Performability evaluation of the ERTMS/ETCS – Level 3

Level 3 of the ERTMS/ETCS improves the capacity of railways by replacing fixed-block signalling, which prevents a train to enter a block occupied by another train, with moving block signalling, which allows a train to proceed as long as it receives radio messages ensuring that the track ahead is clear of other trains. If messages are lost, a train must stop for safety reasons within a given deadline, even though the track ahead is clear, making the availability of the communication link crucial for successful operation.We combine analytic evaluation of failures due to burst noise and connection losses with numerical solution of a non-Markovian model representing also failures due to handovers between radio stations. In so doing, we show that handovers experienced by a pair of chasing trains periodically affect the availability of the radio link, making behavior of the overall communication system recurrent over the hyper-period of periodic message releases and periodic arrivals at cell borders. As a notable aspect, non-Markovian transient analysis within two hyper-periods is sufficient to derive an upper bound on the first-passage time distribution to an emergency brake, permitting to achieve a trade-off between railway throughput and stop probability. A sensitivity analysis is performed with respect to train speed and headway distance, permitting to gain insight into the consequences of system-level design choices.     

基于MATLAB的汽车动力性GUI界面开发

以MATLAB软件的GUI为设计工具,建立了汽车动力性数学模型,通过最小二乘法和插值法绘制了发动机外特性曲线、汽车驱动力与行驶阻力平衡图、加速度倒数曲线、爬坡度曲线,以及加速时间曲线、最高车速变化曲线、加速度变化曲线和爬坡度变化曲线,直观、清晰地分析了汽车的动力性和各参数对动力性灵敏度的影响,使设计者清楚地了解汽车的动力性好坏以及各参数的影响,进而对设计作出改进。     

Highway alignment optimization through feasible gates

An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model's computation time and solution quality. Such improvements are demonstrated with two test examples from a real road project.     

Multi-scale robustness model for highway networks under flood events

Transportation system infrastructure often experiences severe flood-related disruptions such as overtopping, erosion, and scour. The ensuing damages can result in enormous direct and indirect economic losses to the traffic network and consequently the individuals through conditions like inaccessibility to commuters and reduction in traffic safety. Many studies have claimed that a robust transportation system could significantly prevent such consequences from natural hazards such as floods, highlighting the importance of robustness measures that could be used by decision-makers to properly manage flooded transportation system. Most available measures related to network robustness assessment are qualitative, and while some recent studies have focused on such evaluation using quantitative assessment approaches related to environmental or social-economic operations, they lack the holistic view towards robustness under flood events. This study develops a composite multi-scale transportation-system robustness model considering flood hazards by synthesizing geographical damage recognition, topological functionality analysis, network operation evaluation, and traffic-user loss estimation. This integrated model has been applied in a real-world highway network, mainly revealing that a given intensive flood occurrence at different locations may result in a variety of after-flood disruptions in the transportation network. To assist the asset owners with developing more reasonable prevention and recovery plans, the developed multi-scale robustness index presents both visible multi-denominational flood consequences and an overall post-event transportation-system robustness indicator.     

Robust control of traffic networks under uncertain conditions

Uncertainty of traffic network operations has been a subject of lively debate in the last decade. However, little effort has been put in developing control frameworks that are not only aimed at improving the average performance of the system, but also at improving the system robustness and reliability. In fact, it can be argued that most of the current control approaches are only aimed at improving the efficiency, which can even be counterproductive from a robustness point of view. The main contributions of this article is the proposition of a new control framework based on the notion of controlled Markov processes, which explicitly takes into account the uncertainty in predicted traffic conditions and system performance. Furthermore, in contrast to traditional optimal control approaches, the objective function can include general statistic of the random system performance, such as the mean, standard deviation or 95‐percentile. The contribution aims to make clear how different performance function specifications yield different control strategies. This is shown for a relatively simple case study.     

