SW-220K型转向架参数优化试验研究

对配装SW—220K型转向架的25T型客车进行了振动试验;分析了车辆的主要振型;分别进行了采用不同空气弹簧、二系阻尼系数值时的试验,根据垂向、横向平稳性指标测试结果,得出了采用原型空气弹簧结构并增大二系垂向阻尼系数值能够改善车辆运行性能的结论。     

Design of robust-stable and quadratic finite-horizon optimal controllers with low trajectory sensitivity for uncertain active suspension systems

This paper presents a design method for designing the robust-stable and quadratic-finite-horizon-optimal controllers of uncertain active suspension systems. The method integrates a robust stabilisability condition, the orthogonal functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA). Using the integrative computational method, a robust-stable and quadratic-finite-horizon-optimal controller with low-trajectory sensitivity can be obtained such that (i) the active suspension system with elemental parametric uncertainties is stabilised and (ii) a quadratic-finite-horizon-integral performance index including a quadratic trajectory sensitivity term for the nominal active suspension system is minimised. The robust stabilisability condition is proposed in terms of linear matrix inequalities (LMIs). Based on the OFA, an algebraic algorithm only involving the algebraic computation is derived for solving the nominal active suspension feedback dynamic equations. By using the OFA and the LMI-based robust stabilisability condition, the dynamic optimisation problem for the robust-stable and quadratic-finite-horizon-optimal controller design of the linear uncertain active suspension system is transformed into a static-constrained-optimisation problem represented by the algebraic equations with constraint of LMI-based robust stabilisability condition; thus greatly simplifies the design problem. Then, for the static-constrained-optimisation problem, the HTGA is employed to find the robust-stable and quadratic-finite-horizon-optimal controllers of the linear uncertain active suspension systems. A design example is given to demonstrate the applicability of the proposed integrative computational approach.     

考虑能源类型的城市出租车运营效率评价研究

以分析西安市燃气型、电动型及甲醇型3种能源类型出租车在运营中的既有期望运营投入和非期望运营投入，既有期望产出和非期望产出为基础，本文构建基于DEA-Malmquist的考虑能源类型的出租车运营效率评价模型。从西安市出租车管理处提取西安市 2020 年 9~12 月期间 14946辆出租车的GPS轨迹数据，并随机选取1000辆甲醇型出租车、1000 辆电动型出租车及 1000辆燃气型出租车作为样本进行实例分析。通过处理3000辆出租车GPS数据，得到乘客在工作日和双休日不同时段的出行需求和特征，分析3种不同能源类型出租车的运营效率差异。所得结论可为西安政府部门对不同能源类型出租车的管理运营提供决策支持。     

Real-time identification of probe vehicle trajectories in the mixed traffic corridor

This paper proposes three enhanced semi-supervised clustering algorithms, namely the Constrained-K-Means (CKM), the Seeded-K-Means (SKM), and the Semi-Supervised Fuzzy c-Means (SFCM), to identify probe vehicle trajectories in the mixed traffic corridor. The proposed algorithms are able to take advantage of the strengthens of topological relation judgment and the semi-supervised learning technique by optimizing the selection of pre-labeling samples and initial clustering centers of the original semi-supervised learning technique based on horizontal Global Positioning System data. The proposed algorithms were validated and evaluated based on the probe vehicle data collected at two mixed corridors on Shanghai’s urban expressways. Results indicate that the enhanced SFCM algorithm could achieve the best performance in terms of clustering purity and Normalized Mutual Information, followed by the CKM algorithm and the SKM algorithm. It may reach a nearly 100% clustering purity for the uncongested conditions and a clustering purity greater than 80% for the congested conditions. Meanwhile, it could improve clustering purity averagely by 21% and 14% for the congested conditions and 6.5% and 6% for the uncongested conditions, as compared with the traditional K-Means algorithm and the basic SFCM. The proposed algorithms can be applied for both on-line and off-line purposes, without the need of historical data. Clustering accuracies under different traffic conditions and possible improvements with the use of historical data are also discussed.     

Stop-and-go traffic analysis: Theoretical properties,environmental impacts and oscillation mitigation

This study aims (i) to analyze theoretical properties of a recently proposed describing-function (DF) based approach (Li and Ouyang, 2011; Li et al., 2012) for traffic oscillation quantification, (ii) to adapt it for estimating fuel consumption and emission from traffic oscillation and (iii) to explore vehicle control strategies of smoothing traffic with advanced technologies. The DF approach was developed to predict traffic oscillation propagation across a platoon of vehicles following each other by a nonlinear car-following law with only the leading vehicle’s input. We first simplify the DF approach and prove a set of properties (e.g., existence and uniqueness of its solution) that assure its prediction is always consistent with observed traffic oscillation patterns. Then we integrate the DF approach with existing estimation models of fuel consumption and emission to analytically predict environmental impacts (i.e., unit-distance fuel consumption and emission) from traffic oscillation. The prediction results by the DF approach are validated with both computer simulation and field measurements. Further, we explore how to utilize advantageous features of emerging sensing, communication and control technologies, such as fast response and information sharing, to smooth traffic oscillation and reduce its environmental impacts. We extend the studied car-following law to incorporate these features and apply the DF approach to demonstrate how these features can help dampen the growth of oscillation and environmental impact measurements. For information sharing, we convert the corresponding extended car-following law into a new fixed point problem and propose a simple bisecting based algorithm to efficiently solve it. Numerical experiments show that these new car-following control strategies can effectively suppress development of oscillation amplitude and consequently mitigate fuel consumption and emission.     

