基于动态执行机构的船舶循迹反步积分控制

文章针对连续曲率路径,用一种简单的几何方法生成连续曲率的路径.基于该几何方法生成的连续路径,文中利用line-of-sight(LOS)引导律解决了循迹控制中横向偏差最小的问题.为了减弱控制输出的振荡和获得平滑的控制输出,一种基于动态执行机构的改进反步积分控制器在过驱动船舶循迹控制中得到了应用.值得注意的是,文中用积分操作来抵抗风浪流环境力.数值分析结果展示了该控制器的有效性.     

Combined longitudinal and lateral control for automated vehicle guidance

This paper deals with the longitudinal and lateral control of an automotive vehicle within the framework of fully automated guidance. The automotive vehicle is a complex system characterised by highly nonlinear longitudinal and lateral coupled dynamics. Consequently, automated guidance must be simultaneously performed with longitudinal and lateral control. This work presents an automated steering strategy based on nonlinear model predictive control. A nonlinear longitudinal control strategy considering powertrain dynamics is also proposed to cope with the longitudinal speed tracking problem. Finally, a simultaneous longitudinal and lateral control strategy helps to improve the combined control performance. This whole control strategy is tested through simulations showing the effectiveness of the present approach.     

城市交通信号控制系统(ACTRA)应用简介及构想

介绍了ACTRA交通信号控制系统的结构、特点及其主要控制策略,并对该控制系统几种主要的系统功能以图形界面形式进行了描述.对此系统目前在北京市的初步应用进行了简要介绍,并在路段调查数据的基础上进行效果评价.提出了ACTRA系统应该如何与路线诱导系统实现数据共享和方案协调,并使交通控制中心在诱导条件下实现交通控制子区自动划分的构想,以便更好地提高路网的运行效益.     

基于改进遗传算法的最优路径求解

动态路径诱导系统(dynamic route guidance system,DRGS)是通过提供基于实时交通信息的最优路径来引导交通流的,因此,最优路径的求解是关键.而遗传算法具有全局寻优和潜在并行的特点,对求解最优路径具有一定优势.但采用序号编码方式进行遗传操作时会产生大量无效路径.文中结合城市道路交叉口左转、右转、直行等转向行为,设计了一种新的基于转向行为的编码方式,减少了染色体在交叉、变异时的无效路径的生成.算例表明,这种编码方式可以有效提高算法收敛性,更容易获得最优解.     

包含禁行路线路网的最优路径HNN算法

为了解决包含禁行路线路网的最优路径快速求解问题,研究了不含禁行路线路网和包含禁行路线路网的特点,建立了相应的路网数学模型。通过路网转化法把包含禁行路线的路网转化为不含禁行路线的路网,降低了最优路径求解的难度。研究了霍普费尔特神经网络(Hopfield Neural Network,HNN)的特点,设计了适合求解路网最优路径的HNN算法,在算法中采用动态邻接矩阵,节省了计算机内存,减少了运算时间。将所研究的路网转化方法和设计的HNN算法应用于所研发的车辆诱导系统中,并进行了实际路网测试,结果表明应用该方法能够在包含禁行路线路网中求解最优路径,且比经典算法的运算效率高。     

基于中关村西区的地下停车诱导信息系统设计

以北京中关村西区地下停车场为背景，对停车诱导信息系统进行了设计与研究。文章主要介绍了中关村西区地下停车场诱导信息发布方案的设计，基于BP神经网络的停车泊位预测以及基于模糊推理的地下环廊路段优化选择，并给出了Matlab环境下的仿真结果。     

基于交通网络数据集的动态路径诱导系统规划与实现探讨

智能交通是当前公认的有效解决交通拥堵、能源消耗及交通污染等突出问题的根本途径,而动态的交通诱导系统则是智能交通的核心研究领域之一,并一直被学术界和企业界所关注。当前已有诸多成果,但能广泛应用于实际交通环境的不多,通过着重探讨基于交通网络数据集下的动态路径诱导系统的规划设计与实现方式,有利于交通动态路径诱导系统的开发应用。     

关于海事行政指导的几点思考

文中梳理了海事行政指导的概念和特征，分析了推行海事行政指导的重要意义，提出了推行海事行政指导的几点措施建议.     

Reliable route guidance: A case study from Chicago

Reliable route guidance can be obtained by solving the reliable a priori shortest path problem, which finds paths that maximize the probability of arriving on time. The goal of this paper is to demonstrate the benefits and applicability of such route guidance using a case study. An adaptive discretization scheme is first proposed to improve the efficiency in computing convolution, a time-consuming step used in the reliable routing algorithm to obtain path travel time distributions. Methods to construct link travel time distributions from real data in the case study are then discussed. Particularly, the travel time distributions on arterial streets are estimated from linear regression models calibrated from expressway data. Numerical experiments demonstrate that optimal paths are substantially affected by the reliability requirement in rush hours, and that reliable route guidance could generate up to 5-15% of travel time savings. The study also verifies that existing algorithms can solve large-scale problems within a reasonable amount of time.