Abstract

Civil aviation air traffic undergoes many random disturbances. Air traffic controllers watch the real traffic and ensure that it is free from collision hazards in the whole airspace — the ATC sector — under their control. The ATFM service takes care that the flow capacity in each sector, called capacity of the air traffic sector, is not exceeded. In the paper an original method of model estimation of the capacity of the designed ATC sectors is described. In this method an experimentally established statistical relationship between the random variables of control load and the air traffic density is used. The capacity of a sector was found from the joint probability distribution of such a two-dimensional random variable model determined as a quanti le of adequate order. This method was verified in practice by determining the capacity of the designed new ATC sectors in FIR Warsaw. Document type: Book

Abstract

Aiming to successfully meet the requirements of a large output torque and a wide range of flux weakening speed expansion in permanent magnet synchronous motors (PMSM) for electric vehicles, a novel surface insert permanent magnet synchronous motor (SIPMSM) is developed. The method of notching auxiliary slots between the magnetic poles in the rotor and unequal thickness magnetic poles is proposed to improve the performance of the motor. By analyzing the magnetic circuit characteristics of the novel SIPMSM, the notching auxiliary slots between the adjacent magnetic poles can affect the q-axis inductance, and the shape of magnetic pole effects the d-axis inductance of the motor. The combined action of the two factors not only weakens the cogging torque, but also improves the flux weakening capability of the motor. In this paper, the response surface methodology (RSM) is used to establish a mathematical model of the relationship between the structural parameters of the motor and the optimization objectives, and the optimal design of the motor is completed by solving the mathematical model. Experimental validation has been conducted to show the correctness and effectiveness of the proposed SIPMSM. Document type: Article

Abstract

Electric vehicles (EVs) have been widely used in urban cold chain logistic distribution and transportation of fresh products. In this paper, an electric vehicle routing problem (EVRP) model under time-varying traffic conditions is designed for planning the itinerary for fresh products in the urban cold chain. The object of the EVRP model is to minimize the total cost of logistic distribution that includes economic cost and fresh value loss cost. To reflect the real situation, the EVRP model considers several influencing factors, including time-varying road network traffic, road type, client’s time-window requirement, freshness of fresh products, and en route queuing for charging. Furthermore, to address the EVRP, an improved adaptive ant colony algorithm is designed. Simulation test results show that the proposed method can allow EVs to effectively avoid traffic congestion during the distribution process, reduce the total distribution cost, and improve the performance of the cold chain logistic distribution process for fresh products. Document type: Article

Abstract

With the constantly increasing pressure of the competitive environment, supply chain (SC) decision makers are forced to consider several aspects of business climate. More specifically, they should take into account the endogenous features (e.g., available means of transportation, and the variety of products) and exogenous criteria (e.g., the environmental uncertainty, and transportation system conditions). In this paper, a mixed integer nonlinear programming (MINLP) model for dynamic design of a supply chain network is proposed. In this model, multiple products and multiple transportation modes, the time value of money, traffic congestion, and both supply-side and demand-side uncertainties are considered. Due to the complexity of such models, conventional solution methods are not applicable; therefore, two hybrid Electromagnetism-Like Algorithms (EMA) are designed and discussed for tackling the problem. The numerical results show the applicability of the proposed model and the capabilities of the solution approaches to the MINLP problem. Document type: Article

Abstract

With the continuous urban scale expansion, traffic networks have become extremely complex. Finding an optimal route in the shortest time has become a difficult and important issue in traffic engineering study. In this study, a novel computing model, namely, probe machine, is used to solve this problem. Similar to previous studies, urban transport networks can be abstracted into maps, in which points representing places of origin, destinations, and other buildings constitute the data library and edges representing the road make up the probe library. The true solution can be obtained after one probe operation on the computing platform. And by comparing the solving process with Dijkstra’s and Floyd’s algorithms, the computing efficiency of the probe machine is clearly superior, although all three methods can solve the shortest path problem and obtain the same solution. Document type: Article

