Driving cycle prediction model based on bus route features

Bus fuel economy is deeply influenced by the driving cycles, which vary for different route conditions. Buses optimized for a standard driving cycle are not necessarily suitable for actual driving conditions, and, therefore, it is critical to predict the driving cycles based on the route conditions. To conveniently predict representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route features, which supports bus optimization. The relations between 27 inter-station characteristics and bus fuel economy were analyzed. According to the analysis, five inter-station route characteristics were abstracted to represent the bus route features, and four inter-station driving characteristics were abstracted to represent the driving cycle features between bus stations. Inter-station driving characteristic equations were established based on the multiple linear regression, reflecting the linear relationships between the five inter-station route characteristics and the four inter-station driving characteristics. Using kinematic segment classification, a basic driving cycle database was established, including 4704 different transmission matrices. Based on the inter-station driving characteristic equations and the basic driving cycle database, the driving cycle prediction model was developed, generating drive cycles by the iterative Markov chain for the assigned bus lines. The model was finally validated by more than 2 years of acquired data. The experimental results show that the predicted driving cycle is consistent with the historical average velocity profile, and the prediction similarity is 78.69%. The proposed model can be an effective way for the driving cycle prediction of bus routes.     

船舶甲板智能抛丸机器人设计

为解决在船舶外场涂装阶段除锈和拉毛施工效率低、质量不稳定、环境污染严重等问题,设计一款用于船舶甲板的智能抛丸机器人。简介该型机器人系统组成,阐述其抛丸分系统、除尘分系统和越障辅助机构的硬件设计及其软件设计,并设计手动遥控和自主导引操作方式。实船测试结果表明,该型机器人可满足船舶甲板除锈清理的工作要求。     

On the variance of recurrent traffic flow for statistical traffic assignment

This paper generalizes and extends classical traffic assignment models to characterize the statistical features of Origin-Destination (O-D) demands, link/path flow and link/path costs, all of which vary from day to day. The generalized statistical traffic assignment (GESTA) model has a clear multi-level variance structure. Flow variance is analytically decomposed into three sources, O-D demands, route choices and measurement errors. Consequently, optimal decisions on roadway design, maintenance, operations and planning can be made using estimated probability distributions of link/path flow and system performance. The statistical equilibrium in GESTA is mathematically defined. Its multi-level statistical structure well fits large-scale data mining techniques. The embedded route choice model is consistent with the settings of O-D demands considering link costs that vary from day to day. We propose a Method of Successive Averages (MSA) based solution algorithm to solve for GESTA. Its convergence and computational complexity are analyzed. Three example networks including a large-scale network are solved to provide insights for decision making and to demonstrate computational efficiency.     

A traffic-condition-based route guidance strategy for a single destination road network

Most of existing route guidance strategies achieves user optimal equilibrium by comparing travel time. Measuring travel time, however, might be uneasy on an urban road network. To contend with the issue, the paper mainly considers easily obtained inflow and outflow of a link and road capacity as input, and proposes a route guidance strategy for a single destination road network based on the determination of free-flow or congested conditions on alternative routes. An extended strategy for a complex network and a feedback approximation for avoiding forecast are further explored. Weaknesses of the strategy are also explicitly analyzed. To test the strategy, simulation investigations are conducted on two networks with multiple parallel routes. The results indicate that the strategy is able to provide stable splitting rates and to approximate user optimal equilibrium in different conditions, in particular when traffic demand is high. This strategy has potential to be applied in an urban road network due to its simplicity and easily obtained input data. The strategy is also applicable for single destination if some alternatives and similar routes are available.     

某型号制导电子箱的检测系统设计*

为解决现有导弹检测设备存在的缺陷,设计了一种模块化、通用化、智能化和标准化的综合检测修理平台。论文介绍了系统的硬件组成以及基于Labwindows／CVI的软件开发。通过部队实践证明,该系统具有重大军事效益和经济效益和广泛的运用前景。     

带落角约束的变结构三维末制导律设计

分析导弹与目标水面舰艇之间三维空间的相对运动特性,并在此基础上进行带落角约束的变结构制导律设计。该制导律设计中,针对一次设计时切换面导数形式过于复杂的情况,作出变换进行二次设计,极大地简化模型;另外,由于目标信息难以获取,故将其视为扰动;最后通过数值仿真验证了所设计制导律的可行性和有效性,具有一定的工程应用价值。     

总装车间继电器安装自动化的应用

文章介绍了一种车载线束继电器安装的自动化设备,设备采用Dalta并联机器人抓取继电器进行安装,继电器上料由另一台Dalta并联机器人和视觉引导完成。继电器安装过程中,力和位移的数据被实时监控和保存,单颗继电器安装节拍满足≤1.1s,单条线束作业节拍≤45s,满足汽车总装生产线节拍要求。     

山钢莱芜分公司专用铁路编组站改造方案研究

专用铁路编组站改造是山东钢铁股份有限公司莱芜分公司新旧动能转换项目的控制工程之一,对于铁路运输组织、站场设施管理工作的提升具有重要意义.在阐述既有莱钢编组站站场设施和运输组织现状的基础上,结合钢铁新旧动能转换工程规划,分析莱钢编组站目前存在的无贯通正线、到发线有效长不足、卸车线有效长不足、站坪坡度超限等问题,提出莱钢编...     

舰载机起降指导技术研究现状及发展趋势

介绍了航空母舰舰载机起降指导技术的研究现状,论述了基于纵摇运动的舰载机起飞指导方珐,及光学助降系统等着舰指导方式的特点、原理．介绍了全天候自动着舰系统以及着舰决策支持工具,讨论了起降指导系统的未来研究方向．