Traffic Scheme Research Articles

Bi-Level Optimization Model for Greener Transportation by Vehicular Networks

In general, dynamic traffic signal control or smooth driving benefits energy saving and CO2 emissions. However, most of studies in the past lack the integrated optimization of traffic signals control and instantaneous vehicle motion states simultaneously on energy saving and CO2 emission reduction. In this paper, a bi-level optimization model is proposed to minimize fuel consumption and CO2 emissions by considering real-time traffic signal control in road side unit (RSU) and instantaneous vehicle motion states optimization in on-board unit (OBU) synthetically. The RSU communicates with OBUs by vehicle wireless communication networks. Then, the traffic signal scheme in RSU is optimized with the received vehicle motion data sent from OBUs, and the system in vehicles optimize their speed and acceleration with the received traffic signal scheme sent from RSU. The simulation results indicate that the proposed model outperforms the existing Maximize Throughput Model (MaxTM) up to 10% in reducing fuel consumption and CO2 emissions especially when the traffic is heavy.

Environmental Protection in Scenic Areas: Traffic Scheme for Clean Energy Vehicles Based on Multi-agent

The low-carbon environmental protection and traffic congestion are two primary issues that people focus on highly and need to be solved efficiently. Under the circumstance, this paper designs a transportation simulation system for clean energy vehicles in scenic area based on multi-agent. From the view of introducing clean energy electric vehicles with limited funds and unlimited funds, we investigate the optimal introduction scheme and the optimal traffic scheme of clean energy vehicles to alleviate air pollution and tourist overcrowding. Combined with the specific circumstances of a famous scenic spot in China, we conduct the simulation and propose many countermeasures and suggestions to improve traffic scheme of clean energy vehicles.

Privacy-preserved traffic forecast scheme for intelligent transportation system

Traffic forecast in intelligent transportation system (ITS) involves the responsibility of traffic conductor, traffic control and so on, which is an important part in our daily life. Nowadays, traffic forecast schemes in ITS have been widely studied by researchers in many countries. However, these traffic forecast schemes do not take users' privacy into consideration. Users' privacy information is always leaked to the infrastructures and other users in the same system, and this can cause great damage to the information owner. In this paper, a privacy-preserving traffic forecast scheme is proposed, for ITS, to solve the problem of traffic forecast and privacy leakage together. The proposed scheme is based on a recurrent neural network which is operated by the infrastructures. In addition, the infrastructures or other vehicles can get nothing about the sender's privacy from the data package sent by a target vehicle. Our simulation can prove the advantages of our scheme in terms of the forecast accuracy. The security analysis can prove the privacy-preserving property. At the end of simulation part, we give a detailed analysis of forecast accuracy and the fault tolerance of our traffic forecast scheme.

TERS: a traffic efficient repair scheme for repairing multiple losses in erasure-coded distributed storage systems

The high repair traffic and the long repair time of erasure coding have posed a new challenge: how to minimise the amount of data transferred among nodes and reduce the repair time when repairing the lost data. Existing schemes are mostly designed for single node failures, which incur high network traffic and result in low efficiency. In this paper, we propose a traffic efficient repair scheme TERS suitable for repairing data losses when multiple nodes fail. To evaluate the repair cost and the repair time, we provide an implementation of integrating TERS into HDFS-RAID. The numerical results confirm that TERS reduces the repair traffic by 44% on average compared with the traditional erasure codes and regenerating codes. Theoretical analysis shows that TERS effectively reduces the repair time.

Bi-level optimisation model for greener transportation with intelligent transport system

In this paper, we propose a bi-level optimisation model (BLOM) with three algorithms. BLOM is intended for fuel saving and carbon dioxide emission reduction in both upper-level and lower-level model with intelligent transport system. Traffic signal schemes are optimised for minimising total fuel consumption passing through a road intersection in unit time in the upper-level model. At the same time, traffic signal information data are sent to the lowerlevel model in which vehicle motion states are optimised for greener transportation. Three algorithms include hybrid genetic algorithm and particle swarm optimisation in upper-level model with hybrid genetic algorithm and particle swarm optimisation in lower-level model (GA-PSO/GA-PSO), GA in upper-level model with PSO in lower-level model (GA/PSO) and GA in both level model (GA/GA) are realised to compare and improve the performance of the model. The simulation results derive GA-PSO/GA-PSO hybrid algorithm converges faster with the best resolution and least calculation time than other GA/PSO and GA/GA algorithms.

