机场救援消防车底盘系统研究

机场救援消防车底盘系统因特殊的使用要求,使其性能及技术应用达到了重型越野汽车技术的最高水平。随着我国重型越野车辆研究、制造水平的提高,我国已经在此领域进行了一些研究和试验。本文通过对机场救援消防车底盘系统的性能、国内外现有技术水平和未来发展趋势等几个方面的阐述对机场救援消防车底盘系统进行了较为全面的分析。     

调车作业分散自律控制系统的研究

通过分析我国铁路车站调车作业流程,提出调车作业分散自律控制系统模型,指出其实质就是将车站值班员的经验、知识和各种规章制度进行计算机形式化描述.通过空间冲突法和时间冲突法对列调车作业相互干扰问题进行智能疏解,得到列车进路指令序列和调车进路指令序列.根据实际列车运行位置、调车作业申请和当前时刻,自动匹配进路指令序列,生成列车进路命令序列和调车进路命令序列,自动下达车站联锁系统执行.采用多智能体技术和面向服务技术构建车站分散自律控制逻辑单元,实现调车作业以车站为自治域的分散自律控制.     

“行为导向”的建筑类英语自主学习能力探究

"行为导向"是上世纪80年代德国"双元制"职业教育中提倡的一种教学方法。近年来它被越来越多的高职教师所关注,并逐步应用于自己的课堂教学。本文介绍了行为导向教学模式及其优势,通过对建筑类高职生英语学习现状的分析,指出公共英语教师应将"行为导向法"引入其课堂,结合其理论下的模拟仿真教学法、合作学习法、案例教学法和大脑风暴法这四种教法,有效提高和培养学生英语自主学习的能力,使其为高职院校的英语课程改革服务。     

基于自适应神经网络的UUV航速控制仿真研究

针对无人水下航行器(UUV)在水动力参数变化和外界不确定干扰下的航速控制问题,提出一种基于李雅普诺夫方法的自适应神经网络控制算法。引入RBF神经网络来估计建模误差和海流干扰,并设计自适应学习律来保证神经网络权值的最优估计,保证了系统的航速误差收敛到零。仿真试验结果表明设计的控制器在航速控制过程中可有效抑制UUV载体的模型不确定性及海流干扰,且控制参数易于调节。     

水下爆炸二次脉动压力下舰船抗爆性能研究

将船体梁视为两端自由的Timoshenko梁,在借用二维切片法和水弹性方法的基础上,计算船体染在水下爆炸二次脉动压力下的响应特性。同时,还建立了在考虑水面效应和气泡运动时舰船受到二次脉动压力的计算模型。最后,分析了浮筏式减振装置在水下爆炸二次脉动压力下船用设备的减振抗冲性能。     

大断面水下盾构隧道管片接头抗弯刚度及其对管片内力影响研究

以大断面水下铁路盾构隧道-狮子洋隧道工程为研究对象,运用有限元数值分析方法,并结合管片接头原型抗弯试验,研究环向管片接头抗弯刚度,并运用梁-弹簧模型进行接头抗弯刚度对整环管片结构内力影响的研究.结果表明:该隧道管片接头抗弯刚度的取值范围为50～700MN·m·rad-1,在相同轴力条件下,接头抗弯刚度会随接头弯矩的增加降低1个数量级左右;在相同接头弯矩条件下,接头抗弯刚度随轴力的增加而增大;接头抗弯刚度对管片轴力分布的影响微弱,对管片弯矩的影响显著;随接头抗弯刚度的增大,整环管片的弯矩分布趋于均匀;在抗弯刚度取值范围内,极值弯矩相差最大达80％左右,极值轴力最大减小5％左右,变形最大减小20％左右;基于接头抗弯刚度-弯矩-轴力的非线性关系改进的梁-弹簧模型,更能体现接头对整环管片受力的影响,也更适用于大断面盾构隧道管片内力的计算.     

实施人化管理构建和谐校园

人化管理以召唤学生主体意识,促进学生个体生成,构建校园的和谐氛围为终极目标。文章针对在构建和谐校园中,实施人化管理的重要意义和实践方法作了一些探索和研究。     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Orchestration of driving simulator scenarios based on dynamic actor preparation and automated action planning

In driving simulation, a scenario includes definitions of the road environment, the traffic situation, simulated vehicles’ interactions with the participant’s vehicle and measurements that need to be collected. The scenarios need to be designed in such a way that the research questions to be studied can be answered, which commonly imply exposing the participant for a couple of predefined specific situations that has to be both realistic and repeatable. This article presents an integrated algorithm based on Dynamic Actor Preparation and Automated Action Planning to control autonomous simulated vehicles in the simulation in order to generate predefined situations. This algorithm is thus able to plan driving actions for autonomous vehicles based on specific tasks with relevant contextual information as well as handling longitudinal transportation of simulated vehicles based on the contextual information in an automated manner. The conducted experiment shows that the algorithm is able to guarantee repeatability under autonomous traffic flow. The presented algorithm can benefit not only the driving simulation community, but also relevant areas, such as autonomous vehicle and in-vehicle device design by providing them with an algorithm for target pursue and driving task accomplishment, which can be used to design a human-vehicle cooperation system in the coming era of autonomous driving.     

Auction-based tolling systems in a connected and automated vehicles environment: Public opinion and implications for toll revenue and capacity utilization

Autonomous and connected vehicles are expected to enable new tolling mechanisms, such as auction-based tolls, for allocating the limited roadway capacity. This research examines the public perception of futuristic auction-based tolling systems, with a focus on the public acceptance of such systems over current tolling practices on highways (e.g., dynamic and fixed tolling methodologies). Through a stated-preference survey, responses from 159 road-users residing in Virginia are elicited to understand route choice behavior under a descending price auction implemented on a hypothetical two-route network. Analysis of the survey data shows that there is no outright rejection of the presented auction-based tolling among those who are familiar with the current tolling methods. While males strongly support the new method, no clear pattern emerges among other demographic variables such as income and education level, and age. While high income respondents and regular commuters are more likely to pay higher tolls, no statistical significance between different genders, age groups, household sizes, and education levels is found. Based on the modeling results and the hypothetical road network, it is found that descending price tolling method yields higher average toll rates, and generates at least 70% more revenue when travel time saving is 30 min, and improves capacity utilization of the toll road significantly compared to fixed tolls.