探索新能源汽车充电设施的电气设计

现如今,新能源电动汽车充电装置电气设计,得要顺应现代化实际需求与发展趋势。在后期发展阶段之中,新能源汽车会引领着整个汽车行业的发展,当然也可以凸显出节能减排、绿色出行的优势。因此在新能源项目发展阶段之中,针对新能源汽车充电设施实施电气设计至关重要。鉴于此,本文主要分析新能源汽车充电设施的电气设计。     

中国智慧公交示范现状分析及展望

智慧公交示范属于智能网联示范中的特色应用场景,也是智能网联开放道路示范的先行力量。本文梳理了我国现有典型智慧公交示范情况,分析其共性特点及存在问题,并对未来发展进行了展望。旨在从智慧公交视角窥见整体智能网联汽车产业发展进程,促进智能网联汽车从封闭走向开放、从示范应用走向商业化推广。     

智能汽车的人机共驾技术研究现状和发展趋势

智能汽车的人机共驾技术(HM IoIV)是解决其智能化级别难以快速跨越至高度自动化水平的有效过渡手段.HMIoIV涉及了L0～L3级别的智能汽车的多种自动化技术,包括先进辅助驾驶系统.针对当前国内外智能汽车人机共驾技术的研究现状,对其概念、结构和研究内容进行总结,根据独立驾驶人参与的数量和驾驶操作方参与的数量将现有的人...     

铁路重载货车转向架技术应用探究

铁路重载货车转向架为铁路重载运输提供保障.由于铁路重载货车的重载质量不断增加,运行的速度越来越快速,从而造成了轮轨的损坏,这就需要加强对转向架技术的深入研究.对我国铁路重载货车转向架技术发展的历程进行阐述,详细分析了铁路重载货车转向架技术的应用,并对铁路重载货车转向架的发展趋势进行阐述.     

高速公路可变限速中大车混入因素研究

制定限速是防止超速的一项重要措施。文中介绍了可变限速系统的主要组成部分,工作原理以及应用情况。以京津塘高速公路为例,分析了大车的时间分布规律,对车流速度以及速度差的影响。介绍了基于大车比例的可变限速值确定的流程及限速数值,建立起大车比例与运行速度的关系。可变限速的实时性可以提供给驾驶员更准确的路况信息。     

新形势下我国新能源汽车政策现状与发展趋势研究

汽车产业作为我国重要的经济支柱产业,在我国的经济发展和国家发展中发挥了重要的作用,为了寻求产业发展和能源消耗之间的平衡,新能源汽车的概念应时而生。特别是在当前我国各方面建设都进入新常态的形势下,推进新能源汽车的进一步发展,是现在我们必须要认清的一个很迫切的问题,也是一个很现实的问题。     

弹性需求下高速公路超限补偿费率优化模型

为了准确刻画超限需求弹性对补偿费率的影响,从用户和系统的角度分别对超限运输的收益和成本进行分析和建模,构造超限运输弹性需求函数,反映超限运输需求量与其运输效益之间的变化关系,将超限运输业者运输行为的选择归结为弹性需求下的用户均衡配流问题,进而利用高速公路管理者与超限运输业者之间的Stackelberg博弈关系,建立了基于弹性需求的高速公路超限补偿费率的双层规划优化模型,并设计了基于模拟退火算法求解的优化算法。结果表明：模型能较好地优化超限补偿费率,使之对超限运输业者进行合理补偿收费和适度惩罚,有效遏制超限运输,从而产生更大的社会与经济效益。     

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.