基于多层隐类贝叶斯网络的舰船生存能力评估模型研究

生存能力是舰船设计时需要考虑的一个重要性能指标,然而其涉及的因素较多,因素之间的关系错综复杂,不确定信息充斥其间.在系统分析舰船生存能力评估要素的基础上,针对评估过程中的不确定性信息难以量化处理的特点,引入基于贝叶斯网络的多层隐类模型算法对舰船生存能力进行评估,给出了模型评分原理.最后以实例说明了建模方法与评估过程,并结合专家意见分析了模型的优劣,说明该多层隐类模型的算法符合实际情况.     

基于自然驾驶数据的高速公路跟驰模型参数标定

为了研究中国驾驶人在高速公路上的跟驰行为特征,从上海自然驾驶研究试验数据库中提取48位驾驶人在高速公路上的跟驰事件并进行特征分析。利用自动化筛选准则及人工验证方式提取1 548个有效事件,选取后车车速与车头间距为性能指标,其均方根百分比误差之和为目标函数,利用遗传算法对Gazis-Herman-Rothery模型、GIPPS模型、智能驾驶人模型、全速度差模型和Wiedemann模型进行参数标定及效果验证。基于误差、碰撞及后退等异常情况出现次数等比较其表现性。研究结果表明：不同模型对中国驾驶人的适应性不同,智能驾驶人模型具有最小的误差和误差标准差,更加适合仿真中国驾驶人在高速公路上的跟驰行为。研究结果对于开发适合于中国驾驶人与道路环境特征的跟驰模型具有重要价值。     

Is car drivers’ response to congestion charging schemes based on the correct perception of price signals?

This paper deals with the question of whether the capability of car drivers to estimate the cost of a new hypothetical, highly differentiated congestion charge influences their decision to change travel behaviour. The analysis makes use of an integrated choice and latent variable model (ICLV) which merges classic choice models with the structural equation approach (SEM) for latent variables. This hybrid model improves the explanatory power considerably compared with a conventional discrete choice model. The results suggest that charge complexity decreases the resistance in considering behavioural changes. Car drivers tend to avoid a travel option where the price is not known beforehand, a phenomenon known as ambiguity avoidance.     

Evaluating the effects of automated vehicle technology on the capacity of freeway weaving sections

Weaving sections, where a merge and a diverge are in close proximity, are considered as crucial bottlenecks in the highway network. Lane changes happen frequently in such sections, leading to a reduced capacity and the traffic phenomenon known as capacity drop. This paper studies how the emerging automated vehicle technology can improve the operations and increase the capacity of weaving sections. We propose an efficient yet effective multiclass hybrid model that considers two aspects of this technology in scenarios with various penetration rates: (i) the potential to control the desired lane change decisions of automated vehicles, which is represented in a macroscopic manner as the distribution of lane change positions, and (ii) the lower reaction time associated with automated vehicles that can reduce headways and the required gaps for lane changing maneuvers. The proposed model is successfully calibrated and validated with empirical observations from conventional vehicles at a weaving section near the city of Basel, Switzerland. It is able to replicate traffic dynamics in weaving sections including the capacity drop. This model is then applied in a simulation-based optimization framework that searches for the optimal distribution of the desired lane change positions to maximize the capacity of weaving sections. Simulation results show that by optimizing the distribution of the desired lane change positions, the capacity of the studied weaving section can increase up to 15%. The results also indicate that if the reaction time is considered as well, there is an additional combined effect that can further increase the capacity. Overall, the results show the great potential of the automated vehicle technology for increasing the capacity of weaving sections.     

Analysis of peak and non‐peak traffic forecasts using combined models

Accurate and timely traffic forecasting is crucial to effective management of intelligent transportation systems (ITS). To predict travel time index (TTI) data, we select six baseline individual predictors as basic combination components. Applying the one‐step‐ahead out‐of‐sample forecasts, the paper proposes several linear combined forecasting techniques. States of traffic situations are classified into peak and non‐peak periods. Based on detailed data analyses, some practical guidance and comments are given in what situation a combined model is better than an individual model or other types of combined models. Indicating which model is more appropriate in each state, persuasive comparisons demonstrate that the combined procedures can significantly reduce forecast error rates. It reveals that the approaches are practically promising in the field. To the best of our knowledge, it is the first time to systematically investigate these approaches in peak and non‐peak traffic forecasts. The studies can provide a reference for optimal forecasting model selection in each period. Copyright © 2010 John Wiley & Sons, Ltd.     

