太阳能游船光伏逆变器控制系统EMC设计

从船舶环境和光伏逆变器的基本原理和功能出发,分别对太阳能游船EMC干扰源和干扰路径进行分析,通过信号滤波与保护、工艺设计和试验测试,实现高可靠性的太阳能游船光伏逆变器控制系统研究和设计,为太阳能游船的光伏逆变器控制系统研究提供基本EMC设计思路与实现技巧。     

Mental models of driving and speed: biases,choices and reality

This paper provides a review of research performed by Svenson with colleagues and others work on mental models and their practical implications. Mental models describe how people perceive and think about the world including covariances and relationships between different variables, such as driving speed and time. Research on mental models has detected the time-saving bias [Svenson, O. (1970). A functional measurement approach to intuitive estimation as exemplified by estimated time savings. Journal of Experimental Psychology, 86, 204–210]. It means that drivers relatively overestimate the time that can be saved by increasing speed from an already high speed, for example, 90–130?km/h, and underestimate the time that can be saved by increasing speed from a low speed, for example, 30–45?km/h. In congruence with this finding, mean speed judgments and perceptions of mean speeds are also biased and higher speeds given too much weight and low speeds too little weight in comparison with objective reality. Replacing or adding a new speedometer in the car showing min per km eliminated or weakened the time-saving bias. Information about braking distances at different speeds did not improve overoptimistic judgments of braking capacity, but information about collision speed with an object suddenly appearing on the road did improve judgments of braking capacity. This is relevant to drivers, politicians and traffic regulators.     

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.     

基于虚拟化云技术的路局中心地震预警监测系统方案及联动研究

通过研究铁路地震预警监测系统现状和建设趋势,从资源共享、重复性建设、地震联动触发信号系统停车、牵引供电系统断电等多角度分析存在的问题,结合实际需求,提出铁路局中心系统采用虚拟化云技术的建设思路,并提出地震预警监测系统通过路局中心系统与信号RBC、牵引供电中心接口的联动触发策略。文中论述了采用虚拟化云技术搭建的地震预警监测铁路局中心系统功能、系统构成、硬件配置,从而解决各条铁路接入路局中心增加大量服务器等所带来的资源浪费严重、重复性建设等问题,为建设项目节省投资;阐述了通过路局中心系统与信号RBC、牵引供电中心接口的联动触发方案,为安全提供保障的同时尽可能节省建设投资和维护成本,更好地为铁路安全保驾护航。     

道路环境对交通安全的影响及对策

交通安全,涉及到人、车以及道路和环境等很多因素。近年来,因为各种原因使得有关单位以及人员将更多的将精力放在人、车、道路这几个因素上,对道路交通环境没有过多的考虑和研究。深入研究道路交通环境,有利于道路交通的安全,文章通过对其的研究和分析,得出有关道路交通环境对交通安全的影响和解决措施,对于防止道路交通安全事故具有重要意义。同时为人们的生命财产的安全提供保障、对构建社会主义和谐社会具有很大帮助。     

铁路沿线城市空间物业开发研究——以宝鸡市南客站核心区站前广场工程为例

为了提升铁路沿线城市空间物业开发的设计手法,结合宝鸡市南客站核心区站前广场工程的设计实践,从系统性设计观、工程性质解析、消防设计思路、空间建构方法、无缝接驳、技术要素等方面进行研究分析,展示将铁路与城市系统进行一体化设计、利用自然资源解决消防和投资问题、平层空间中对多种交通体系的有机组织、不同坐标和高程系统背景下分区域构建柱网、各板块交接处的问题解决等技术成果,总结出同类型建筑的设计思路,力求为该领域的建筑设计发展提供有益的借鉴。     

Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

Socially optimal electric driving range of plug-in hybrid electric vehicles

This study determines the optimal electric driving range of plug-in hybrid electric vehicles (PHEVs) that minimizes the daily cost borne by the society when using this technology. An optimization framework is developed and applied to datasets representing the US market. Results indicate that the optimal range is 16 miles with an average social cost of $3.19 per day when exclusively charging at home, compared to $3.27 per day of driving a conventional vehicle. The optimal range is found to be sensitive to the cost of battery packs and the price of gasoline. When workplace charging is available, the optimal electric driving range surprisingly increases from 16 to 22 miles, as larger batteries would allow drivers to better take advantage of the charging opportunities to achieve longer electrified travel distances, yielding social cost savings. If workplace charging is available, the optimal density is to deploy a workplace charger for every 3.66 vehicles. Moreover, the diversification of the battery size, i.e., introducing a pair and triple of electric driving ranges to the market, could further decrease the average societal cost per PHEV by 7.45% and 11.5% respectively.     

面向智能车辆的现役道路设施行驶适应性研究综述

为了总结面向智能车辆的现役道路设施行驶适应性，即现役道路基础设施承载智能车辆行驶的适宜程度，阐述自主智能驾驶定义与驾驶自动化等级分类，在此基础上剖析不同等级间的人机功能差异，并分别从感知层、感知-决策层、决策-控制层探讨与道路设计要素相关联的人机功能差异，通过归纳总结智能车辆与道路几何要素、路面性能及其他道路要素(如道路标线)的相互作用机制研究，从道路工程角度及其他道路要素方面回顾该领域的研究现状，指出存在的问题和未来发展方向。研究结果表明：相比传统车辆，配置高等级自动驾驶系统的智能车辆对现役道路设施行驶适应性最高，主动安全系统次之，而驾驶辅助及有条件自动驾驶系统适应性不足。而目前研究主要问题包括：难以归纳、标定不同驾驶自动化等级间的人机功能差异及其对于道路设计参数的需求设计值；测试道路场景条件过于理想，考虑的驾驶自动化等级单一，试验规模和样本有限；道路几何、路面性能以及道路标志、标线等道路要素与智能车辆间的相互作用机制研究不足，缺乏与不同道路场景相匹配的智能车辆驾驶特征数据的获取手段。因此建议：重视并推动与道路设计要素相关联的关键人机功能差异指标信息共享；联合高保真且可交互的道路场景、高精度感知传感器物理模型、车辆动力学模型及微观交通流模型，利用测试场景自动化生成、极限工况场景搜寻与泛化等技术开展智能驾驶虚拟测试，突破现有研究的深度和广度；探索反映不同等级智能车辆的道路行驶适应性特征指标与评价标准，精准、有效地评估预测复杂道路场景及不利道路条件下的行驶适应性。