列车动力响应的平稳性和各态历经性分析

研究列车动力响应的平稳性和各态历经性对寻求列车动力响应随机过程的统计规律具有重要意义。基于多体动力学理论,采用多体动力学分析软件Simpack建立国内某高速列车动车车辆的多体动力学模型。采用三角级数法模拟得到的轨道不平顺作为随机输入激励计算得到列车以不同速度行驶不同距离的动力响应时程样本序列。进一步运用平稳性检验方法中的逆序数检验法和单位根检验法对列车动力响应随机过程的平稳性进行检验。运用Monte-Carlo方法并结合随机过程的相关理论,计算1 500个在随机轨道不平顺激励下列车以200 km/h速度行驶1 km工况的动力响应时程样本序列的集合均值和集合相关函数,时间均值和时间相关函数,对列车动力响应的平稳性和各态历经性进行了证明。研究结果表明,列车以200 km/h的速度行驶1 km工况的动力响应可近似为具有各态历经性的平稳随机过程,即可采用一个时程响应样本来反映列车动力响应总体的统计规律。随着列车动力响应样本个数的增加,列车动力响应的平稳性和各态历经性都将更加稳定。     

环境可持续集装箱班轮运输管理研究综述

集装箱班轮运输业如何在追求成本经济性和服务可靠性的同时做好环境可持续性，对航 运企业、港口运营商以及政府组织都提出了新的挑战。围绕集装箱班轮运输在环境层面实现可 持续发展的目标，本文分别从战略、战术和运营等3个层面就措施、技术和规章制度等所做的研究 进行文献综述、分析发展趋势。战略层面，从市场减排机制和政策的制定、绿色政策、技术及措施 评估和企业竞争与合作等3个方面综述；战术层面，从控制油耗或碳排放的班轮运营优化、预调度 式的绿色班轮运营优化和污染排放控制区的设立对班轮运营优化的影响等3个方面综述；在运营 层面，从控制排放的集装箱调运和反应式的绿色班轮运营优化等两方面综述。按照决策水平、时 间脉络和研究主题分析后发现，该领域的研究趋势变化与行业及政府的环境政策紧密关联。其 次，从决策水平和问题类别来看，针对战术层决策的研究远多于针对战略和执行两层。第三，从 决策主体来看，大部分研究以航运公司作为单独的决策主体。本文建议：继续在优化班轮运输中 考虑多目标，将多目标优化作为决策手段可兼顾经济、环境以及社会责任，有利于航运可持续发 展；结合行业实践提炼科学问题，国际航运、尤其班轮运输极易受到政策导向、世界经济环境的影 响；从供应链角度研究集装箱班轮运输的可持续发展问题；为配合在运营层面的努力，还要研究 通过技术途径或手段推动班轮运输业可持续发展；借鉴其他运输行业较为成熟的绿色环保发展 思路促进班轮运输环境可持续发展。     

基于滚动时域优化的共享自动驾驶汽车动态调度方法

共享自动驾驶汽车被视为未来城市交通系统的重要组成部分。本文考虑随机订单需求研究共享自动驾驶汽车的动态调度优化方法。通过建立车辆调度时空网络，分别针对订单分配与空车移位生成车辆运行时间弧，提出车辆调度问题的刻画方法。基于马尔科夫决策框架，以时空节点流量为状态，以时空弧流量为决策变量，建立最大化系统净收益的车辆动态调度优化模型。 采取滚动时域优化思想，建立含前视时间窗的随机规划模型，并利用CPLEX优化引擎，滚动求解车辆动态调度决策结果。Sioux Falls网络算例结果表明，滚动时域优化方法可保证车辆动态调度决策效果，提升系统运营效率。在计算时间限制下，滚动时域方法应优先采用长时间窗中等规模 样本。在最大化系统净收益的同时进一步最小化乘客等待时间，可有效提升车辆动态调度决策效果。     

Vehicle response-based track geometry assessment using multi-body simulation

The assessment of the geometry of railway tracks is an indispensable requirement for safe rail traffic. Defects which represent a risk for the safety of the train have to be identified and the necessary measures taken. According to current standards, amplitude thresholds are applied to the track geometry parameters measured by recording cars. This geometry-based assessment has proved its value but suffers from the low correlation between the geometry parameters and the vehicle reactions. Experience shows that some defects leading to critical vehicle reactions are underestimated by this approach. The use of vehicle responses in the track geometry assessment process allows identifying critical defects and improving the maintenance operations. This work presents a vehicle response-based assessment method using multi-body simulation. The choice of the relevant operation conditions and the estimation of the simulation uncertainty are outlined. The defects are identified from exceedances of track geometry and vehicle response parameters. They are then classified using clustering methods and the correlation with vehicle response is analysed. The use of vehicle responses allows the detection of critical defects which are not identified from geometry parameters.     

