浅谈青藏线转辙设备的养护与维修

本文根据CTS2轨枕式转辙机本身的特点以及青藏铁路的管理模式，从养护、维修的角度，简要说明了CTS2轨枕式转辙机需要的养护工作量、故障处理方法、维修特点及在施工中要注意的问题。     

ZYJ7型电动液压转辙机控制电路故障判断与处理

根据ZYJ7型电动液压转辙机启动、表示电路原理,结合日常处理故障经验,从室内到室外阐述了判断ZYJ7型电动液压转辙机启动电路、表示电路各种故障方法,为我们日常处理ZYJ7型电动液压转辙机启动电路、表示电路故障提供了准确、快捷的处理方法。     

智能车辆机器视觉发展近况

简要回顾了机器视觉的早期发展，从简单的特定场合应用到模拟人眼的复杂系统设计，介绍了机器视觉产品在智能汽车上的应用情况，分析了世界各国在车用机器视觉技术领域研究开发情况以及未来发展趋势。     

基于视觉的前方车辆探测技术研究方法综述

对国内外关于车道上本车前方车辆检测方法进行了综述。根据探测车辆所采用的传感器不同,分别对采用单目视觉、双目视觉、视觉与其他传感器融合以及非视觉传感器的几种探测方法进行了比较与分析。同时,针对每种探测方法,进一步阐述了目前车辆识别的一些具体算法。最后,指出了每种方法存在的优点和一些不足。     

载人潜器人因工程研究

对载人潜器人因工程的研究现状、研究范畴、技术手段和发展趋势进行梳理和总结,旨在为指导载人潜器设计总体集成优化、提高潜器综合效能、节省全寿命周期费用及缩减潜器人员编制提供参考。     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.     

Modeling time-of-day car use behavior: A Bayesian network approach

In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.     

隧道病害维修保养技术方案设计

为保障铁路隧道安全运营,在分析国内外车辆技术、作业平台技术和检测技术现状的基础上,从车辆技术、作业平台技术、检测技术和作业模式4方面,提出隧道病害维修保养技术方案设计思路,设计一套整合隧道病害维修保养相关技术装备及检测模式方案。该方案采用内燃电传动及蓄电池电传动集成的混合动力传动系统,搭载三作业平台,配备探地雷达系统、手持雷达、音频检测系统和高速成像系统,采用智能巡检、机械复检和人工专检的检测作业模式,是适应我国铁路发展的隧道病害维修保养可行方案。     

Autonomous vehicle perception: The technology of today and tomorrow

Perception system design is a vital step in the development of an autonomous vehicle (AV). With the vast selection of available off-the-shelf schemes and seemingly endless options of sensor systems implemented in research and commercial vehicles, it can be difficult to identify the optimal system for one’s AV application. This article presents a comprehensive review of the state-of-the-art AV perception technology available today. It provides up-to-date information about the advantages, disadvantages, limits, and ideal applications of specific AV sensors; the most prevalent sensors in current research and commercial AVs; autonomous features currently on the market; and localization and mapping methods currently implemented in AV research. This information is useful for newcomers to the AV field to gain a greater understanding of the current AV solution landscape and to guide experienced researchers towards research areas requiring further development. Furthermore, this paper highlights future research areas and draws conclusions about the most effective methods for AV perception and its effect on localization and mapping. Topics discussed in the Perception and Automotive Sensors section focus on the sensors themselves, whereas topics discussed in the Localization and Mapping section focus on how the vehicle perceives where it is on the road, providing context for the use of the automotive sensors. By improving on current state-of-the-art perception systems, AVs will become more robust, reliable, safe, and accessible, ultimately providing greater efficiency, mobility, and safety benefits to the public.