Traffic Growth Research Articles

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything (IoE) which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay. However, these massive devices will lead to explosive traffic growth, which in turn cause great burden for the data transmission and content delivery. This challenge can be eased by sinking some critical content from cloud to edge. In this case, how to determine the critical content, where to sink and how to access the content correctly and efficiently become new challenges. This work focuses on establishing a highly efficient content delivery framework in the IoE environment. In particular, the IoE environment is re-constructed as an end-edge-cloud collaborative system, in which the concept of digital twin is applied to promote the collaboration. Based on the digital asset obtained by digital twin from end users, a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention (TPA) enabled Long Short-Term Memory (LSTM) model. Then, the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning (RL) technology. Finally, a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead. The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate, the average throughput, the successful content delivery rate and the average routing overhead.

Model for Determining Noise Level Depending on Traffic Volume at Intersections

The negative external effects caused by traffic growth have been recognized as the main factors that degrade city quality of life. Therefore, research around the world is being conducted to understand the impact of traffic better and find adequate measures to reduce the negative impact of traffic growth. The central part of this research consists of mathematical models for simulating the negative consequences of congestion and noise pollution. Four non-linear models for determining noise levels as a function of traffic flow parameters (intensity and structure) in the urban environment were developed. The non-linear models, including two artificial neural networks and two random forest models, were developed according to the experimental measurements in Novi Sad, Serbia, in 2019. These non-linear models showed high anticipation accuracy of the equivalent continuous sound level (Laeq), with R2 values of 0.697, 0.703, 0.959 and 0.882, respectively. According to the developed ANN models, global sensitivity analysis was performed, according to which the number of buses at crossings was the most positively signed influential parameter in Laeq evaluation, while the lowest Laeq value was reached during nighttime. The locations occupied by frequent traffic such as Futoska and Temerinska positively influenced the Laeq value.

Plasmonic Resonance-Enhanced Low Dark Current and High-Speed InP/InGaAs Uni-Traveling-Carrier Photodiode

High-speed and high-efficiency photodiodes are especially beneficial for exponential data communication traffic growth. However, improving high responsivity while maintaining low dark current and high bandwidth remains a challenge for vertical detector design. This study proposes a plasmonic InP/InGaAs uni-traveling-carrier photodiode with optical antenna arrays, which exhibits a low dark current of 2.52 nA at a −3 V bias voltage, a high bandwidth of over 40 GHz, and a high responsivity of 0.12 A/W. The absorption efficiency of the photodiode shows 2-fold improvement using plasmonic resonance generated by nanodisks at 1550 nm. This work designs a low dark current and high-bandwidth photodiode with improved responsivity, which provides a potential method for high-speed vertical photodiode design.

A comparison study on the growth pattern of traffic oscillations in car-following experiments

A recent car-following experiment (Experiment-I) showed that the speed standard deviation grows in a concave way along a platoon of vehicles following one another. This paper investigates the growth pattern of traffic oscillations in a platoon in another car-following experiment (Experiment-II) and compares it with that in Experiment-I. It is shown that the speed standard deviation also exhibits concave growth characteristics in Experiment-II. The hypothesis test show that there is no significant difference in growth pattern of speed standard deviation between the two experiments. However, since drivers are asked to follow closely in Experiment-II, the acceleration standard deviations, the driver sensitivities, and the strength of stochastic factors are larger than the ones in Experiment-I. Furthermore, a new comparison experiment is performed which indicates that traffic oscillation growth in the platoon in the set of experiments on a circular track is likely to be equivalent to that on a straight track.

