运输船舶在波浪中失速的近似估算

如何准确、快速、简便地估算船舶在波浪中的失速,已成为船舶研究、设计人员及航运界有关人员共同关心的一个重要课题。文中给出了近似估算运输船舶在波浪中失速的2个方法。对处于初步设计阶段且尚未做过静水快速性能模型试验的运输船舶,可直接应用第2个方法。该方法提出的近似估算公式应用方便,也不用编程便可直接人工计算,且与模型试验结果相当吻合。     

国有收费公路企业全要素生产率测度及提升路径研究

近年来,收费公路行业绩效问题愈发凸显,但针对政府还贷公路运营载体的国有收费公路企业的研究却相对匮乏.为此,以2000～2019年21家国有收费公路企业的面板数据为研究样本,基于半参数估计法及Sequential-Malmquist指数法对国有收费公路企业全要素生产率(TFP)及其变动的内在结构性因素进行实证测度,得到如...     

Quasi-dynamic estimation of o–d flows from traffic counts: Formulation,statistical validation and performance analysis on real data

The paper proposes a “quasi-dynamic” framework for estimation of origin–destination (o–d) flow from traffic counts, under the assumption that o–d shares are constant across a reference period, whilst total flows leaving each origin vary for each sub-period within the reference period. The advantage of this approach over conventional within-day dynamic estimators is that of reducing drastically the number of unknowns given the same set of observed time-varying traffic counts. Obviously, the gain in accuracy depends on how realistic is the underlying assumption that total demand levels vary more rapidly over time than o–d shares. Firstly, the paper proposes a theoretical specification of the quasi-dynamic estimator. Subsequently, it proposes empirical and statistical tests to check the quasi-dynamic assumption and then compares the performances of the quasi-dynamic estimator of o–d flows with both classical off-line simultaneous dynamic estimators and on-line recursive Kalman filter-based estimators. Experiments are carried out on the real test site of A4–A23 motorways in North-Eastern Italy. Results confirm the acceptability of the assumption of quasi-dynamic o–d flows, even under the hypothesis of constant distribution shares for the whole day and show that the quasi-dynamic estimator outperforms significantly the simultaneous estimator. Data also suggest that using the quasi-dynamic estimates instead of the simultaneous estimates as historical o–d flows improves significantly the performances of the Kalman filter, which strongly depends of the quality of the seed o–d flows. In addition, it is shown that the aggregation of quasi-dynamic o–d estimates across subsequent time slices represents also the most effective way to obtain o–d estimates for larger time horizons (e.g. hourly estimates). Finally, a validation based on an hold-out sample of link flows (i.e. counts not used as inputs in the o–d estimation/updating process) revealed the quasi-dynamic estimator to be overall more robust and effective with respect to the other tested estimators.     

浅谈公路工程估算编制的新规则

新的《公路工程基本建设项目投资估算编制办法》和《公路工程估算指标》自2012年1月1日正式实施。取代1996编办和指标,针对估算编制的新规则,分析总结新旧差异,为以后估算编制工作提供指导。     

TransCAD平台下OD矩阵反推结果对比研究

在介绍基于T ransCAD软件平台下OD矩阵反推方法基础上,设计不同的OD矩阵反推方案。通过方案反推结果之间的对比,研究基于路段交通量反推OD矩阵的结果精度与交通分配方法、路段拥挤程度、种子OD矩阵以及路段交通量调查点覆盖范围之间的关系。     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design,demonstration and validation

Estimation/updating of Origin–Destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in on-line contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks – except from closed highway systems – thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under “standardized” conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources.     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.     

Observer-based clutch disengagement control during gear shift process of automated manual transmission

A clutch disengagement strategy is proposed for the shift control of automated manual transmissions. The control strategy is based on a drive shaft torque observer. With the estimated drive shaft torque, the clutch can be disengaged as fast as possible without large driveline oscillations, which contributes to the reduction of total shift time and shift shock. The proposed control strategy is tested on a complete powertrain simulation model. It is verified that the system is robust to the variations of driving conditions, such as vehicle mass and road grade. It is also demonstrated that the revised system with switched gain can provide satisfactory performance even under large estimation error of the engine torque.