公路货运信息服务业运营模式及发展对策研究

在分析和界定公路货运信息服务业内涵的基础上，研究了公路货运信息服务业4种运营模式（个体信息服务中介模式、场站信息服务中心模式、区域信息服务平台模式和公共信息服务网络模式），并基于公路货运信息服务业发展现状及向现代物流发展的趋势，提出了公路货运信息服务业向现代物流体系发展的基本思路和策略。     

运行环境对稀油润滑牵引电机轴承的影响及分析

某型牵引电机轴承采用稀油润滑,在运行中传动端轴承部分出现不同程度的异常磨损,甚至发生固死故障。文章通过解体电机故障轴承并对为轴承提供润滑油的齿轮箱油取样分析,找出了轴承故障与运行环境的相关性,并提出了改善措施。     

崩塌滑坡堵江堰塞湖灾害链铁路减灾选线策略

青藏高原南缘是崩塌滑坡堵江形成堰塞湖灾害链的高风险区,而我国铁路缺乏应对堰塞湖灾害的经验。铁路灾后改建工程线路优化设计将产生直接减灾效益,而新建铁路在选线阶段就采取一些主动减灾策略,也是风险调控的重要手段。为此,以中巴经济走廊中拟建哈维连至喀什铁路Attabad堰塞湖段为研究对象,根据堰塞湖灾害特点,通过将改建工程分段设计,并对不同改建线路方案进行技术经济指标比较,完成该段改建线路设计。基于上述工作,提出以有利地形控制溢流口开挖深度、宜尽量利用既有工程、在离开湖区后集中展线尽快与既有线联接、有条件时可提高限制坡度等灾后绕湖铁路选线设计要点与高位选线、酌情预留提高限坡措施的条件、尽量不跨河等新建铁路减灾选线设计策略,希望为铁路应对崩塌滑坡堵江堰塞湖灾害链提供参考。     

某铁路线运转值班人员工作负荷调查报告

为了解铁路运转值班人员工作负荷情况,为铁路运输的合理倒班、合理用工提供依据,对某铁路线的117名运转值班人员做了工作前后的生理疲劳和健康指标改变调查,评价其工作期间身体和生理健康水平,工作前后的生理疲劳、工作负荷情况。采用问询调查表调查117名运转值班人员的感觉疲劳情况及对工作班制的看法。调查结果表明,该线铁路的117名运转值班人员工作前后的生理疲劳指标改变、心理健康指标改变三班制和四班制差异显著,班制、工作单调和责任大是主要原因。提示改革班制、开展健康教育和干预是保证运转值班人员身体健康的主要手段。     

编组站系统能力协调度的计算分析

以编组站实际作业过程为研究背景,基于编组站车流到达的不均衡性,将每一时段[ti-1,ti)的车流输入强度划分为3种不同的到达状态,结合对车流状态及编组站各系统能力的分析,得出编组站系统作业能力的协调度计算公式,最后,根据某编组站的实际车流量,计算出该编组站车流密集到达状态下的系统协调度。实例计算分析表明:所得出的协调度计算结果能够反映出编组站系统能力协调的薄弱环节,为提高编组站整体作业能力提供了一种新的方法。     

高速铁路营业线新建车站施工安全技术研究

武广英德西站是我国第一个高铁营业线的新建车站工程,安全风险大、施工难度高。详细介绍了英德西站施工中有关安全方面的一些技术措施和安全管理经验,以供类似工程参考。     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.     

Competitiveness of container terminal operating companies in South Korea and the industry–university–government network

Burgeoning container port facilities have fostered intensified competition among container terminal operating companies (CTOCs). However, despite research into their survival strategies which identified antecedents of competitiveness including hard factors such as facilities, available cargo and cargo processing ability, softer factors spanning human resource management, networks and strategic alliances with universities and government agencies in industry–university–government (I–U–G) networks have been overlooked. This study aims to examine both hard and softer antecedents of competitiveness as perceived by 152 professionals in South Korean CTOCs; empirical relationships among these antecedents, I–U–G networks, and competitiveness itself; and the significance of the I–U–G network in establishing and improving competitiveness. Posited antecedents of competitiveness included human resources, facilities, service quality, customer orientation, reputation, and government support policy as independent variables; the I–U–G network as a moderating variable; and competitiveness as a dependent variable. Empirical structural relationships revealed that excepting government support policy, each variable significantly affected CTOC competitiveness. Further, the I–U–G network moderated the relationships between the antecedents of competitiveness and competitiveness. Because an effective I–U–G network was pivotal in controlling CTOC competitiveness, improved competitiveness requires not only differentiation of human resources, facilities, service quality, customer orientation, and reputation factors but also I–U–G network developments.     

共享自动驾驶汽车经营策略优化分析

研究共享自动驾驶汽车(SAV)与普通汽车共存背景下，SAV公司如何根据运营目标优化经营策略并影响通勤者出行方式选择. 假设高速公路上存在一定数量的独驾通勤者，无车通勤者在SAV和地铁之间进行权衡. 分析固定需求和弹性需求下，SAV公司追求系统总成本最小或系统净收益最大和利润最大时的最优经营策略，即SAV票价和容量，进而得到均衡时模式划分情况，SAV最优发车数，系统总成本或系统净收益，以及公司利润等指标. 算例对均衡结果进一步验证发现，SAV公司垄断经营会收取较高的票价，提供容量较小的车型. 在系统最优情形下，SAV公司无法获得正利润，需要政府补贴运营.     

Generating lane-based intersection maps from crowdsourcing big trace data

Lane-based road information plays a critical role in transportation systems, a lane-based intersection map is the most important component in a detailed road map of the transportation infrastructure. Researchers have developed various algorithms to detect the spatial layout of intersections based on sensor data such as high-definition images/videos, laser point cloud data, and GPS traces, which can recognize intersections and road segments; however, most approaches do not automatically generate Lane-based Intersection Maps (LIMs). The objective of our study is to generate LIMs automatically from crowdsourced big trace data using a multi-hierarchy feature extraction strategy. The LIM automatic generation method proposed in this paper consists of the initial recognition of road intersections, intersection layout detection, and lane-based intersection map-generation. The initial recognition process identifies intersection and non-intersection areas using spatial clustering algorithms based on the similarity of angle and distance. The intersection layout is composed of exit and entry points, obtained by combining trajectory integration algorithms and turn rules at road intersections. The LIM generation step is finally derived from the intersection layout detection results and lane-based road information, based on geometric matching algorithms. The effectiveness of our proposed LIM generation method is demonstrated using crowdsourced vehicle traces. Additional comparisons and analysis are also conducted to confirm recognition results. Experiments show that the proposed method saves time and facilitates LIM refinement from crowdsourced traces more efficiently than methods based on other types of sensor data.