RNN-Based Demodulation Framework for Spectrum Narrowing in Ultra-Dense WDM Networks

To cope with the continuous traffic growth, spectral efficiency needs to be enhanced. Ultra-dense WDM systems, where narrower guard-bands are inserted between wavelength-division-multiplexed (WDM) signals than those used in conventional dense WDM (DWDM) systems, are expected to offer higher spectral efficiency. However, such systems are hindered by the spectrum narrowing induced by wavelength selective switches (WSSs) at nodes. As a result, intersymbol interference (ISI) can be excessive. Linear digital filters widely used in typical digital coherent receivers can equalize the ISI. However, ISI equalization yields noise enhancement due to the interaction between ISI and amplifier noise. Sequence estimation can alleviate the impact of this interaction; however, to introduce sequence estimation into real systems, an ISI-imposing filter is needed because the adaptive filter used for polarization recovery automatically equalizes the ISI. Although the optimum ISI-imposing filter can be created with the proper spectrum model, its characteristics change frequently in real optical path networks. Therefore, we need to develop a demodulation framework that does not necessitate any spectrum models. In this letter, we propose a novel demodulation framework that uses a recurrent neural network (RNN) to simultaneously realize the ISI-imposing filter and sequence estimator. Extensive computer simulations show that our proposal increases the transmission distance in ultra-dense WDM networks.

Health burden of road traffic noise in the EU in 2020–2035

The negative health effects of road traffic noise in the EU are analyzed over the period 2020–2035. For a baseline scenario, with autonomous traffic growth and fleet development, we find that there will be 31 million highly annoyed persons and 15 million highly sleep-disturbed persons in the EU in 2030. The corresponding EU health burden in 2030 is equivalent to the loss of 1.7 million “healthy life years”. Various noise abatement scenarios are analyzed, with noise solutions such as quiet road surfaces, quiet tires, and electric vehicles. The health benefits of the scenarios are calculated as health-burden differences from the baseline scenario. The calculation methodology is based on the noise exposure distributions reported in 2017 by EU member states, for urban agglomerations and for major roads. Changes in noise exposure are calculated with EU model Cnossos for vehicle emission, considering different types of roads (residential streets, main roads, motorways,...), and taking into account the separate contributions of rolling noise and propulsion noise to the vehicle emission. Two different noise valuation methods are used to express the health benefits in Euros. The monetized health benefits are used as input for a cost-benefit analysis of the scenarios over the period 2020–2035. For quiet tires, for example, high health benefits and low costs are found, resulting in a high benefit-cost ratio. This work was part of a study for the European Commission, exploring different options for reducing the EU health burden caused by noise from road, rail, and air traffic.

Characteristics Analysis and Equilibrium Optimization of Mixed Traffic Flow considering Connected Automated and Human-Driven Vehicles

Considering the impact of informatization condition, vehicles on the road network are divided into connected automated vehicles (CAVs) and human-driven vehicles (HDVs), which follow the principle of system optimization and stochastic user equilibrium, respectively. Taking the road network reserve capacity maximization model under the condition of road capacity constraint as the upper-level programming and the traffic assignment model under heterogeneous flow environment as the lower level programming, then a bilevel programming model is constructed. Among them, the nonuniform demand growth multiplier is adopted for each OD pair to reflect the inconsistency of traffic demand structure growth, and the calculation of link capacity is related to the market penetration of CAVs. The incremental method, method of successive averages, and simulated annealing algorithm are used to solve the model, and the effects of different market penetration on road network capacity, travel time, and saturation are analyzed through a numerical example. The relevant data under different weights are normalized and the optimal deployment scheme of CAVs and HDVs in different periods is obtained by comprehensive evaluation. Meanwhile, the mixed equilibrium flow state is explored under the premise of given market penetration to verify the feasibility of the model and algorithm.

Decoupling Emission Reductions and Trade-Offs of Policies in Norway Based on a Bottom-Up Traffic Emission Model

The way Norway is spearheading electrification in the transport sector is of global interest. In this study, we used the Norwegian Emissions from Road Vehicle Exhaust (NERVE) model, a bottom-up high-resolution traffic emission model, to calculate all emissions in Norway (2009–2020) and evaluate potential co-benefit and trade-offs of policies to target climate change mitigation, air quality and socioeconomic factors. Results for municipal data with regard to traffic growth, road network influences, vehicle composition, emissions and energy consumption are presented. Light vehicle CO2 emissions per kilometer have been reduced by 22% since 2009, mainly driven by an increasing bio-fuel mixing and battery electric vehicles (BEV) share. BEVs are mostly located in and around the main cities, areas with young vehicle fleets, and strong local incentives. Beneficiaries of BEVs incentives have been a subset of the population with strong economic indicators. The incentivized growth in the share of diesel-fuelled passenger vehicles has been turned, and together with Euro6 emission standards, light vehicle NOx emissions have been halved since peaking in 2014. BEVs represent an investment in emission reductions in years to come, and current sales set Norway up for an accelerated decline in all exhaust emissions despite the continual growth in traffic.

