专家系统在分散自律调度集中系统中的应用

描述了将专家系统理论应用于分散自律调度集中系统的车站自律机的设计,给出了自律机专家系统的知识库、推理机的构架及原理,并介绍了自律机知识库自学习机制.由于采用了专家系统,从而提高了自律机的自动化和智能化程度.     

Model based urban traffic control,part II: Coordinated model predictive controllers

The present paper describes how to use coordination between neighbouring intersections in order to improve the performance of urban traffic controllers. Both the local MPC (LMPC) introduced in the companion paper (Hao et al., 2018) and the coordinated MPC (CMPC) introduced in this paper use the urban cell transmission model (UCTM) (Hao et al., 2018) in order to predict the average delay of vehicles in the upstream links of each intersection, for different scenarios of switching times of the traffic lights at that intersection. The feedback controller selects the next switching times of the traffic light corresponding to the shortest predicted average delay. While the local MPC (Hao et al., 2018) only uses local measurements of traffic in the links connected to the intersection in comparing the performance of different scenarios, the CMPC approach improves the accuracy of the performance predictions by allowing a control agent to exchange information about planned switching times with control agents at all neighbouring intersections. Compared to local MPC the offline information on average flow rates from neighbouring intersections is replaced in coordinated MPC by additional online information on when the neighbouring intersections plan to send vehicles to the intersection under control. To achieve good coordination planned switching times should not change too often, hence a cost for changing planned schedules from one decision time to the next decision time is added to the cost function. In order to improve the stability properties of CMPC a prediction of the sum of squared queue sizes is used whenever some downstream queues of an intersection become too long. Only scenarios that decrease this sum of squares of local queues are considered for possible implementation. This stabilization criterion is shown experimentally to further improve the performance of our controller. In particular it leads to a significant reduction of the queues that build up at the edges of the traffic region under control. We compare via simulation the average delay of vehicles travelling on a simple 4 by 4 Manhattan grid, for traffic lights with pre-timed control, traffic lights using the local MPC controller (Hao et al., 2018), and coordinated MPC (with and without the stabilizing condition). These simulations show that the proposed CMPC achieves a significant reduction in delay for different traffic conditions in comparison to these other strategies.     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

船用中压细水雾灭火系统的总体设计

作为国际火灾科学前沿的研究热点之一,细水雾灭火技术以其高效、环保的特点,已经成为最具有发展潜力的哈龙替代技术。本文根据船舶的实际情况及船用细水雾灭火系统的技术要求,提出了船用泵－罐联用式中压细水雾灭火系统的总体设计方案,以实现对船舶的消防保护。     

电动客车轮边驱动电机的转矩分配控制策略研究

轮边驱动电机采用轮毂电机,实现四轮独立驱动,方便汽车动力学性能的控制。对于电动客车,轮边电机驱动以其轻量化、传递效率高等优势正在取代中央直驱的方式,成为现在研究的热点。这种驱动方式取消了离合器和变速器等,驱动电机安装在车轮旁边,结构空间和重量得以大幅度降低电。文章以四轮独立驱动的轮毂电机电动客车为研究对象,通过驱动转矩的合理分配,保证其有最佳的动力性和经济性。     

GSM-R分布式基站在多隧道区段的应用

从GSM-R分布式基站的特性入手,对组网结构、设备性能以及可维护性三方面进行了分析,并进行了大秦线多隧道区段应用GSM-R分布式基站前后质量对比,为GSM-R分布式基站在多隧道区段应用提供了可靠的理论和实践依据.     

微观交通分布式并行仿真系统设计与效益分析

为了提高交通网络仿真的速度和效率,从挖掘交通网络仿真的并行性出发,设计了分布式并行仿真系统的结构和仿真算法,通过比较选择PVM(Parallel Virtual Machine)作为并行计算的编程环境,提出基于车辆数的网络分割算法和数据时钟同步的通讯方式,使并行仿真达到负载平衡。用程序执行时间、加速比、并行效率和可扩展性4个测度指标来评价算法的并行效益,并以24个交叉口组成的交通网络为例,应用设计的并行算法在不同处理器数目下进行仿真。试验结果显示并行仿真速度比串行仿真提高了3.5倍,因此,这种并行算法提高了交通网络仿真的速度和效率,为实现更大规模的交通仿真奠定了基础。     

分布式工业进程参数监测系统实时多任务软件的设计

作者从操作系统的观点出发,分析分布式工业过程参数监测系统实时多任务软件的方法,解决了在DOS环境下,支持多任务问题。     

基于CORBA与RMI／EJB的异构分布对象系统的集成

本文系统地分析了分布式计算模型CORBVA，Java RMI的体系结构及组件模型EJB的现状和发展趋势的基础上，对CORBA与RMI／EJB的集成进行研究，并将其应用于大庆站信息系统的开发。     

分布式地铁列车驾驶仿真器的体系结构

从列车驾驶仿真器的体系结构出发,提出一种分布式列车驾驶仿真器的实现方案。该方案中,地铁列车驾驶仿真器由数据采集及输出、主控、ATC仿真、视景仿真、声音仿真、数字广播及通信仿真、运动平台控制等仿真子系统组成。子系统间采用IP组播的方式进行通信。方案支持基于DIS协议的仿真器间的通信,可实现多仿真器协同训练。为降低通信强度,提高仿真的实时性,采用一种DR算法。