地铁列车逻辑控制电路安全服役技术应用研究

为克服传统地铁列车继电器控制电路高故障率和无记录功能等诸多缺陷,提出了基于新型二乘二取二技术的无触点逻辑控制方案。完成了系统架构设计包括热备冗余、网络通信、故障诊断、日志分析等功能。针对既有地铁列车进行了控制电路技术方案设计和施工改造,首先在分析原有控制回路原理的基础上,完成无触点逻辑控制单元替代继电器点位设计;然后综合安全性和可用性提出了故障分级方案和大旁路方案;最后在运营线路完成了列车功能验证。试验结果表明改造后列车具备逻辑完整性,功能测试符合车辆技术要求,并可实现单板故障的自动无缝切换。具备自诊断健康管理功能,在满足高可靠性高安全性的同时,实现逻辑控制的网络信息化。     

可编程逻辑控制器在上海轨道交通6号线设备监控系统中的应用

随着城市轨道交通的快速发展,设备监控系统越来越受到人们的关注。上海轨道交通6号线设备监控系统采用可编程逻辑控制器作为系统的核心部件。介绍了基于工业以太网构建的系统平台,分析了该系统的特点,并结合上海轨道交通6号线的具体情况,对工业以太网的实时性进行分析。     

应用模糊自适应PID和预瞄策略的自主车辆转向控制

文中结合智能车辆路径跟踪过程中转向控制方面的特点，提出了一种将模糊逻辑、预瞄规律和自适应PID控制相结合的控制策略，建立起了相应的模型，验证了该方法的可行性和有效性，并提出了进一步改进的方向。     

模糊逻辑推理在消除交通流诱导负效应中的应用

针对交通流诱导可能产生的负效应问题,提出了诱导负效应消除的原理和模糊逻辑推理方法。在原理设计中,考虑了出行者的出行行为对网络交通流分配的影响;在实现方法上,应用模糊推理技术对分流交通量进行了预测,并设计了路线交叉口信号灯配时方案调整的模糊控制算法,模拟结果验证了模糊逻辑推理技术的有效性。研究表明:交通流诱导负效应的产生主要是由于信息条件下的道路出行者路线选择行为的不确定性引起的,而且交通流诱导与控制同时进行是消除交通流诱导负效应产生的关键。     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

Ontologies for transportation research: A survey

Transportation research relies heavily on a variety of data. From sensors to surveys, data supports day-to-day operations as well as long-term planning and decision-making. The challenges that arise due to the volume and variety of data that are found in transportation research can be effectively addressed by ontologies. This opportunity has already been recognized – there are a number of existing transportation ontologies, however the relationship between them is unclear. The goal of this work is to provide an overview of the opportunities for ontologies in transportation research and operation, and to present a survey of existing transportation ontologies to serve two purposes: (1) to provide a resource for the transportation research community to aid in understanding (and potentially selecting between) existing transportation ontologies; and (2) to identify future work for the development of transportation ontologies, by identifying areas that may be lacking.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.     

基于逻辑推演理论的船舶避碰决策

提出了研究船舶避碰决策的一个新方法,并把多逻辑系统作用的结构演化引入舰艇避碰决策系统,构建了船舶避碰决策系统逻辑推理的基本理论,指出了进一步的研究方向。     

TRIP DISTRIBUTION MODELLING USING FUZZY LOGIC AND A GENETIC ALGORITHM

This article examines possibilities for the application of soft computing techniques for the prediction of travel demand. The model, based on fuzzy logic and a genetic algorithm, successfully solves the trip distribution problem. The possibilities of using the proposed model in solving trip generation, modal split and route choice problems have also been indicated. The model has been tested on a real numerical example. Exceptionally good correspondences between estimated and real values of passenger flows have been obtained.     

基于模糊逻辑控制策略的混合动力汽车仿真研究

以燃油经济性和排放性能为主要控制目标,提出一种基于模糊逻辑的能量分配控制策略,应用ADVISOR仿真软件,对制定的控制策略在不同的道路循环工况下进行仿真。仿真结果表明,所设计的模糊逻辑控制策略能够合理分配发动机和电机的转矩,可使发动机工作在效率较高、排放较低的中等负荷区,整车的燃油经济性较好、排放较低。