SimDB in action

Array DBMSs operate on big N -d arrays. Cellular automata (CA) work on a discrete lattice of cells, essentially on N -d arrays. CA facilitate decision support as they realistically simulate complex phenomena including road traffic, fire spread, and urban growth. Array DBMSs can bring numerous benefits to the CA domain via a "database approach": powerful parallelization, out-of-the box array operators, and interoperability to name a few. On the other hand, CA expand the area of Array DBMS applications and open a wide range of R&D opportunities. However, it is not straightforward to make an Array DBMS to support CA simulation workloads. SimDB enables end-to-end CA simulations directly inside the ChronosDB array DBMS via numerous new components and is the first effort to run CA simulations entirely inside an Array DBMS. We also developed a new desktop application specially designed to showcase SimDB. The application features interactive components to graphically reveal the insights of SimDB internals. Moreover, our application provides a convenient GUI to comprehensively investigate how end-to-end road traffic simulations run entirely inside an Array DBMS.

Who should hold the baton of aviation sustainability?

Purpose In the past four decades, substantial air traffic growth has triggered enthusiasm in the aviation sector. At the same time, this growth has posed challenges to its financial and environmental sustainability commitments. A buzz has been centered on introducing and supporting aviation sustainability initiatives. These challenges have led to acknowledging the need to reduce aviation fuel consumption, a function of multiple factors. The different stakeholders having a diverse type of interplay govern the effective implementation of the factors at different decision levels (strategic, tactical and operational). Thus, the present study aims to critically examine various decision levels involved to understand opportunities and requirements related to aviation sustainability. Design/methodology/approach In this study, the best–worst method is used to quantify different decision levels’ role on various factors affecting aviation fuel consumption. Findings The results of this study signify that tactical-level decisions are most influential in reducing aviation fuel consumption with the highest impact (0.41) followed by operational-level decisions (0.30) and strategic-level decisions (0.29), respectively. Research limitations/implications The results point toward the critical role of middle-level hierarchy, i.e. aircraft manufacturers, airlines and others in the aviation industry’s sustainable growth. Thus, middle-level stakeholders must be inspired and empowered to act, being at the center they link the other two levels. Originality/value This study has added to the body of knowledge by exploring the decision-making competencies needed by different aviation sector stakeholders. It also presents the possible options available in the sector and the role of stakeholders at different levels in exploiting and implementing the sustainable aviation sector changes.

Impact of SOA-Based Add-Drop Switch Nodes on High-Capacity Multicarrier Transmission for Metro-Access Networks

Internet-generated traffic growth is forcing the development of new low-cost solutions in metropolitan area networks (MANs), in particular in the transceiver and network node architectures. Semiconductor optical amplifier (SOA)-based wavelength blockers can be used as fundamental building blocks to add and drop optical channels in the node architecture of several network hierarchical levels. Even if its employment is advantageous in terms of costs and amplification bandwidth, the SOA can operate in a nonlinear regime. This work analyzes the impact of SOA-based node crossing on high-capacity discrete multitone (DMT) signals. In order to properly evaluate the interplay between optical channels and SOA self-gain modulation, both external and direct modulations are considered. Dual-sideband (DSB) and single-sideband (SSB) DMT variants are taken into account, showing no significant difference in the impact of SOA crossing for external modulation of a DFB laser. On the other hand, an important effect of subcarrier suppression arises on DSB DMT direct modulation of a vertical cavity surface emitting laser (VCSEL), less consistent for SSB DMT direct modulation. The analysis allowed to properly choose the bias current for the SOA employed in an experimental setup used to evaluate the transmission performance in a MAN scenario including add-drop lossless switch nodes. The experimental results demonstrate that a target capacity of more than 50 Gb/s per channel can be achieved in a 116-km MAN network composed of an SOA-based metro-access node and two metro-core aggregators, considering the transmission of three 25-GHzspaced DMT channels.