Sharing space or meaning? A geosemiotic perspective on shared space design

If urban design aims to influence sociality in public urban space, a nuanced understanding of the dialectic relationship of the social and the spatial matters. Especially in street design, this relationship is frequently presented in a simplified and unidirectional way, with the spatial producing the social. Design experiments often lack to fully recognize the role of users in influencing socio-spatiality in public urban spaces. This paper meets this lack and applies a geosemiotic approach to explore socio-spatiality on a central urban square in Oslo, Norway, designed in line with a street design idea called shared space. The paper frames the idea as an experiment aiming to alter the dynamic interrelationship of different semiotic systems, highlighting users’ agency in influencing socio-spatiality. The findings contrast most accounts in the literature tending to portray shared spaces as stable and calm traffic schemes. The paper reveals that such streetscapes may support a dynamic and constantly changing, mobile, socio-spatiality, based on permanently changing compositions of users and their distinct ways of interpreting and using the ambiguous environment.

Throughput Analysis of an Energy Harvesting Multichannel System Under Delay and Energy Storage Constraints

High power to guarantee strict performance requirement and low power to avoid energy depletion result in an inevitable conflict for a renewable energy harvesting communication system with finite energy storage. This paper proposes a generic approach to study the per-flow performance in such a multichannel system multiplexed by multiple flows. The queueing delay constraint and energy storage constraint are constructed to express the probabilistic bound of queuing delay and that of energy depletion, respectively. We study these constraints with the statistical information of the processes, including traffic arrivals and service, energy harvesting, and consumption. The lower bound of the long-term maximum per-flow throughput is then derived to meet the constraints under a specific system. The accuracy of the proposed approach is validated by simulation experiments. The analysis reveals how the sustained throughput is affected by various factors, such as the queueing delay and energy storage constraints, the packet size, the energy block size, the traffic scheduling schemes, the bandwidth allocation schemes as well as the interdependence among the channel service processes. Particularly, the analysis also provides valuable insight into traffic admission control from the viewpoint of small queueing delay and finite energy storage.

A quality of service–aware preemptive tidal flow queuing model for wireless multimedia sensor networks in the smart grid environment

The smart grid incorporates a two-way communication system between customers and the utility for advanced monitoring and intelligent control of supply and demand. Wireless multimedia sensor network can be treated as an organic supplement and a peripheral network in this two-way communication system. However, the challenging smart grid environment makes it difficult to achieve a high quality of service in wireless multimedia sensor network. This article proposes a prioritization mechanism that considers the heterogeneous characteristics of smart grid traffic. Specifically, an innovative channel allocation and traffic scheduling scheme, named the preemptive tidal flow queuing model, is presented. This scheme achieves differentiated services for diverse communication data when the wireless multimedia sensor network accesses the core network and ensures the performance for high-priority data at the expense of the performance for low-priority data. Simulation analyses show that the performance for high-priority messages can be reliably guaranteed and that the preemptive tidal flow queuing model satisfies the requirements for a wireless multimedia sensor network operating in the smart grid environment. This article offers three main contributions: the development of a prioritization mechanism specifically for a wireless multimedia sensor network in the smart grid environment, the proposal of the preemptive tidal flow queuing model, and the presentation of formulas and simulations to verify the performance of the preemptive tidal flow queuing model.

Distributed Optimal Cooperation for Spectral and Energy Efficiency in Hyper-Dense Small Cell Networks

Hyper-dense small cell networks have been recognized as one of the most effective ways to enhance spectrum and energy efficiency. However, performance enhancement can be significantly degraded due to inter-cell interference and traffic loading imbalance. Optimal cooperation has been widely used to tackle these problems by exploring and exploiting cooperative gains. Various potential cooperation opportunities exist among heterogeneous small cells. The denser the small cells are, the more cooperation opportunities a network may have. In this article, we first survey different optimal cooperation techniques from the network-wide and user-centric perspectives. To explore and exploit these cooperative diversity gains, we present a utility maximization framework, where a newly-defined utility function is formulated to jointly consider spectrum and energy efficiency. As a use case of the presented framework, we further propose a distributed interference-aware traffic offloading scheme. Numerical results validate the improved spectrum and energy efficiency of the presented win-win scheme.