差分GPS的对流层伪距残差的计算机模拟

简单回顾了对流层中GPS信号传播延迟的原理。介绍了2种常见的校正模型,Hopfield模型和Black模型。定义了差分GPS(DGPS)的对流层伪距残差的概念,并建立了数学模型。用计算机对DGPS的对流层伪距残差进行仿真。仿真结果表明用户和基准台之间距离增大和低卫星仰角都将使伪距残差增大,气象因素和高程对伪距残差也有影响。     

Accounting for stochastic variables in discrete choice models

The estimation of discrete choice models requires measuring the attributes describing the alternatives within each individual’s choice set. Even though some attributes are intrinsically stochastic (e.g. travel times) or are subject to non-negligible measurement errors (e.g. waiting times), they are usually assumed fixed and deterministic. Indeed, even an accurate measurement can be biased as it might differ from the original (experienced) value perceived by the individual.Experimental evidence suggests that discrepancies between the values measured by the modeller and experienced by the individuals can lead to incorrect parameter estimates. On the other hand, there is an important trade-off between data quality and collection costs. This paper explores the inclusion of stochastic variables in discrete choice models through an econometric analysis that allows identifying the most suitable specifications. Various model specifications were experimentally tested using synthetic data; comparisons included tests for unbiased parameter estimation and computation of marginal rates of substitution. Model specifications were also tested using a real case databank featuring two travel time measurements, associated with different levels of accuracy.Results show that in most cases an error components model can effectively deal with stochastic variables. A random coefficients model can only effectively deal with stochastic variables when their randomness is directly proportional to the value of the attribute. Another interesting result is the presence of confounding effects that are very difficult, if not impossible, to isolate when more flexible models are used to capture stochastic variations. Due the presence of confounding effects when estimating flexible models, the estimated parameters should be carefully analysed to avoid misinterpretations. Also, as in previous misspecification tests reported in the literature, the Multinomial Logit model proves to be quite robust for estimating marginal rates of substitution, especially when models are estimated with large samples.     

An Epsilon Bargaining Game-Theoretic Formulation Between Carrier and Container Terminal Operators for Servicing Vessels During Unloading Operations

Due to globalization trends and the increasing competition between ports, the maritime policy for container shipments has witnessed a change in operations that resulted in less reliance on direct freight flows and higher transshipment operations. Motivated to investigate a soft intelligent decision-making approach using game theory in the context of servicing vessels during unloading operations in transshipment, we propose an epsilon bargaining approach between the carrier and the container terminal operator (CTO). The objective of the game is to maximize the carrier service level while minimizing operation costs for the CTO. The players' utilities, which depend on the service level and the fees for the carrier, as well as the revenues generated and the cost incurred for the CTO, are uniquely formulated and evaluated in a bargaining scenario using an ordinal ranking approach. The negotiation process is further improved between the two players based on our proposed Epsilon Bargaining Equilibrium, which to the best of our knowledge has not been used in maritime transportation problems. Results from a risk aversion case illustrate the value of the soft computing mathematical model that we formulated and motivate follow-up research.     

基于风场模拟的接触网b值动态响应分析

接触网线索受风振动会造成b值变化,为了将风荷载引起的变化量剔除,对随机风场作用下的接触网进行仿真研究。利用ANSYS软件建立全补偿简单链形悬挂接触网模型;采用谐波叠加法模拟得到随机风场;分析b值风致变化的机理,仿真完成了接触网模型在不同随机风荷载作用下的动态响应分析。研究结果表明:接触网b值风致变化是线索受风偏移导致的结果,横向偏移起主要作用;脉动风场作用下接触网各跨会随机产生不同大小的补偿位移,随着风速提升补偿位移振幅相应变大且变化率呈增大趋势;对于半个锚段12跨接触网,当风速达到41m/s时,补偿位移振幅为60.61 mm,接近棘轮补偿装置断线b值变化量,说明识别断线事故时应考虑风振的影响。     

Stochastic Monte Carlo simulations of the pantograph–catenary dynamic interaction to allow for uncertainties introduced during catenary installation

The simulation of the pantograph–catenary dynamic interaction is at present mainly based on deterministic approaches. However, any errors made during the catenary stringing process are sources of variability that can affect the dynamic performance of the system. In this paper, we analyse the influence of dropper length, dropper spacing and support height errors on the current collection quality by applying a classic Monte Carlo method to obtain the probability density functions of several output quantities. The effects of installation errors are also studied for a range of train speeds. Finally, the pre-sag that, on average, produces the best behaviour of the system is identified, allowing for the uncertainty in the catenary installation. The results obtained show the convenience to consider variability in pantograph–catenary dynamic simulations.