人机协作系统中车辆轨迹规划与轨迹跟踪控制研究

自动驾驶系统需具备响应驾驶人意图且有效执行驾驶人意图的能力，以解决人机协作系统中存在的人机冲突、人机优势融合等问题。提出决策层“以人为主”、执行层“以机为首”的人机协作关系，构建包含驾驶人意图识别模块、基于意图识别的轨迹规划模块与轨迹跟踪控制模块的人机协作一体化控制系统框架，并重点对轨迹规划模块与轨迹跟踪控制模块开展研究。首先，结合双向长短期记忆神经网络（Bi-directional Long Short Term Memory，Bi-LSTM）与注意力机制模型建立换道轨迹规划模型；在改进人工势场算法中引入模型预测控制并建立避险轨迹规划模型。其次，通过开展驾驶模拟器试验建立换道与避险驾驶行为数据集，为拟人化模型训练和模型参数确定提供支撑。然后，综合考虑车辆状态变量、控制输入与输出以及道路结构参数等约束条件，构建基于最优转向前轮输入的线性时变模型预测轨迹跟踪控制器，实现对规划轨迹的精准跟踪。最后，基于驾驶模拟器搭建人机协作系统硬件在环测试平台，对轨迹规划模块与轨迹跟踪控制模块开展硬件在环测试与验证。结果表明：换道与避险规划轨迹光滑且平稳，轨迹跟踪控制过程中，车辆航向角与前轮转角变化平稳；所构建的轨迹规划与轨迹跟踪控制模块在确保安全性前提下可实现不同场景中的车辆运动控制需求。     

基于全弹道控制分析的水下航行器攻击模型视景仿真*

研究并建立高空滑翔水下航行器的虚拟现实的视景仿真系统,分析水下航行器全弹道控制并在视景仿真平台下实现水下航行器全弹道多状态攻击轨迹模型。高空滑翔水下航行器姿态变化快,背景参数复杂,视景仿真中会出现局部模型快速变化或者模型分离的难题。提出采用DOF和Switch节点相结合的方法,利用其Matlab Simulink仿真模型,计算高空滑翔水下航行器的六自由度数据,通过Matlab的“To Workspace”模块将六自由度数据输出并存档。在VC＋＋6．0环境下编写Vega应用程序,读取运动参数,应用LOD技术在不降低显示速度的同时提高仿真视觉效果。仿真实验和测试效果表明,系统实能实现水下航行器在空中滑翔、低空突防、滑翔翼脱离以及水下攻击等多状态的水下航行器运动弹道轨迹和视景仿真效果,以及运动控制参数的同步跟踪,不再会因局部模型快速变化和模型分离而失真。为分析空投滑翔水下航行器的运动轨迹提供了数据支撑和视景平台支持,对展开高空滑翔水下航行器的弹道控制研究和试验具有重要价值。     

海底溢油输移扩散的可视化数值模拟系统

为直观研究溢油在复杂水下环境中的动态行为,设计和开发一套海底溢油可视化数值模拟系统(SIMPACT-SOS).系统由数值模型、数据库和图形界面构成,具有地理信息系统(GIS)应用平台、数值建模分析、溢油数值模拟等专业功能.应用算例表明,SIMPACT-SOS系统可为海底沉船溢油、海底输油管道泄漏、海洋石油钻井井喷等水下污染事故的风险评估、应急决策及损害评估提供理论和技术支持.     

船舶航迹跟踪的滑模控制

为了解决船舶路径跟踪中的非线性问题,在建立船舶非线性模型的基础上,采用指数趋近律,设计了船舶轨迹跟踪的滑模控制器,分别进行了动态直线跟踪和环形跟踪仿真试验,仿真结果表明,船舶动态轨迹跟踪性能良好,能精确保持航迹。     

潜艇目标大散布条件下鱼雷搜索弹道仿真

针对潜艇目标大散布条件,选取定角度扩展圆形和定时扩展圆形2种搜索弹道形式;对于不同目标散布大小、不同的自导作用距离,采用蒙特卡罗法对鱼雷发现概率进行仿真计算;根据仿真计算结果对鱼雷搜索弹道进行了合理优化,仿真结果可为目标大散布条件鱼雷搜索弹道设计提供一定参考。