Trends and Issues in the Use of Quantitative Color Schemes in Refereed Journals

This article reports on color usage in quantitative thematic mapping, drawing from an evaluation of maps published in eight geographical journals over the ten-year period from 2004 to 2013. During this period we found that color has become the preferred method to represent quantitative data sets, with the percentage of quantitative color maps relative to all quantitative maps rising from 18.4 percent in 2004 to 69.9 percent in 2013. We reviewed a sample of 440 maps from this period to assess the nature and appropriateness of their respective color schemes. We found the following frequencies of color scheme usage: spectral (30 percent), sequential (25.9 percent), diverging (25.7 percent), traffic (7.7 percent), and uncategorized (10.7 percent). Each scheme exhibited a distinct set of significant associations with particular map and data attributes, including subject matter, symbolization method, data polarity, and map size. Diverging and sequential schemes were the most effective, having strong associations with five key questions that we used to evaluate map effectiveness; for example, both schemes tended to be completely effective in terms of communicating spatial patterns and representing quantitative data values. Despite their popularity, spectral schemes were demonstrably unreliable and ineffective. Both spectral and traffic schemes were problematic for those with color vision deficiencies. Given the problems that we found with the use of various colors schemes, we make several suggestions for improving the design of maps appearing in refereed journals.

An adaptive traffic distribution scheme for CMT based on Lotka-Volterra model in multihomed networks

CMT (concurrent multipath transfer) can increase throughput and transmission efficiency in multihomed networks. However, it is still an important challenge about distributing traffic adaptively into multiple access networks. Based on LV (Lotka-Volterra) model, we propose an adaptive traffic distribution scheme. In the scheme, two competition modes are concluded, multiple S-D (source-destination) streams competition for bandwidth of one path and multipath competition for traffic between each multihomed S-D host pair. Actually, each access network can establish a path for S-D pairs. So, in the first mode, each path is analogous to a predator, and overall traffic in a multihomed host is reducing file transmission time and increasing network throughput in FTP service analogous to prey. Then, each path has to compete for the traffic by path information, e.g., bandwidth and congestion level. In the other one, if several S-D pairs pass through a shared path simultaneously, they will compete for bandwidth of the path. Here, each S-D pair is analogous to a predator, and the bandwidth of the common path is analogous to the prey. At last, compared with other three schemes, uniform traffic distribution, greedy path selection, random path selection in OPNET simulator, the proposed scheme can perform better on

A Traffic Restriction Scheme for Enhancing Carpooling

For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling) and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system.

P2P Traffic Optimization Based on Dynamic Network Information Aware

Peer-to-Peer (P2P) service may damage the interests of Internet Service Provider (ISP) because P2P traffic usually takes a lot of network link bandwidth and even overwhelms some network links. Aimed at the problem, mainstream solutions are usually optimizing P2P traffic through the interaction between applications and underlying network. However, current solutions still have two aspects of defects: one is that the interacted underlying network status information is immutable and can’t reflect the real-time dynamic changes because it is usually configured by ISP. The other is that some solutions may cause excessive traffic localization, which may greatly influence other services in the local network. In order to improve the above two defects and provide P2P users with better service experience, we propose an enhanced application layer traffic optimization scheme, in which more valuable network status information of underlying network is dynamically calculated and provided to P2P application. Extensive simulations demonstrate that our P2P traffic optimization scheme is superior to other solutions in terms of available bandwidth, resource transmission delay and user service experience.

Delay Insertion Based P2PTV Traffic Localization Considering Peer's Relaying Capability

Recently, P2PTV is a popular application to deliver video streaming data over Internet network. On the overlay network, P2PTV applications create the logical links between pairs of peers considering round trip time (RTT) without physical network consideration. P2PTV packets are shared over a network without localization awareness which is the serious problem for Internet Service Providers (ISPs). The delay-insertion-based traffic localization scheme was proposed for solving this problem. However, this scheme sometimes leads the newly joining peer to download streaming traffic from a local neighbor peer which has only scarce upload bandwidth. This paper proposes a novel scheme of delay-insertion-based traffic localization in which the router estimates relay capability to each relay peer candidate and leads the newly joining peer to connect to a neighbor peer with sufficient performance for relaying video data. Parameters were evaluated for the optimized condition in the relay capability estimation process. In addition, experiments conducted on a real network show that our proposed scheme can lead the newly joining peer to avoid downloading video data from insufficient relay capability peers and maintain video quality close to normal P2PTV system while efficient traffic localization in level of Autonomous System (AS) network.

