ROBUST FILTERS WITH SAMPLED-DATA ESTIMATION COVARANCE CONSTRAINT FOR UNCERTAIN CONTINUOUS-TIME SYSTEMS

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厦深铁路榕江特大桥列车运行稳定性试验研究

厦深铁路榕江特大桥为孔跨布置（110＋2×220＋110）m的钢桁梁柔性拱桥，桥面系为正交异性钢桥面系、有砟轨道，采用剪力法测试货物列车在桥上、路基、钢轨伸缩器3种不同位置的轮轨力，对货物列车运行稳定性指标进行计算分析和评判，验证了该桥梁运营的安全性；分析货物列车运行稳定性指标与速度的关系，揭示了轮对横向力、列车脱轨系数和轮重减载率的最大值随着车速的提高而增大的现象；对相同速度下货物列车通过不同轨道基础的运行稳定性指标进行比较，提出应特别重视钢轨伸缩调节器位置轨道结构的日常管养的建议；结合联调联试测试结果，对比分析货物列车和动车通过各测试工点的稳定性，结果表明动车组运行稳定性优于货物列车；试验也验证了本文设计的轮轨力标定加力架设计合理、使用方便。     

The causal relationship between GDP and domestic air passenger traffic in Brazil

Abstract

This paper examines the causal relationship between economic growth and domestic air passenger transport in Brazil, using Granger's causality test. Total domestic passenger-kilometres are used as a proxy for air transport demand and gross domestic product as a proxy for economic growth. The test spans the period from 1966 to 2006. The results lead to the acceptance of the hypothesis that there is a unidirectional Granger causal relationship from economic growth to domestic air transport demand in Brazil, having a high elasticity in the short term.     

Door-to-door travel times in RP departure time choice models: An approximation method using GPS data

A common way to determine values of travel time and schedule delay is to estimate departure time choice models, using stated preference (SP) or revealed preference (RP) data. The latter are used less frequently, mainly because of the difficulties to collect the data required for the model estimation. One main requirement is knowledge of the (expected) travel times for both chosen and unchosen departure time alternatives. As the availability of such data is limited, most RP-based scheduling models only take into account travel times on trip segments rather than door-to-door travel times, or use very rough measures of door-to-door travel times. We show that ignoring the temporal and spatial variation of travel times, and, in particular, the correlation of travel times across links may lead to biased estimates of the value of time (VOT). To approximate door-to-door travel times for which no complete measurement is possible, we develop a method that relates travel times on links with continuous speed measurements to travel times on links where relatively infrequent GPS-based speed measurements are available. We use geographically weighted regression to estimate the location-specific relation between the speeds on these two types of links, which is then used for travel time prediction at different locations, days, and times of the day. This method is not only useful for the approximation of door-to-door travel times in departure time choice models, but is generally relevant for predicting travel times in situations where continuous speed measurements can be enriched with GPS data.     

Bus running time prediction using a statistical pattern recognition technique

Abstract

Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.     

An improved headway-based holding strategy for bus transit

Abstract

This paper presents an improved headway-based holding strategy integrating bus transit travel and dwelling time prediction. A support vector machine-based (SVM) model is developed to predict the baseline travel and dwell times of buses based on recent data. In order to reduce prediction errors, an adaptive algorithm is used together with real-time bus operational information and estimated baseline times from SVM models. The objective of the improved holding strategy is to minimize the total waiting times of passengers at the current stop and at successive stops. Considering the time-varying features of bus running, a ‘forgetting factor’ is introduced to weight the most recent data and reduce the disturbance from unexpected incidents. Finally, the improved holding strategy proposed in this study is illustrated using the microscopic simulation model Paramics and some conclusions are drawn.     

“高超临界航行”的流体动力设计研究

文章提出了能够实现"高超临界航行"的新船型,并对该新船型进行了流体动力设计研究.通过理论分析及试验研究表明,采用新船型的超高速高超临界海上运输平台具有超高航速、优良的耐波性、极佳的稳定性和良好的经济性.     

基于公交GPS 和IC 卡数据的乘客人均候车时间估算方法研究

候车是公交出行的重要组成部分，而候车时间是决定公交系统吸引力的关键因素，也是评价城市公交服务水平的指标之一. 目前，获取乘客候车时间的主要途径为问卷调查法和视频采集法. 但是这些方法费时费力，仅能实现小范围典型站点的候车时间的调查，无法快速完成线路甚至线网级别的候车时间采集. 为解决上述问题，本文基于北京公交GPS和IC 卡刷卡数据，采用非时齐泊松过程理论构建了乘客到站模型，并给出了一种离散条件下任意时刻的乘客人均候车时间计算方法，该方法能动态准确的获知不同站点、线路和线网乘客的人均候车时间. 基于此方法本文计算了1 d 内北京公交606 路全线的人均候车时间变化情况，计算结果表明，606 路早晚高峰和中午乘客人均候车时间最短大约在200 s 左右，下午乘客的候车时间较长.     

The impact of route guidance,departure time advice and alternative routes on door-to-door travel time reliability: Two data-driven assessment methods

ABSTRACT

Conventional travel time reliability assessment has evolved from road segments to the route level. However, a connection between origin and destination usually consists of multiple routes, thereby providing the option to choose. Having alternatives can compensate for the deterioration of a single route; therefore, this study assesses the reliability and quality of the aggregate of the route set of an origin-destination (OD) pair. This paper proposes two aggregation methods for analyzing the reliability of travel times on the OD level: 1) an adapted Logsum method and 2) a route choice model. The first method analyzes reliability from a network perspective and the second method is based on the reliability as perceived by a traveler choosing his route from the available alternatives. A case study using detailed data on actual travel times illustrates both methods and shows the impact of having variable departure times and the impact of information strategies on travel time reliability.     

Application of the support vector machine and heuristic k-shortest path algorithm to determine the most eco-friendly path with a travel time constraint

This study aims to determine an eco-friendly path that results in minimum CO₂ emissions while satisfying a specified budget for travel time. First, an aggregated CO₂ emission model for light-duty cars is developed in a link-based level using a support vector machine. Second, a heuristic k-shortest path algorithm is proposed to solve the constrained shortest path problem. Finally, the CO₂ emission model and the proposed eco-routing model are validated in a real-world network. Specifically, the benefit of the trade-off between CO₂ emission reduction and the travel time budget is discussed by carrying out sensitivity analysis on a network-wide scale. A greater spare time budget may enable the eco-routing to search for the most eco-friendly path with higher probability. Compared to the original routes selected by travelers, the eco-friendly routes can save an average of 11% of CO₂ emissions for the trip OD pairs with a straight distance between 6 km and 9 km when the travel time budget is set to 10% above the least travel time. The CO₂ emission can also be reduced to some degree for other OD pairs by using eco-routing. Furthermore, the impact of market penetration of eco-routing users is quantified on the potential benefit for the environment and travel-time saving.