自主式水下机器人最优路径规划问题的研究

路径规划是水下机器人实现自主航行的重要环节。根据自主式水下机器人的动力学性质，路径规划的特点以及实现智能行为的要求，采用基于案例的遗传算法，实现了自主式水下机器人最优路径规划。给出该方案的基本框架和算法，在基于案例类比的学习方法中引入模糊多属性综合决策的方法建立决策算子进行案例的匹配，在遗传算法中实际知识的指导，适当地改进遗传算子，加快搜索速度。仿真结果证明该路径规划方法能够取得较好的规划结果，使自主式水下机器人具有了一定的自主导航，自主避障和自主作业的能力。     

When human beings are like drunk robots: Driverless vehicles,ethics, and the future of transport

It is often argued that driverless vehicles will save lives. In this paper, we treat the ethical case for driverless vehicles seriously and show that it has radical implications for the future of transport. After briefly discussing the current state of driverless vehicle technology, we suggest that systems that rely upon human supervision are likely to be dangerous when used by ordinary people in real-world driving conditions and are unlikely to satisfy the desires of consumers. We then argue that the invention of fully autonomous vehicles that pose a lower risk to third parties than human drivers will establish a compelling case against the moral permissibility of manual driving. As long as driverless vehicles aren’t safer than human drivers, it will be unethical to sell them. Once they are safer than human drivers when it comes to risks to 3rd parties, then it should be illegal to drive them: at that point human drivers will be the moral equivalent of drunk robots. We also describe two plausible mechanisms whereby this ethical argument may generate political pressure to have it reflected in legislation. Freeing people from the necessity of driving, though, will transform the relationship people have with their cars, which will in turn open up new possibilities for the transport uses of the automobile. The ethical challenge posed by driverless vehicles for transport policy is therefore to ensure that the most socially and environmentally beneficial of these possibilities is realised. We highlight several key policy choices that will determine how likely it is that this challenge will be met.     

Help or hindrance? The travel,energy and carbon impacts of highly automated vehicles

Experts predict that new automobiles will be capable of driving themselves under limited conditions within 5–10 years, and under most conditions within 10–20 years. Automation may affect road vehicle energy consumption and greenhouse gas (GHG) emissions in a host of ways, positive and negative, by causing changes in travel demand, vehicle design, vehicle operating profiles, and choices of fuels. In this paper, we identify specific mechanisms through which automation may affect travel and energy demand and resulting GHG emissions and bring them together using a coherent energy decomposition framework. We review the literature for estimates of the energy impacts of each mechanism and, where the literature is lacking, develop our own estimates using engineering and economic analysis. We consider how widely applicable each mechanism is, and quantify the potential impact of each mechanism on a common basis: the percentage change it is expected to cause in total GHG emissions from light-duty or heavy-duty vehicles in the U.S. Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half – or nearly double them – depending on which effects come to dominate. We also find that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. We close by presenting some implications for policymakers and identifying priority areas for further research.     

Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities.     

A hybrid controller for autonomous vehicles driving on automated highways

This paper addresses the problem of the hybrid control of autonomous vehicles driving on automated highways. Vehicles are autonomous, so they do not communicate with each other nor with the infrastructure. Two problems have to be dealt with: a vehicle driving in a single-lane highway must never collide with its leading vehicle; and a vehicle entering the highway at a designated entry junction must be able to merge from the merging lane to the main lane, again without any collision. To solve these problems, we equip each vehicle with a hybrid controller, consisting of several continuous control laws embedded inside a finite state automaton. The automaton specifies when a given vehicle must enter the highway, merge into the main lane, yield to other vehicles, exit from the highway, and so on. The continuous control laws specify what acceleration the vehicle must have in order to avoid collisions with nearby vehicles. By carefully designing these control laws and the conditions guarding the automaton transitions, we are able to demonstrate three important results. First, we state the initial conditions guaranteeing that a following vehicle never collides with its leading vehicle. Second, we extend this first result to a lane of autonomous vehicles. Third, we prove that if all the vehicles are equipped with our hybrid controller, then no collision can ever occur, and all vehicles either merge successfully or are forced to drop out when they reach the end of their merging lane. Finally, we show the outcome of a highway microsimulation modelled after the Katy Corridor near Houston, Texas: our single-lane highway can accommodate 4000 vehicles per hour with neither drop-outs nor traffic congestion. It is entirely programmed in SHIFT, a hybrid systems simulation language developed at UC Berkeley by the PATH group. This shows that SHIFT is a well suited language for designing safe control laws for autonomous highway systems, among others.     

电动汽车常用牵引电动机

本文简要介绍电动汽车常用牵引电动机的种类、结构、工作原理、特点以及控制系统。     

深水爆炸水动压力场对潜体结构的动态影响

拓广ＤＡＡ法用于预报水中一次冲击波对悬浮体的动响应；引和当量能量与当量深度概念，计算了有自由水面的水下爆炸迁移气泡多次脉冲动力学特性，数值计算值与实测值作了对比，并给给出了水中存在圆柱壳时气泡脉动压力的经验公式。     

水下文物原址保护施工技术与造价分析

涪陵白鹤梁题刻原址水下文物保护工程,采用“无压容器”原理,在白鹤梁上端修建一椭圆形平面单跨拱形壳体,通过岸上交通廊道连接水下U形参观廊道,绕题刻一周,可在“水下博物馆”看到石刻原貌。此文旨在介绍其施工方法和施工工艺,并对造价进行分析。     

解读CJ/T416—2012《城市轨道交通车辆防火要求》

在介绍CJ/T 416—2012《城市轨道交通车辆防火要求》制定背景和标准概况的基础上,从车辆防火等级判定原则、防火隔板设置要求、试验标准的确定、部件和材料的防火性能要求等方面,解读标准的技术关键内容,并提出标准的实施建议。     

广深港客专狮子洋隧道照明系统改造防腐措施的探讨

通过对广深港客专狮子洋隧道照明系统供电设施的现状调查与分析,针对隧道内高潮湿、高盐分、强腐蚀等特点,提出隧道照明系统防腐蚀控制措施:(1)配电箱(柜)设备外壳的材质采用防腐蚀性强的材料316L不锈钢并加喷涂船舰漆;(2)照明灯具表面加一层氧化铝薄膜,以提升设备使用寿命;(3)电力电缆增加铅护套层,以提高电缆防潮抗腐能力;(4)配电箱(柜)采用双层结构,照明灯具采用光源室和驱动电路室相互独立结构,以提高产品自身的防腐结构设计;(5)照明供电及控制系统进行优化设计,减少控制开关和电源设备,以减少设备数量和日常维护工作量,达到良好的维护管理。