Smart Urban Mobility: When Mobility Systems Meet Smart Data

Cities around the world are expanding dramatically, with urban population growth reaching nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by 2050. The economic contribution of the transport sector represents 5% of the GDP in Europe and costs an average of US <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 482.05 billion in the United States. These figures indicate the rapid rise of industrial cities and the urgent need to move from traditional cities to smart cities. This article provides a survey of different approaches and technologies such as intelligent transportation systems (ITS) that leverage communication technologies to help maintain road users safe while driving, as well as support autonomous mobility through the optimization of control systems. The role of ITS is strengthened when combined with accurate artificial intelligence models that are built to optimize urban planning, analyze crowd behavior and predict traffic conditions. AI-driven ITS is becoming possible thanks to the existence of a large volume of mobility data generated by billions of users through their use of new technologies and online social media. The optimization of urban planning enhances vehicle routing capabilities and solves traffic congestion problems, as discussed in this paper. From an ecological perspective, we discuss the measures and incentives provided to foster the use of mobility systems. We also underline the role of the political will in promoting open data in the transport sector, considered as an essential ingredient for developing technological solutions necessary for cities to become healthier and more sustainable.

The Climate and Ozone Impacts of Black Carbon Emissions From Global Rocket Launches

AbstractAerosol emissions from spaceflight activities play a small but increasing role in the background stratospheric aerosol population. Rockets used by the global launch industry emit black carbon (BC) particles directly into the stratosphere where they accumulate, absorb solar radiation, and warm the surrounding air. We model the chemical and dynamical response of the atmosphere to northern mid‐latitude rocket BC emissions. We initially examine emissions at a rate of 10 Gg per year, which is an order of magnitude larger than current emissions, but consistent with extrapolations of space traffic growth several decades into the future. We also perform runs at 30 and 100 Gg per year in order to better delineate the atmosphere's response to rocket BC emissions. We show that a 10 Gg/yr rocket BC emission increases stratospheric temperatures by as much as 1.5 K in the stratosphere. Changes in global circulation also occur. For example, the annual subtropical jet wind speeds slow down by as much as 5 m/s, while a 10%–20% weakening of the overturning circulation occurs in the northern hemisphere during multiple seasons. Warming temperatures lead to a ozone reduction in the northern hemisphere by as much as 16 DU in some months. The climate response increases in a near linear fashion when looking at larger 30 and 100 Gg emission scenarios. Comparing the amplitude of the atmospheric response using different emission rates provides insight into stratospheric adjustment and feedback mechanisms. Our results show that the stratosphere is sensitive to relatively modest BC injections.

Publisher’s Note

Railways have a significant role to play in sustainable transportation. Rail travel is currently the only mode of rapid, large-scale, long-distance transport for both freight and passengers that offers zero carbon dioxide emissions at the point of use. However, our railway infrastructure needs to be more robust and resilient to the combined effects of climate change, traffic growth and increases in vehicle loads and speed. Rail buckling is of increasing concern as environmental temperatures rise and traffic loads, speed and intensity of use increase. A key indicator and control of the propensity for track buckling is the stress-free temperature of the rails. However, determining the actual stress-free temperature of a given section of track is challenging. Knowledge of the factors affecting stress-free temperature will help in the identification of vulnerable sections of track and the development of an appropriate maintenance regime. This paper reviews and discusses the factors affecting stress-free temperature in ballasted railway track with continuous welded rails (CWR).

