c-SPSA: Cluster-wise simultaneous perturbation stochastic approximation algorithm and its application to dynamic origin–destination matrix estimation

The simultaneous perturbation stochastic approximation (SPSA) algorithm has been used in the literature for the solution of the dynamic origin–destination (OD) estimation problem. Its main advantage is that it allows quite general formulations of the problem that can include a wide range of sensor measurements. While SPSA is relatively simple to implement, its performance depends on a set of parameters that need to be properly determined. As a result, especially in cases where the gradient of the objective function changes quickly, SPSA may not be as stable and even diverge. A modification of the SPSA algorithm, referred to as c-SPSA, is proposed which applies the simultaneous perturbation approximation of the gradient within a small number of carefully constructed “homogeneous” clusters one at a time, as opposed to all elements at once. The paper establishes the theoretical properties of the new algorithm with an upper bound for the bias of the gradient estimate and shows that it is lower than the corresponding SPSA bias. It also proposes a systematic approach, based on the k-means algorithm, to identify appropriate clusters. The performance of c-SPSA, with alternative implementation strategies, is evaluated in the context of estimating OD flows in an actual urban network. The results demonstrate the efficiency of the proposed c-SPSA algorithm in finding better OD estimates and achieve faster convergence and more robust performance compared to SPSA with fewer overall number of function evaluations.     

Customer loads of two-wheeled vehicles

Customer usage profiles are the most unknown influences in vehicle design targets and they play an important role in durability analysis. This publication presents a customer load acquisition system for two-wheeled vehicles that utilises the vehicle's onboard signals. A road slope estimator was developed to reveal the unknown slope resistance force with the help of a linear Kalman filter. Furthermore, an automated mass estimator was developed to consider the correct vehicle loading. The mass estimation is performed by an extended Kalman filter. Finally, a model-based wheel force calculation was derived, which is based on the superposition of forces calculated from measured onboard signals. The calculated wheel forces were validated by measurements with wheel–load transducers through the comparison of rainflow matrices. The calculated wheel forces correspond with the measured wheel forces in terms of both quality and quantity. The proposed methods can be used to gather field data for improved vehicle design loads.     

Road classification for two-wheeled vehicles

This publication presents a three-part road classification system that utilises the vehicle's onboard signals of two-wheeled vehicles. First, a curve estimator was developed to identify and classify road curves. In addition, the curve estimator continuously classifies the road curviness. Second, the road slope was evaluated to determine the hilliness of a given road. Third, a modular road profile estimator has been developed to classify the road profile according to ISO 8608, which utilises the vehicle's transfer functions. The road profile estimator continuously classifies the driven road. The proposed methods for the classification of curviness, hilliness, and road roughness have been validated with measurements. The road classification system enables the collection of vehicle-independent field data of two-wheeled vehicles. The road properties are part of the customer usage profiles which are essential to define vehicle design targets.     

沉桩挤土效应分析及克服挤土效应的措施

该文针对某水厂清水池扩建沉桩时,对相邻构筑物影响进行沉桩挤土效应的分析,提出克服挤土效应的措施,以确保相邻构筑物的安全运行。     

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交通信息集成能够综合分析和利用各种交通信息系统所产生和采集的数据,从而实现对城市交通的综合管理和统一调度。但由于交通信息数据量大且有较强的实时性,并且不同的交通信息对传输性能的要求也不尽相同,因此交通信息传输的QoS要求尤为重要。基于统计分析对交通信息集成的优化是在利用消息总线实现对数据集成,对实时交通信息的传输延时和信息之间的传输相干性进行统计分析,来获取交通信息传输的定量特性,为交通信息传输过程中的消息传输通道、缓冲队列和时间限制等参数设置提供依据,从而优化交通信息的集成,有助于提高实时交通信息的响应时间和处理效率。     

绕越干线公路网规划方案适应性评价体系研究

根据适应性的内涵,提出了绕越干线公路网适应性的目标,以此为基础构建出绕越干线公路网规划方案适应性评价指标体系,并运用多层次-灰色关联度评价方法进行规划方案综合评价,最终建立了绕越干线公路网适应性评价体系。     

基于大规模定制的新产品成本估算研究

成本是企业为获得所需的各项资源而付出的代价。在基于对大规模定制产品成本分析研究现状的基础上,针对产品不同的估价精度要求,提出综合运用模型估算法和详细计算法两种成本计算模型相结合的成本估算方法。该方法能使企业有效地控制和削减成本,最终达到提高产品市场竞争力和节约资源的目的。     

不确定条件下开行固定车组重量分组列车适用条件研究

分组列车与单组列车是我国车流组织的两种形式,二者互有利弊,对其开行适用条件研究具有理论价值和现实意义。根据固定车组重量分组列车集结的动态特性和车组到达的不确定性,将车组的车数和间隔时间都视为随机变量,应用随机过程理论,解析其在编成站和途中换挂站的集结耗费相对于单组列车的节省和额外消耗,以一昼夜所产生的总净节省的数学期望作为其综合效益的度量,给出分组列车合理开行的判别式和更易判定的必要条件。针对模型的特点,应用离散事件系统仿真方法进行模拟。仿真算例表明:判定条件的吻合率为97.36%,必要条件的失真率为4.52%;其综合效益受到车组平均车数和平均间隔时间参数影响且前者灵敏程度更高;适用于车流量较小且车流到达强度之比接近固定车组重量之比情形。     

高速公路建设管(杆)线拆迁费用估算探究

导致工程超概算的原因很多,如宏观经济政策的变化、不可抗力的影响、工程的变更以及工程可行性研究费用的估算不足等。随着城市化进程的加快,绕城和延伸线等高速公路规划向城市靠近,高速公路建设所需拆迁管(杆)线的数量及拆迁难度随之增大。其拆迁费用的估算,值得探究。该文介绍的有关经验可供类似工程参考。     

初始模型的不确定性对梁式结构静力损伤识别的影响

结合初始模型和结构损伤的概率定义,给出了一个具有统计意义的梁式结构静力损伤识别方法.在此基础上,重点研究了初始模型的不确定性对损伤识别的影响.经数值分析,发现当初始模型的不确定程度低于或基本相当于损伤程度时,本文的方法依然具有较好的损伤识别效果.而当初始模型的不确定程度超过结构损伤程度时,已无法识别出结构损伤.因此,为了获得较好的损伤识别结果,必须保证初始模型具有足够的精度.