TRIP-based transport travel demand model for intelligent transport system measure evaluation based on micro simulation

Nowadays, the systems developed to integrate real physical processes and virtual computational processes - the cyber-physical systems, are used in multiple areas such as medicine, traffic management, automotive engineering, industrial robots, nanotechnology and biological systems technology. The current paper provides an overview of CPS, their application in different fields of modern business, with main video recording accent to intelligent transport system. Various transport travel demand models are considered: trip-based, tour-based and activity-based. Strengths and weaknesses of each transport travel demand model are described. ITS strategies and its evaluation measures are considered for transport intelligent transport system effective management. An example of transport management solutions realisation process based on transport microscopic modelling is presented. The example is illustrated for one of the Latvian cities - Adazi, where it was necessary to improve accessibility level for local drivers for three to five-year periods in future by evaluating different ITS measures combined with traffic organisation scheme changes.

Моделирование тенденций развития спроса на пассажирские перевозки в дальнем сообщении с учетом особенностей его формирования по регионам Российской Федерации

Forecast of transport mobility of population is an important landmark in the development of passenger transport of JSC "Russian Railways". Business processes of transport planning, justification the traffic volume and train composition schemes, the definition of the operating fleet of cars and infrastructure needs are based on the data on projected traffic volume and the dynamics of their changes. The article describes the results of research work on modeling and forecasting passenger flow and the choice with reference calculation an optimal model having the smallest prediction error. Taking into account that the public demand for transport services depends on many conditions, a list of factors was justified and the most affecting ones were selected. The stages of the modeling process by extrapolating trends and multivariate analysis are presented, reflecting the connection of passenger flows with the economic, demographic and regional characteristics. The accuracy of prediction was made together with conclusions about the performance of the proposed models. The correctness of the developed mathematical apparatus for the forecast of passenger flows is confirmed by supervisory calculations. They are based on actual data on passenger railway transport and assessment of share participation of aviation and road transport in the development of demand.

A Traffic Transmission Scheme for Smart Grid Communication

A Traffic Transmission Scheme for Smart Grid Communication

An inexact fuzzy bi-level programming model for energy–traffic system planning under uncertainty: a case study of Urumqi city, China

ABSTRACTIn this study, an inexact fuzzy bi-level programming model was developed for regional energy and traffic system management under uncertainty in Urumqi city, China. The energy system and traffic system are important subsystems of regional areas such as cities. The coordinated management of regional subsystems is a difficult problem for regional management. A bi-level programming model is an appropriate and simple method to describe the coordinated management of regional subsystems. The energy and traffic structure adjustment, clean power generation and pollutant emission–reduction targets are designed to support the construction of an environmentally sustainable city in China. Methods of interval parameter programming and bi-level programming were incorporated into the developed model to tackle uncertainties and reflect the features in the system. The environmental impacts of energy and traffic activities and policies were analysed. The results are valuable for supporting the management or justification of the existing energy and traffic policies and schemes under uncertainty.

A Cross-Layer Quality-Oriented Scheme for Energy-Efficient Multimedia Delivery in Wireless Networks

Limited battery life has become a critical issue, particularly when mobile devices run multimedia applications, for which users have high quality expectations. In this paper, we propose a cross-layer quality-oriented energy-efficient multimedia delivery scheme (Q-PASTE), which balances the need for the following: increased energy efficiency/battery lifetime and high user quality of experience. The contribution of this work is twofold. First, the Packet/ApplicaTion manager (PAT) is employed as a novel traffic shaping scheme at the application layer of both the gateway and the client host. At the service gateway, PAT first utilizes a fast start approach to support smooth multimedia playback and then shapes traffic from the server into bursts to reduce the wireless transceivers duty cycle for energy efficiency. At the client side, PAT performs traffic monitoring and provides the medium access control (MAC) layer with session-specific traffic-related information. Second, a MAC-located Slow sTart Exponential and Linear Algorithm (STELA) is proposed, which adjusts the sleep/wakeup schedule of the wireless network interface card (WNIC) to increase energy efficiency. An additional parameter-tuning procedure working with the information provided by PAT ensures that data arrive at the client without serious delays. It is demonstrated both analytically and via simulations that the proposed scheme improves energy efficiency significantly, in comparison with other solutions, while maintaining high quality levels.

항공기내 무선 네트워크에서 백홀 트래픽 감소 기법

항공기내 무선 네트워크에서 백홀 트래픽 감소 기법