考虑螺旋桨体积力的水下机器人水动力特性仿真

为在初步设计时预测ROV的水动力性能,使用CFD技术进行分析,以ROV模型为例,最大程度地保留ROV内部的构件,使模型更加接近真实状况。分别计算ROV在不同工况下的阻力、不同漂角下的横向力和转艏力矩以及添加体积力模型之后的螺旋桨流场状况,很好地模拟出ROV周围的流场,并与已有的试验数据进行对比。结果验证了CFD水动力仿真的可行性和准确性,并还可预测ROV在螺旋桨作用下的进速等,对ROV设计具有实际的参考价值和指导意义。     

A two-dimensional simulation model for modelling turning vehicles at mixed-flow intersections

The turning behavior is one of the most challenging driving maneuvers under non-protected phase at mixed-flow intersections. Currently, one-dimensional simulation models focus on car-following and gap-acceptance behaviors in pre-defined lanes with few lane-changing behaviors, and they cannot model the lateral and longitudinal behaviors simultaneously, which has limitation in representing the realistic turning behavior. This paper proposes a three-layered “plan-decision-action” (PDA) framework to obtain acceleration and angular velocity in the turning process. The plan layer firstly calculates the two-dimensional optimal path and dynamically adjusts the trajectories according to interacting objects. The decision layer then uses the decision tree method to select a suitable behavior in three alternatives: car-following, turning and yielding. Finally, in the action layer, a set of corresponding operational models specify the decided behavior into control parameters. The proposed model is tested by reproducing 210 trajectories of left-turn vehicles at a two-phase mixed-flow intersection in Shanghai. As a result, the simulation reproduces the variation of trajectories, while the coverage rate of the trajectories is 88.8%. Meanwhile, both the travel time and post-encroachment time of simulation and empirical turning vehicles are similar and do not show statistically significant difference.     

港口高杆灯的无线智能控制系统设计

随着港口建设规模的扩大,港区堆场面积越来越大,配套的高杆灯及其他照明设施的数量也相应增加,需要一个自动化的、科学的管理方式和系统对其进行管理和控制。照明无线智能控制系统采用先进可靠的远距离无线通信技术,将人机操作界面和远程控制环节有机结合起来,实现对高杆灯的远距离无线控制。通过高杆灯无线智能控制系统,合理组合开启灯具数量和安排开启时间,智能调光,以达到高效节能、安全运行的良好效果。     

轨道交通车辆的工艺流程标准化

从生产线建立、工艺流程编制、工艺布局设计和生产能力等方面进行分析,提出了轨道交通车辆工艺流程标准化设计方法和优化方法。基于精益管理理念和工序能力测算法,可以合理编制标准化工艺流程,从而降低劳动强度,提高生产效率。     

Eco-driving behaviors of electric vehicle users: A survey study

Previous research has shown that electric vehicle (EV) users could behave differently compared to internal combustion engine vehicle (ICEV) drivers due to their consciousness or practices of eco-driving, but very limited research has fully investigated this assumption. This research explores this topic through investigating EV drivers’ eco-driving behaviors and motivations. We first conducted a questionnaire survey on EV drivers’ driving behavior and some hypothetical decisions of their driving. It indicates various characteristics between EV and ICEV commuters, including self-reported daily driving habits, preferences of route choices, tradeoff between travel time and energy saving, and adoption of in-vehicle display (IVD) technologies. Then, through statistical analysis with Fisher’s exact test and Mann-Whitney U test, this research reveals that, compared to ICEV drivers, EV drivers possess significantly calmer driving maneuvers and more fuel-efficient driving habits such as trip chaining. The survey data also show that EV drivers are much more willing to save energy in compensation of travel time. Furthermore, the survey data indicate that EV drivers are more willing to adopt eco-friendly IVD technologies. All these findings are expected to improve the understanding of some unique behavior found in EV drivers.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

城市轨道交通车辆产品标准体系探索

分析了国内外城市轨道交通车辆产品标准体系的现状,重点介绍了城市轨道交通车辆产品标准体系的总体要求、结构搭建、产品标准的制修订,以及标准的实施和改进措施。     

弹性垫形式的水下弹性体发射动力学分析

弹性垫会对水下运载器发射动力学产生影响,文章针对弹性垫形式,利用Lagrange方程推导了新型适配关系下的发射动力学方程,同时考虑了运载器的刚体运动、弹性变形、弹性垫变形与接触对发射过程的影响。利用文中的方法,建立了水下运载器发射动力学模型,对发射过程的载荷进行了求解,研究了弹性垫数量、刚度、位置等参数对运载器弹性振动的影响。结果表明文中方法是有效的,可用于水下运载器发射动力学分析。     

快速路可变限速与匝道控制协同优化策略

可变限速控制和匝道控制是快速路交通控制的主要手段,本文对两者的协同优化策略进行了研究.借助智能车路协同系统强大的信息感知能力,通过引入微观交通流信息,对经典METANET模型进行了改造,构建了可变限速控制影响下的微观METANET模型,实现了一种新的可变限速控制策略,同时,采用ALINEA算法,对入口匝道进行了优化控制,实现了两者的协同优化.最后,基于实际道路和交通流数据搭建了仿真平台,对微观METANET模型和协同优化策略的有效性进行了验证.仿真结果表明,微观METANET模型具有良好的交通流预测效果,协同优化策略能有效地改善快速路交通流状态.     

基于GPS与图像融合的智能车辆高精度定位算法

车辆自定位是实现智能车辆环境感知的核心问题之一.全球定位系统(Global Positioning System,GPS)定位误差通常在10 m左右,不能满足智能车辆的定位需求;惯性导航系统成本较高,不适于智能车辆的推广.本文在视觉地图基础上,提出一种基于GPS与图像融合的智能车辆定位算法.该算法以计算当前位置距离视觉地图中最近一个数据采集点的位姿为目标,首先运用GPS信息进行初定位,在视觉地图中选取若干采集点作为初步候选,其次运用Oriented FAST and Rotated BRIEF(ORB)全局特征进行特征匹配,得到一个候选定位结果,最后通过待检测图像中的局部特征点与候选定位结果中的三维局部特征点建立透视n点模型(Perspective-n-Point,Pn P),得到车辆当前的位姿,并以此对候选定位结果进行修正,得到最终定位结果.实验在长为5 km的路段中进行,并在不同天气及不同智能车辆平台测试.经验证,平均定位精度为11.6 cm,最大定位误差为37 cm,同时对不同天气具有较强鲁棒性.该算法满足了智能车定位需求,且大幅降低了高精度定位成本.