Case Study of Traffic Forecasting of Nh-3 (New Nh 848) Section, Vadape to Thane

On account of the recent thrust on developing and improving highways in order to boost national economy, the government of India recognizes that the expansion and development of efficient road network is one of the pre-requisites for country’s economic development. The rate of traffic growth had always been a significant concern in the development of road infrastructures over the years, as it could either lead to premature failure of the pavement or could result in the wastage of valuable resources. The present study attempts on forecasting future traffic growth on Vadape-Thane section of NH-3 (New NH-848) from 539.200 to 563.00 km. In this research, traffic growth rate forecasting is done with the help of part registration of vehicle, economic growth of state and nation, socio-economic parameters, future economic growth, transport demand elasticity. The job of traffic forecasting becomes subjective and approximate with the hindrances of availability of proper data and fluctuation of economic parameters.

Software-defined optical intra-data center network and access control Strategy

The continuously emerging cloud services provide an unprecedented traffic growth into the large-scale data centers (DCs) globally. In this paper, we introduce an optical DC network (DCN) architecture to organize the servers into computing clusters. Since a high percentage of the total DCΝ traffic is served within a cluster, we assume two distinct networks: the intra-cluster passive optical network that handles the traffic destined to any server of the same cluster and the inter-cluster one to route the traffic to any other cluster. The servers interconnection within the passive optical intra-cluster network causes low power consumption, while the Top-of-Cluster (ToC) switch requires less ports than a relative Top-of-Rack (ToR) one to interconnect the same number of servers within the intra network, reducing even more the total power consumption. In the data plane, the intra- and the inter-cluster networks use separate wavelengths. In the control plane, the software-defined networking (SDN) paradigm is followed. Especially, in each cluster we adopt a cluster controller to coordinate the medium access control (MAC) in both the intra and inter-cluster networks. Unlike other studies that assume electrical connectivity with the controller, we consider that it is performed in the optical domain to guarantee the effective synchronized operation of the control and data planes. In our work, we focus on the intra-cluster network. We propose a synchronous transmission software-defined bandwidth allocation (SD-BA) MAC protocol to fairly coordinate the collisions-free transmission of different quality of service traffic categories in the intra-cluster network, based on the wavelength and time division multiplexing (W&TDM) techniques. The proposed DCN architecture along with the SD-MAC protocol provides scalability and efficiency. Simulations results show that the proposed SD-BA MAC protocol achieves almost 100% bandwidth utilization, while it reaches at high loads 145% higher throughput, 573% lower delay and 233% less dropped packets as compared to the relative DMAC network architecture (Zheng and Sun, Apr. 2020) [24]. Also, the proposed intra-cluster DCN architecture is compared to some other currently leading relative ones in terms of throughput and power consumption and it is proven to be a performance and energy efficient DCN solution.

Desain Bahu Jalan Letjen S. Parman, Kelurahan Panjer, Kecamatan Denpasar Selatan, Kawasan Niti Mandala Renon Denpasar - Bali

Letjen S. Parman Roadside design, Sumerta Kelod, County District East Denpasar. Denpasar is one out of nine districts/cities and it is the most populated in Bali Province. Rapid population growth leads to an increase in its population density that affects traffic growth in Denpasar City. Letjen S. Parman is one of the business district roads in the Renon Field area located in the heart of Denpasar City that is often used for public with or without vehicles, which makes this area dense and requires a balance of infrastructure and supporting traffic signs and signals to ensure safety and enhance convenience. Roadsides of Letjen S. Parman Road is still often converted by the public into a parking space and a marketplace. The purpose of this study was to research traffic rules along Letjen S. Parman road and users’ opinions on it. Methodology employed to conduct the study was direct survey and collecting the data by direct field observations, interviews, and questionnaires. The research revealed that, according to traffic laws, Letjen S. Parman roadsides were not supposed to be misused by road users. Pedestrians who use Letjen S. Parman roadsides also feel disturbed by road users who inappropriately turned them into parking spots or a marketplace. The result of the study is related to design recommendations to solve traffic problems along Letjen S. Parman Road as well as a point of reference for relevant agencies and government officials.

