Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data

Accurately modeling traffic speeds is a fundamental part of efficient intelligent transportation systems. Nowadays, with the widespread deployment of GPS-enabled devices, it has become possible to crowdsource the collection of speed information to road users (e.g. through mobile applications or dedicated in-vehicle devices). Despite its rather wide spatial coverage, crowdsourced speed data also brings very important challenges, such as the highly variable measurement noise in the data due to a variety of driving behaviors and sample sizes. When not properly accounted for, this noise can severely compromise any application that relies on accurate traffic data. In this article, we propose the use of heteroscedastic Gaussian processes (HGP) to model the time-varying uncertainty in large-scale crowdsourced traffic data. Furthermore, we develop a HGP conditioned on sample size and traffic regime (SSRC-HGP), which makes use of sample size information (probe vehicles per minute) as well as previous observed speeds, in order to more accurately model the uncertainty in observed speeds. Using 6 months of crowdsourced traffic data from Copenhagen, we empirically show that the proposed heteroscedastic models produce significantly better predictive distributions when compared to current state-of-the-art methods for both speed imputation and short-term forecasting tasks.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.     

柴油发动机掺烧生物柴油的经济性研究

为了更好地评价柴油机燃用生物柴油的经济性,分析了生物柴油和0#石化柴油的理化性质,分别对生物柴油的体积分数为0.2,0.5,1的B20、B50、B100 3种燃料和0#柴油在495Q3柴油机上进行了试验。试验结果显示燃用3种燃料的燃油消耗率比0#柴油在中小负荷时平均增加5.30%,9.65%,19.04%,大负荷时平均增加2.86%,4.75%,9.64%;能量等值折合油耗率在中小负荷时平均增加2.65%,2.63%,5.74%,大负荷时平均降低0.26%,1.97%,4.80%。     

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飞机多机种出动架次率是衡量飞机作战效能的重要指标,本文对空军场站军用飞机多机种（型）出动架次率进行了研究。通过对飞机出动回收过程的描述,基于排队理论建立多服务器多服务率的飞机多机种（型）出动回收网络模型,并采用扩展后的平均值分析对飞机出动能力进行了求解。通过解析计算,给出飞机多机种（型）出动架次率曲线,分析架次率与飞机数量之间的关系,并结合平均队长、利用率等系统性能指标,识别出制约飞机多机种（型）出动架次率提高的因素。最后通过蒙特卡洛仿真对构建的回收网络模型的计算结果进行验证。验证结果表明,飞机多机种（型）出动网络模型及其算法适合应用于实践中,并且有助于对空军场站飞机多机种（型）出动能力的研究。     

中国铁路提速后技术进步对产出贡献的测算

选取我国铁路提速后1997~2007年间的相关数据,采用基于科布——道格拉斯生产函数的Solow余值法,将有限分布滞后模型和半参数回归模型引入计算模型,对数据进行拟合,计算得到铁路提速后技术进步、固定资本投入以及人力资本投入对产出的贡献率,并根据计算结果提出促进我国高速铁路建设的相关对策建议.     

一种适用于虚拟惯量优化控制研究的风电场等值建模方法

大型风电场的建模分析是研究风电参与电力系统频率调控的前提。风电场内机组众多且运行方式各异,根据风电机组的整体结构及虚拟惯量控制策略的基本原理,在直驱式风电机组单机详细模型的基础上进行简化,然后按典型风速将风电场内全部机组分为三群,同群机组采用聚合方法得到等值机组,从而形成最终的风电场多机并网等值模型。考虑风速扰动和负荷扰动两种情况,通过Matlab/Simulink软件对比校验所建模型,仿真结果显示了该建模方法的有效性。     

基于参数化船型的阻力优化研究

船型几何模型的参数化表达,是船型多学科设计优化的基础。其作用是为各学科分析和优化提供一个统一的几何模型,并根据各学科分析结果自动修改调整船体型线。文中尝试使用Friendship进行船体完全参数化建模,并使用该软件中的feature编程功能编程实现shipflow型值数据的提取;通过改变一系列重要的船型参数实现变换船型几何模型,以获得满足性能需求的船型。最后利用该软件的优化框架,采用切线搜索法 (Tangent Search, TSearch) 完成1300TEU集装箱船的兴波阻力优化,优化球首和前体船体曲面。结果表明,该参数化方法在改进船型水动力性能方面有很好的效果。     

动力定位系统舵桨组合推力分配研究

针对船舶动力定位系统推力分配中舵桨组合的推力建模及优化分配问题,将舵桨组合的非凸推力区域转化成4个凸区域,采用切换控制理论把非线性最优化问题转换为线性最优化问题。将舵、桨组合起来进行推力建模,以最小推力、舵角变化和推力误差为优化目标,对推进器的推力变化率、舵角变化率、推力误差范围和推力大小作了约束,采用多边形的方法把推力范围约束转化为线性不等式约束,基于总功率与总推力误差在不同推力区域设计了切换逻辑,实现了在不同的推力分配器中的切换。实船试验结果表明舵桨组合推力模型及推力分配策略是切实可行的,满足了推力分配的要求,在配备舵的动力定位船上具有良好的应用前景。     

基于 Petri 网的装备临抢修业务流程建模研究*

为了提高装备临抢修业务工作的科学性和准确性,论文利用Petri网建模的优势,将排队系统运用到装备临抢修业务流程建模研究中,利用库所优先级实现对故障装备按重要程度进行优先修理。论文讨论了将排队系统转化为HTCPN模型的建模规则,这种方法既可以给出简单直观的模型顶层结构,又可以根据实际情况对模型进行细化,并有利于对模型进行分析和仿真。最后利用CPN Tools工具对所建立的模型进行了性能分析,验证了模型的实用性和有效性。     

激光焊接夹层板结构设计程序开发

基于U-I型、U-IV型、V-I型、V-IV型4种夹层板结构形式,利用PCL(Patran Command Language)语言对MSC.Patran进行二次开发,设计开发出折叠式夹层板结构设计程序(FEA-LASCOR)。该程序仅需设计者在用户界面简单操作即能够实现夹层板板格快速建模、屈服强度分析、结果处理等功能。验算分析表明FEALASCOR程序具有与传统数值仿真分析一样的精度,并缩短了繁琐的建模工作,显著提高设计分析效率,为夹层板船体结构设计高效、快捷的分析工具。