西安地铁2号线车辆公路运输实施方案

地铁车辆属超长、超大货物,公路运输时需借助长大汽车且通过市区进入车辆段。因此运输组织及运输安全尤为重要。就地铁车辆的公路运输涉及到的几个因素进行了分析,提出了安全可靠的运输方案。通过批量车公路运输的实施和验证,给地铁车辆公路运输方式提供了有益的借鉴。     

跨坐式单轨车辆国产制动系统研制与应用

根据重庆轨道交通二号线车辆制动系统的要求,研制出国产制动系统并成功应用,填补了国内制动产品在跨坐式单轨交通车辆领域的空白。     

长春轻轨三期工程车辆特点

介绍长春轻轨三期工程项目采用的现代有轨电车的基本技术参数、系统组成和系统配置,分析车辆的技术特点,阐明可供借鉴的技术成果,为有轨电车项目建设提供参考。     

地铁柔性接触网线岔检调标准的制定与应用

根据以往运行经验,结合西安地铁2号线的实际情况,从支柱定位、线岔交叉点、始触区、接触线高度、线岔定位拉出值等方面,对柔性接触网线岔的检调标准进行深入研究、分析并加以明确。将所定标准实际应用在西安地铁渭河车辆段接触网的建设中,顺利通过了接触网的冷滑、热滑试验及实际运行的考验。同时,将所定部分标准与国铁普速接触网线岔检调标准进行对比,以供有关接触网生产和技术人员参考。     

不同动力电池新能源货运配送车辆节能减排绩效评价研究

为研究新能源货运车辆装配不同动力电池对节能减排的影响,选取某款新能源货运配送车辆为研究对象,利用GaBi软件建立了3种常用动力电池的整车生命周期评价模型,从原材料获取、生产制造、装配、运行使用、报废回收5个阶段进行节能减排差异分析,并对全球变暖潜值 （Global Warming Potential,GWP） 等环境影响类型进行归一化处理和量化计算处理。结果表明,分别装配3种电池整车的化石能源消耗以煤炭为主、环境排放以CO2为主;纯电动汽车的能源消耗、污染物排放集中在运行使用阶段;综合比较,装配了三元锂电池的整车,其全生命周期节能减排效果最佳,装配了锰酸锂电池的整车则表现最差。加大清洁能源的使用力度、减少用于电力生产的化石能源消耗、提高回收率等措施,可以显著减少污染物排放。     

人工智能在车辆自动驾驶中的应用

提出一种新的基于人工智能的感知 计划 动作agent结构实现智能车辆自动驾驶的方案。首先通过描述该结构的原理说明该结构可以解决自动驾驶中存在的一些问题,接着通过建立自动驾驶知识库阐述如何具体实现自动驾驶,最后通过仿真实验验证该方法能够为智能车辆实现自动或辅助驾驶提供一种非常有效的机制。     

电动汽车充电桩安全管理研究

随着国家对环境保护和能源节约的重视以及新能源政策的实施,电动汽车行业迎来了快速发展。充电基础设施的建设,是加快电动汽车推广的重要需要。电动汽车充电基础设施建设和运营业务发展的机会也极大,随之而来的安全管理工作要求也越来越高。本文依据充电桩建设和运营的特点,剖析其中面临的安全风险,并提出加强安全管理工作的措施,为充电桩企业安全管理运营提供参考和借鉴。     

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.     

An improved cellular automaton with axis information for microscopic traffic simulation

Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.