Rough Terrain Autonomous Mobility—Part 1: A Theoretical Analysis of Requirements

A basic requirement of autonomous vehicles is that of guaranteeing the safety of the vehicle by avoiding hazardous situations. This paper analyses this requirement in general terms of real-time response, throughput, and the resolution and accuracy of sensors and computations. Several nondimensional expressions emerge which characterize requirements in canonical form.The automatic generation of dense geometric models for autonomously navigating vehicles is a computationally expensive process. Using first principles, it is possible to quantify the relationship between the raw throughput required of the perception system and the maximum safely achievable speed of the vehicle. We derive several useful expressions for the complexity of terrain mapping perception under various assumptions. All of them can be reduced to polynomials in the response distance.The significant time consumed by geometric perception degrades real-time response characteristics. Using our results, several strategies of active geometric perception arise which are practical for autonomous vehicles and increasingly important at higher speeds.     

一个新的基于Vague集加权相似度量的双向近似推理方法

提出了一种新的Vague集的加权相似度量方法以解决文献[1]中关于vague集相似度量的某些缺陷，并且提出了Vague集间相似方向的概念，用它来描述两个相似Vague集中哪个所包含的信息更精确，并给出了一个判定方法。在此基础上给出了一种基于Vague集加权相似度量的双向近似推理方法，该方法更好地利用了vague集信息的精确性，从而提高了推理的精确性和适用性．这为智能系统中的近似推理提供了一个十分有用的工具．     

Navigation of an AUV for investigation of underwater structures

There is a great demand for autonomous underwater vehicles (AUVs) to investigate artificial underwater structures such as piles and caissons in harbours, and risers and jackets of deep-sea oilfields. This paper proposes an autonomous investigation method of underwater structures using AUVs that is implemented by initially detecting the target objects, localizing them, then approaching them by taking video images while closely tracing their shape. A laser ranging system and a navigation method based on the relative position with respect to the target objects are introduced to realize this behaviour.     

“车-站-网”多元需求下的电动汽车快速充电引导策略

提出一种面向电动汽车(车)、快速充电站(站)、配电网(网)多元需求的电动汽车快速充电引导策略。首先介绍了“车-站-网”协同模式下充电引导架构,并基于起讫点分析得出的快充需求分布结果,提出一种双层队列模型模拟快速充电站动态队列。然后,根据动态队列和节点电压约束下配电网快充负荷接纳能力,采用动态电价需求函数建立充电电价模型,以用户充电成本最小为目标引导用户选择快速充电站。最后,以某市部分主城区为例,对1 000辆具有快充需求的电动汽车在不同参与度下进行仿真。结果表明,所提充电引导策略能够在节约用户充电成本的同时,提高快速充电站的运营效率,保证配电网的运行安全。     

超小型浅水潜水器用活塞式沉浮系统结构设计

随着水下机器人技术的不断推进,超小型浅水潜水器受到了广泛关注。而在超小型、浅水环境,传统的螺旋桨推进机构却存在着一定的缺点。为此,提出一种基于传统方法的新思路,用活塞式伸缩机构实现潜水器的低功耗,能较好实现稳定沉浮运动。     

UUV海底定点停驻受力特性及稳定性分析

在简单介绍海底定点停驻UUV概念及工作过程的基础上,建立了其在海底时的稳定性分析模型,并推导出了航行器负浮力、主轴与两支撑点之间的半角θ、流体动力Fx、Fy之间的关系。为了研究航行器在海底时的流体动力特性,采用Ansys ICEM对其离海底不同距离及海底有不同倾角时的情况进行结构化的网格划分,并应用CFX软件对其在不同水流速度下的外围流场进行数值仿真,得到了其在海底时所受侧向力、升力随距海底的距离、海水流速及海底倾角的变化趋势。最后,对航行器在海底时的稳定性进行了分析并得到了一组能够保证航行器海底稳定的较好参数。     

基于马尔可夫决策过程的电动汽车充电行为分析

针对电动汽车充电行为不确定性问题,建立了基于出行链理论的电动汽车出行及电池电量变化模型,提出了引入马尔可夫决策过程（Markov decision processes, MDP）的电动汽车用户充电行为分析方法。该方法将用户充电行为作为马尔可夫决策集,根据车辆在各区域间的转移概率构造状态转移矩阵,设置用户满意度指标作为决策过程报酬函数,通过求解有限阶段总报酬准则得到电动汽车用户在每个决策点处的最优充电决策。算例部分根据抽取电动汽车特征量数据进行马尔可夫决策过程仿真,得出充电负荷的时间与空间分布情况,通过与传统蒙特卡洛方法进行对比表明该文所提方法可以较好地模拟用户整个出行过程中的充电行为,反映充电需求的时空分布特点;同时,分析了不同区域、不同停车时长情况下电动汽车的不同充电行为,能够为电动汽车充电桩的规划建设提供参考。     

电动汽车规模化与智能电网建设展望

由于能源短缺、温室效应和大气污染等多方面原因,各个国家和科研机构都纷纷致力于发展各种新型低污染、能源利用率高的插入式电动汽车汽车.近年来混合动力汽车和纯电池电动汽车都得到了较大的发展,阻碍其规模化的原因除了新型汽车本身的技术问题之外,电网技术对其的兼容与支持程度也成为一个重要原因.本文就混合动力汽车和纯电池电动汽车规模化带给电网的影响及电网技术所需要的变革进行了适当讨论.提出以智能电网为基础,实现电动汽车统一协调控制.在兼容和支持电动汽车规模化的同时降低电力生产和维护成本,提高电力系统的可控性和可靠性.     

具有隐私保护的车联网空间众包任务分配方法

为了解决传统车联网空间众包中集中式空间众包服务器不可信和易遭受攻击给用户隐私带来极大威胁的问题,提出区块链架构下具有隐私保护的车联网空间众包任务分配方法. 基于区块链技术,设计分布式可信的车联网空间众包系统. 采用多密钥全同态加密算法实现任务分配,支持对不同车辆用户 (密钥) 的密文数据进行任务分配,降低隐私泄露的可能性. 实验分析表明,采用该方法能够有效地保护用户隐私信息,任务分配的计算时间开销与现有研究方法相比下降了34.3%,提高了任务分配的效率.     

Delays caused by motorized vehicles unable to clear intersections in China： Graphical analysis

In many Chinese cities,motorized vehicles （M-vehicles） move slowly at intersections due to the interference of a large number of non-motorized vehicles （NM-vehicles）.The slow movement makes a part of M-vehicles fail to leave intersections timely after the traffic signal tums red,and thereby conflicts between vehicles from two directions occur.The phenomenon was analyzed graphically by using the cumulative vehicle curve.Delays in three cases were modeled and compared：NM-vehicle priorities and M-vehicle priorities with all-red intervals unable to release all vehicles,and longer all-red intervals ensuring release all vehicles.Marginal delays caused by two illegal behaviors that occasionally happened in mixed traffic intersections were also investigated.It is concluded that increasing the speed of M-vehicles leaving intersections and postponing the entering of NM-vehicles are the keys in mathematics,although they are uneasy in disordered mixed traffic intersections due to a dilemma between efficiency and orders in reality.The results could provide implications for the traffic management in the cities maintaining a large number of M-and NM-vehicles.