Abstract

Public transit priority is very important for relieving traffic congestion. The connotation of dynamic public transit priority and dynamic stochastic park and ride is presented. Based on the point that the travel cost of public transit is not higher than the travel cost of car, how to determine the level of dynamic public transit priority is discussed. The traffic organization method of dynamic public transit priority is introduced. For dynamic stochastic park and ride, layout principle, scale, and charging standard are discussed. Traveler acceptability is high through the analysis of questionnaire survey. Dynamic public transit priority with dynamic stochastic park and ride has application feasibility. Document type: Article

Abstract

"jats:p"In this paper, we consider a kinetic description of follow-the-leader traffic models, which we use to study the effect of vehicle-wise driver-assist control strategies at various scales, from that of the local traffic up to that of the macroscopic stream of vehicles. We provide theoretical evidence of the fact that some typical control strategies, such as the alignment of the speeds and the optimisation of the time headways, impact on the local traffic features (for instance, the speed and headway dispersion responsible for local traffic instabilities) but have virtually no effect on the observable macroscopic traffic trends (for instance, the flux/throughput of vehicles). This unobvious conclusion, which is in very nice agreement with recent field studies on autonomous vehicles, suggests that the kinetic approach may be a valid tool for an organic multiscale investigation and possibly the design of driver-assist algorithms. Document type: Article

Abstract

The construction of shield tunnels inevitably causes displacement of the surrounding soil and additional stress and deformation of the buried pipeline. An energy solution for predicting the deformation of buried pipelines caused by tunneling is proposed in this study. First, based on the uniform ground movement model, the interval of the free displacement field of soil around the pipeline induced by tunneling is calculated. Then, we use the Pasternak model to establish the total potential energy equation of the tunnel-soil-pipeline interaction. The final settlement interval of the pipeline is obtained by solving the numerical calculation program with MATLAB. The calculation results of the energy solution are compared with the results of the centrifugal test and the reported theoretical solutions of Winkler and Pasternak, and then the applicability of the solution for predicting the pipeline response under different geotechnical conditions is verified. Combined with an engineering case, the energy method calculation results, numerical simulation results, and measured results are compared to obtain the most unfavorable position of the pipeline caused by tunneling. At the end of this study, the application steps of the proposed method in actual construction are summarized. These steps are used to predict pipeline response in order to take protective measures. Document type: Article

Abstract

Solutions to the routing strategic conflict between noncooperative P2P overlay and ISP underlay go separate ways: hyperselfishness and cooperation. Unpredictable (possibly adverse) impact of the hyperselfish topology awareness, which is adopted in both overlay routing and traffic engineering, has not been sufficiently studied in the literature. Topology-related information exchange in a cooperatively efficient way should be highlighted to alleviate the cross-layer conflict. In this paper, we first illustrate the hyperselfish weakness with two dynamic noncooperative game models in which hyperselfish overlay or underlay has to accept a suboptimal profit. Then we build a synergistic cost-saving (SC) game model to reduce the negative effects of noncooperation. In the SC model, through information exchange, that is, the classified path-delay metrics for P2P overlay and peer locations for underlay, P2P overlay selects proximity as well as saving traffic transit cost for underlay, and ISP underlay adjusts routing to optimize network cost as well as indicating short delay paths for P2P. Simulations based on the real and generated topologies validate cost improvement by SC model and find a proper remote threshold value to limit P2P traffic from remote area, cross-AS, or cross-ISP. Document type: Article

Abstract

Growth in environmental sustainability has prompted the logistics industry to seek sustainable development, and carbon tax policies are considered an effective approach to reducing carbon emissions. This study investigates the optimization of sustainable transportation and inventory under a carbon tax policy and explores effective methods for coordinating the interests of governments and enterprises. The results can provide insights into sustainable logistics for decision-making by enterprises and policy-making by governments. We first examine a Stackelberg game model and design an iterative solution to optimize sustainable transportation and inventory under the carbon tax policy. We then establish a three-stage dynamic game model to optimize the wholesale price, carbon tax rate, and proportion of sustainable investment shared by the government. Furthermore, we perform a simulation to identify the optimal solution of the three-stage game, and we compare the simulation results with a numerical example. The results indicate that a carbon tax policy can improve social welfare and the sustainability of transportation and inventory but could hinder corporate profits. An appropriate sustainable investment-sharing strategy could compensate for the shortcomings of the carbon tax policy and result in positive outcomes for governments and enterprises. Document type: Article