these innovative technological solutions in the Republic of Serbia, as well as to reasons that explain the existing difference in the level of electrification of vehicles in the Republic of Serbia compared to other European countries.
Artificial neural networks (ANNs) are a promising modelling approach for predicting an airport's air passenger demand.The study proposed and empirically tested an artificial neural network model to predict the annual passenger demand for Huahin Airport, a regional and tourist focused airport located in Thailand.The ANN input variables included Thailand's population size, Thailand's real GDP, world jet fuel prices, Thailand total passengers carried, Thailand's tourist numbers and Thailand's unemployment rates.The data were trained using the Levenberg-Marquandt back-propagation algorithm.The ANN comprises eight neurons in the hidden layer and one neuron in the output layer.80 per cent of the data was used in the training phase with the remaining data divided into validation (10 per cent) and testing (10 per cent) phases.The proposed ANN provided very accurate prediction values.The coefficient of determination R value of model was around 0.995, and the mean absolute percentage error (MAPE) of the final ANN model was 13.27%.The study found that the four key determinants of Huahin Airport annual air passenger demand were Thailand population size, the commencement of AirAsia services at Huahin Airport, Thailand's tourist numbers, and Thailand's real GDP.
The gap acceptance method is one of the most widely used to analyze the capacity of roundabouts.The critical gap has a prominent role in this approach.In every country, driver behavior and local rules are examined and implemented in the local standard for capacity estimation.Hence, a reliable technique for assessing critical gaps can be of great importance.This paper presents an experimental investigation and analysis on whether it is possible to find the correlation between video-based gap acceptance parameters and some traffic parameters in Hungary.Thirteen single-lane roundabouts with different traffic flow rates were recorded for hours in various locations in and around Budapest to estimate the gap acceptance parameter (critical gap) and relate it to circulating and entry flow or the combination of both.Using only linear regression analysis, as a first step, no strong correlation was found between the critical gap and circulating flow and a lower correlation between the critical gap and entry flow.After implementation of a gradient boosted decision tree function, a stronger correlation was found between the critical gap and circulating flow, and an improved correlation between the critical gap and entry flow.The implemented correlation model shows a promising correlation between the critical gap and traffic parameters (circulating and entry flow).Our results indicate that the critical gap has a higher correlation with the circulating flow, and with the increase of the circulating flow, the critical gap value tends to decrease.
The city of Šibenik is one of the most attractive tourist destinations in Croatia.Its street parking is managed by a city company.In this paper, it was our aim to establish whether there was a difference in the methods of payment for street parking and the use of such services between different parking zones, as well as to determine the developments in the use of parking services and the impact of the SARS-CoV-2 pandemic.The analysis established the cyclical nature of the methods of payment for parking services and the use of such services by zones, caused by the tourist season.The research has shown that m-parking is the most frequently used method of payment for parking in the zones 0, 1 and 2, as well as that the significance of this method of payment declines in the summer months in comparison with winter.The research has also shown that the use of parking meters is the most prevalent in Zone 1+, while it is the least prevalent in Zone 0, whereas m-parking is most frequently used in Zone 1 and the least frequently in Zone 1+, while in Zone 0, bank cards are used more frequently in relation to other zones.A trend model has also been elaborated, and it was established that an average growth in the number of issued invoices of 209 per month is to be expected.
The urban accessibility and connectivity are enormously important factors to measure the convenience of life and the territorial liveability for residents, and they are also the most essential prerequisites for planning satellite cities in periphery near the metropolitan cities and for promoting satellite cities’ inclusive progression. Previously relative contributions demonstrated that although the metropolitan cities and their satellite cities are located quite close, but still existing the defeat of accessibility and connectivity. The article identified the need for improvements in innovating the way of eco-friendly mobility to realize the new generation green transportation under the context of all societies facing the dual pressure of environmental pollution and energy crisis. Therefore, the article presented a conceptual framework for connecting the boundary of the metropolitan cities and their satellite cities in the periphery. Through a qualitative analysis of the structure and composition, operation mechanism and the comparative advantages of the solar-powered aerial funicular and the case of Milan-Cusago, results from the research showed that it had potential as a new initiative for clean and green mode of urban mobility to further achieve accessibility and connectivity between the metropolitan cities and their satellite cities that contributes to transition for Smart Sustainable Cities.
The evaluation of residual stress is crucial since it has a significant impact on the component's lifetime and can cause breakdown or failure during manufacture, which may affect the economics, lives, and the environment.Residual stress analysis has now become a mandatory requirement in the automobile industry.Because each manufacturing process like machining, casting, heat treatment, and coating impacts the residual stress state, it can be pretty complicated and varied within the components.If the effects of these processes are well studied, it is possible to achieve a stress state in the part that will increase its lifetime and performance while lowering costs with an optimized method.This paper discusses the effect of residual stress on the automotive industry and illustrates how is residual stress participates in every manufacturing process of vehicles.
Underpinned by an in-depth qualitative instrumental case study research approach, this paper reviews the waste-to-energy (WtE) system at London Gatwick Airport.The airport opened its waste-to-energy (WtE) plant in 2016 and London Gatwick Airport was the first airport in the world to covert wastes to energy onsite.Category 1 and other types of organic waste are converted into biomass fuel that is used to power the processing plant and provide heating for the airport's North Terminal.The waste plant also provides power to the site's water recovery system.London Gatwick Airport's waste-to-energy plant generates 1MW of renewable energy and can generate 22,500kW of heat each day.The environmental-related benefits from this system include a reduction in truck vehicle journeys to external waste plants, which has resulted in lower vehicle-related carbon dioxide (CO 2 ) emissions, lower vehicle noise levels, and less vehicle congestion.The water recovered from the waste-drying stage is also used to clean waste bins located throughout the airport.This re-use of water has enabled the airport to reduce its annual water consumption by 2 million litres per annum.The ash recovered from the system's biomass boiler can be used to make low carbon concrete thereby reducing carbon dioxide (CO 2 ) emissions.Importantly, since 2016, no wastes have been disposed to landfill thereby mitigating the environmental impacts associated with landfill wastes.London Gatwick Airport has applied the circular economy principles to its waste management.As such, the airport aims to re-use and recycle waste wherever possible and those wastes that are unsuitable or not permitted for re-use or recycling are recovered for energy.Since Gatwick Airport's waste-to-energy plant (WtE) became operational in 2016, the annual volumes of wastes recovered for energy were 5,677 tonnes in 2016, 5,509.6 tonnes in 2017, 4,939.9tonnes in 2018, 3,930.5 tonnes in 2019, and 1,243.6 tonnes in 2020, respectively.