Traffic simulation in the LoRaWAN network

LoRaWAN is one of the most commonly used technologies serving the internet of things (IoT) and machine-to-machine (M2M) devices. The traffic growth in the LoRaWAN network gives rise to many problems, which are solved using mathematical modelling. The actual task, in this case, is the development of a traffic simulation model in the LoRaWAN network. This article discusses the issues of traffic simulation in the LoRaWAN network and its research using the MATLAB system. The authors have developed a LoRaWAN network server model as a queuing system with incoming self-similar traffic in the MATLAB system using a separate subsystem for the input traffic modelling allowing to change the number of sources in the LoRaWAN network. The simulation results made it possible to establish the dependences of the network server’s buffer memory, the probability of packet loss from the incoming self-similar traffic parameters, and reveal the possibilities of traffic modelling in the MATLAB system.

Effectiveness of Handover Control Parameters on Handover Performance in 5G and beyond Mobile Networks

Mobility management is essential in mobile communication networks to provide a smooth connection during users’ mobility. Handover control parameters (HCPs), such as handover margin (HOM) and time-to-trigger (TTT), are major and essential factors in mobility management that must be defined carefully to make efficient handover (HO) procedures. Their impact becomes more critical with the deployment of fifth-generation (5G) mobile networks and beyond (B5G). This is due to the different characterizations of next mobile networks, such as the use of millimeter-wave (mmWave) bands, the ultradense deployment of small base stations (BSs), large mobile connection traffic growth, and other more critical factors. The case becomes more sensitive with the high mobility speed scenarios. This study proposes different HCP system settings to be investigated and analyzed over B5G networks. They will be investigated with various mobile speed scenarios to illustrate their impact on the network performance. Various key performance indicators (KPIs) are considered to evaluate and validate system performance, such as reference signal received power (RSRP), HO probability (HOP), HO ping-pong (HOPP), radio link failure (RLF), HO interruption time (HIT), and HO failure (HOF). Results show that the various system settings provide different and significant impacts on the performance of B5G networks. Furthermore, the setting of HCP1 obtained the best performance in RSRP and RLF with -69.7 dBm and 4.8%, respectively, while the optimum performance of HOPP, HIT, HOP, and HOF is achieved in the HCP6 setting with 0%, 0.02 ms, 0.05%, and 0%, respectively. Moreover, the overall outcome of all HCP settings is 54.94%. These results indicate a tradeoff between RLF and HOPP with various HCP settings in B5G mobile networks. Thus, the HCP system settings must be adjusted carefully considering other factors, such as mobile environment and use case.

Analysis of Air Transport Stake Holders Perceptions and Motivations about Long Term Innovations Towards Sustainable Aviation Energy Paradigms

Aviation sustainability and GHG emissions reduction are academic and social trending topics. Air transport intensive energy use together with its constant pre-pandemic growth and the difficulties to evolve towards non-carbon-based energy paradigms, conform an environmentally “worrying frame”. Emissions reduction initiatives comprise aircraft technology and operation improvements, tax schemes, compensation and trading, efficient infrastructures, and sustainable aviation fuels. All of them have been subject of extensive academic analysis. Aspects that have been almost neglected in this analysis are the personal motivation and commitment from air transport stakeholders to pursue longer term technology developments towards sustainable energy paradigms. This paper explores those aspects by using a novel methodology where experts were interviewed prior to the COVID-19 pandemic (2017-2018) and during the pandemic (summer 2021), aiming at exploring the evolution of their beliefs regarding aviation sustainability, focusing in the expectations regarding aviation energy paradigm changes. Additionally, a survey was run among professionals of the aviation and energy sectors performing a quantitative analysis, triangulated with the interviews’ results. Aviation professionals keep relying on air traffic recovery and growth despite the COVID crisis. They are also conscious of the difficulties of the sector to enact the application of emissions reduction technologies and policies. However, there is not consensus in the strategies with the highest potential, although some tendencies have been identified: whilst enthusiasm about aircraft electrification has cooled down, a higher degree of reliance is put in new engine architectures. Fiscal measures are either poorly valued or not well understood. Aviation should leverage the consensus on new engine architectures to achieve tangible emissions contention in the mid-term, increase efforts to improve and explain emissions trading and compensation schemes, keep developing new technologies to unveil their real potential, and manage social expectations realistically, stressing its social and economic sustainability dimensions.