Dynamic modelling and experimental validation of three wheeled tilting vehicles

The present paper describes the study of the stability in the straight running of a three-wheeled tilting vehicle for urban and sub-urban mobility. The analysis was carried out by developing a multibody model in the Matlab/SimulinkSimMechanics environment. An Adams-Motorcycle model and an equivalent analytical model were developed for the cross-validation and for highlighting the similarities with the lateral dynamics of motorcycles. Field tests were carried out to validate the model and identify some critical parameters, such as the damping on the steering system. The stability analysis demonstrates that the lateral dynamic motions are characterised by vibration modes that are similar to that of a motorcycle. Additionally, it shows that the wobble mode is significantly affected by the castor trail, whereas it is only slightly affected by the dynamics of the front suspension. For the present case study, the frame compliance also has no influence on the weave and wobble.     

Surrogate‐based optimization of cordon toll levels in congested traffic networks

The benefit, in terms of social surplus, from introducing congestion charging schemes in urban networks is depending on the design of the charging scheme. The literature on optimal design of congestion pricing schemes is to a large extent based on static traffic assignment, which is known for its deficiency in correctly predict travel times in networks with severe congestion. Dynamic traffic assignment can better predict travel times in a road network, but are more computational expensive. Thus, previously developed methods for the static case cannot be applied straightforward. Surrogate‐based optimization is commonly used for optimization problems with expensive‐to‐evaluate objective functions. In this paper, we evaluate the performance of a surrogate‐based optimization method, when the number of pricing schemes, which we can afford to evaluate (because of the computational time), are limited to between 20 and 40. A static traffic assignment model of Stockholm is used for evaluating a large number of different configurations of the surrogate‐based optimization method. Final evaluation is performed with the dynamic traffic assignment tool VisumDUE, coupled with the demand model Regent, for a Stockholm network including 1240 demand zones and 17 000 links. Our results show that the surrogate‐based optimization method can indeed be used for designing a congestion charging scheme, which return a high social surplus. Copyright © 2016 John Wiley & Sons, Ltd.     

励磁涌流仿真中铁磁元件磁滞特性新模型

介绍了一个模拟铁磁元件磁滞特性的新数学模型。铁磁元件多值的磁滞特性被等值地模拟为一个极限磁滞回线和局部磁滞回线,极限磁滞回线由三次样条函数表示,局部磁滞一则按逆转点的位置及从极限磁滞回线开始的一非线性变化的纵向位移来生成。     

针摆行星传动中复合齿形摆线轮等效代换齿廓的研究

提出了采用完整的短幅外摆线的等距曲线作为摆线轮齿廓，来等效代换针摆行星传动中复合齿形摆线轮齿廓的理论，并给出了求解等效齿廓参数的数学模型、计算方法和求解实例。     

电动汽车全参数化车身平台化与模块化建模及性能带宽研究

为解决概念设计阶段电动汽车开发周期长等问题,基于隐式参数化方法提出一种电动汽车全参数化车身的平台化与模块化建模策略。首先将车身结构分解为上车体结构与下车体结构,根据设计要求对上下车体各自进行区域划分,定义各区域关键平台化衍生尺寸并进行基线总布置,形成平台化建模策略;然后基于平台化建模对下车体进行功能性模块划分,对上车体进行匹配性模块划分,分别进行参数化建模,形成模块化建模策略;最终建立了某款电动汽车车身的全参数化模型。结果表明,建模策略可实现不同车型的快速衍生,并且根据性能带宽规律,探究了轮距、轴距、车高、前端长度以及后端长度变化对刚度和模态性能的影响,有助于实现基于性能驱动的电动汽车车身与电池包的短周期开发。