A stochastic analysis of highway capacity: Empirical evidence and implications

This paper presents a stochastic characterization of highway capacity and explores its implications on ramp metering control at the corridor level. The stochastic variation of highway capacity is captured through a Space–Time Autoregressive Integrated Moving Average (STARIMA) model. It is identified following a Seasonal STARIMA model (0, 0, 2₃) × (0, 1, 0)₂, which indicates that the capacities of adjacent locations are spatially–temporally correlated. Hourly capacity patterns further verify the stochastic nature of highway capacity. The goal of this paper is to study (1) how to take advantage of the extra information, such as capacity variation, and (2) what benefits can be gained from stochastic capacity modeling. The implication of stochastic capacity is investigated through a ramp metering case study. A mean–standard deviation formulation of capacity is proposed to achieve the trade-off between traffic operation efficiency and robustness. Following that, a modified stochastic capacity-constraint ZONE ramp metering scheme embedded cell transmission model algorithm is introduced. The numerical experiment suggests that considering capacity variation information would alleviate the spillback effect and improve throughput. Monte Carlo simulation further supports this argument. This study helps verify and characterize the stochastic nature of capacity, validates the benefits of using capacity variation information, and thus enhances the necessity of implementing stochastic capacity in traffic operation.     

Signal coordination model for local arterial with heavy bus flows

Conventional Transit Signal Priority (TSP) controls often reach the limitation for arterials accommodating heavy bus flows since the priority function can significantly increase delay at minor streets. Under such conditions, a proper signal progression plan that accounts for the benefits of buses may offer the potential to improve the reliability of bus operations and increase the bus ridership. This study proposes a bus-based progression model to reduce the delay of buses on local arterials. Given the cycle length and green splits at each intersection, the bus-based progression model, grounded on the same notion as conventional signal progression methods, considers the operational characteristics of transit vehicles, such as the impact of bus dwell time and the capacity constraints at bus stops. Also, to deal with the stochastic nature of dwell time, this study introduces additional constraints to maximize the percentage of buses which can stay within the green band after leaving bus stops. Taking an arterial with five intersections and three two-way bus stops as an example, this study applies VISSIM as an unbiased tool for model evaluation. The simulation results demonstrate that the proposed model can significantly reduce bus passenger delays and the average person delays for the entire arterial, compared with the conventional progression models.     

基于序贯代理模型的转子系统频响特性区间分析方法

在转子系统的频率响应分析中,不确定性广泛存在,并且对分析结果有较大的影响。本文提出了一种面向含区间不确定性转子系统频响分析的序贯代理模型方法。基于区间数学以及转子动力学理论,本文首先建立了含区间参数转子系统频响的控制方程。基于传统的静态代理模型提出了面向转子系统区间分析的序贯代理模型方法。该方法首先通过叫少量的样本点构造粗糙代理模型,再提出了两个指标函数进行下一阶段的选点。重复该过程,直到满足收敛条件,最终可以得到转子系统频率响应的精细代理模型,进而得到区间边界。和传统的区间分析方法相比,该方法精度高,适合非线性问题。     

Predicting queue variability to enable analysis of overload risk

ABSTRACT

Predicting the risk of traffic demands and delays exceeding critical limits at road junctions, airports, hospitals, etc., requires knowing how both mean and variance of queue size vary over time. Microscopic simulation can explore variability but is computationally demanding and gives only sample results. A computationally efficient approximation to the mean is used in many modelling tools, but only empirical extensions for variance in particular situations have been available. The paper derives theoretical formulae for time-dependent and equilibrium variance, believed to be novel and to apply generally to queues covered by the Pollaczek–Khinchin mean formula, and offering possible structural insights. These are applied in an extended approximation giving mutually consistent mean and variance estimates with improved accuracy. Tests on oversaturated peak demand cases are compared with Markov probabilistic simulation, demonstrating accuracy (R^2?>?0.99) for typical random, priority-like (M/M/1) and traffic-signal-like (M/D/1) queues. Implications for risk analysis, planning and policy are considered.     

融合D-S理论的锅炉人因贝叶斯网络安全性定量分析

针对船用锅炉人因安全性分析中存在的知识不确定性,采用D-S证据理论对多专家信息进行融合并建立考虑人因的贝叶斯网络,得到节点条件概率的区间表示形式.经加权平均后代入贝叶斯网络计算,与面向对象贝叶斯网络和FTA等方法的对比显示,该方法能够更加有效地融合不同专家信息,也更为符合工程实际.     

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.