上海市轨道交通5号线信号系统控制网络的研究与探讨

上海轨道交通5号线信号系统采用了PROFIBUS总线技术。从PROFIBUS的协议结构、传输技术、总线存取协议等几个方面,讨论该技术在上海轨道交通5号线信号系统控制网络中的具体应用,并通过安全性、可靠性分析,阐明采用PROFIBUS现场总线技术的意义。     

庞巴迪将与意大利高科技公司合作开发新型超高速列车

<正>庞巴迪运输集团和芬美卡尼卡股份有限公司旗下主营铁路设备的子公司AnsaldoBreda于4月1日在柏林签署了关于共同开发、投标以及生产新型超高速列车的合作协议。这种超高速列车时速将达到300公里/小时以上,并且能够减少现有此类列车的一系列弊端。借助庞巴迪以及芬美卡尼卡公司最新研发的领先技术成果,包括改进运营效率性及安全性,     

动态

<正>《海峡两岸空运协议》等四项协议签署海协会会长陈云林与海基会董事长江丙坤11月4日下午在台北签署了《海峡两岸空运协议》、《海峡两岸海运协议》、《海峡两岸邮政协议》和《海峡两岸食品安全协议》四项协议。这宣告两岸同胞盼望已     

应急物流基础设施复杂网络抗毁能力仿真研究

基于复杂网络理论,文章首先选取出最大连通子图相对大小与全网效能两个指标进行应急物流基础设施复杂网络抗毁能力的评价;接着制定针对网络节点的随机性攻击和选择性攻击的攻击策略;然后以北京市"十二五"期间物流业发展规划的物流基础设施复杂网络为例,绘制出网络拓扑结构,确定该网络具有小世界效应和无标度特征;然后通过仿真软件MATLAB,对该网络进行针对节点的两种攻击仿真,计算出最大连通子图相对大小及全网效能,结果表明该类型网络对高节点度的选择性攻击抗毁能力低;最后对北京市未来物流基础设施发展给予了建议。     

浅谈MPLS中LDP协议工作原理

文主要介MPLS(Mulfiprotocol Label Switching)LDP(Label Distribution Protocol)的协议工作原理,包括LDP协议报文组成、LDP标签管理、LDP消息,最后对LDP发现机制、会话建立过程、LSP建立过程进行了简单分析.     

星马广发合作

近日,星马集团与广发银行签订银企战略合作协议,标志着双方正式建立起全面战略合作伙伴关系。星马集团董事长刘汉如,广发银行副行长宗乐新分别致词并代表双方在协议书上签字。根据合作协议的约定,双方未来将在汽车按揭、厂商银、资金结算、现金管理和投资银行等业务领域开展深入合作。在此次《银企战略合作协议》的框架下,随着     

世界机场排行旅客吞吐量（至2011年2月）

5月10日,交通运输部部长李盛霖、铁道部部长盛光祖在北京签署《关于共同推进铁水联运发展合作协议》（简称《合作协议》）。联合作协议》明确,两部将在六个方面深化铁水联运合作与交流。一是加强和完善铁水联运发展规划,合理布局联运通道和网络。     

运管

部与江苏签署建成绿色低碳示范省协议 2013年6月18日,交通运输部副部长何建中和江苏省副省长史和平在无锡分别代表交通运输部、江苏省人民政府签署《共同推进江苏省绿色循环低碳交通运输发展框架协议》（简称《框架协议》）,提2020年率先全面建成绿色循环低碳交通运输示范省份。     

国产客车CAN总线全面升级 海格开启安全智能新篇章

<正>CAN总线是什么?CAN是控制器局域网络(Controller Area Network)的简称,是国际上应用最广泛的现场总线之一。在北美和西欧,CAN总线协议已经成为汽车计算机控制系统和嵌入式工业控制局域网的标准总线,并且拥有以CAN为底层协议专为大型货车和重工机械车辆设计的J1939协议。在中国,海格客车全车系标配CAN总线技术,开创了国内客车全系批量应用的先河,开启了中国客车安全、智能又一新篇章。     

宁波市轨道交通管线迁移管理模式初探

管线迁移是轨道交通建设顺利开工的前期工作之一。基于轨道交通管线迁移的特点，介绍了委托代理、集中归口和分工协作等3种管理模式，初步探索了宁波市轨道交通管线迁移工作模式和程序，明确“谁的管线谁负责”的原则，统一管线迁移设计，建立了“框架协议＋分期任务书”的协议模式。     

A three-stage evacuation decision-making and behavior model for the onset of an attack

Pedestrian behavior models have successfully reproduced human movement in many situations. However, few studies focus on modeling human behavior in the context of terrorist attacks. Terrorist attacks commonly occur in crowded public areas and result in a large number of casualties. This paper proposes a three-stage model to reproduce a series of complex behaviors and decision-making processes at the onset of an attack, when pedestrians generally do not have clear targets and have to deal with fuzzy information from the attack. The first stage of the model builds a Bayesian belief network to represent the pedestrians’ initial judgment of the threat and their evacuation decisions. The second stage focuses on pedestrians’ global assessment of the situation through an analogy with diffusion processes. The third stage uses a cost function to reproduce the trade-offs of distance, safety, and emotional impact when considering a path to take. The model is validated using a video from the November 2015 Paris attack. The behavioral characteristics and trajectories of three pedestrians extracted from the video are reproduced by the simulation results based on the model. The research can be used to set rules when performing risk analysis and strategic defensive resource allocation of terrorist attacks using agent-based simulation methods.     

Testing a Framework for the Efficiency Assessment of Road Safety Measures

Abstract

The objective of this research is to develop and test a framework for efficiency assessment of road safety measures and evaluate its use in decision‐making. An exhaustive review of standard methodologies and practices related to cost‐effectiveness and cost–benefit analyses is carried out for that purpose. Moreover, a number of case studies are performed, concerning the efficiency assessment of various road safety measures in different countries, covering different types of road safety measures (user‐, vehicle‐ or infrastructure‐oriented, policy or enforcement, etc.), ranging from national to local levels of implementation and including both ex ante and ex post evaluations. From the results conclusions are drawn on the efficiency of different road safety measures and the related determinants. Furthermore, the case studies reveal a number of methodology and data issues for which further research is required. The procedures and barriers involved in the use of efficiency assessment techniques at different levels of decision‐making are also highlighted by means of feedback received during and after the various case studies. On the basis of these results, a framework for the promotion, implementation and evaluation of efficiency assessment in road safety decision‐making is proposed. A particular set of recommendations is also presented regarding the treatment of barriers (fundamental, institutional or technical) within the efficiency assessment itself and the related decision‐making process.     

Multi‐criteria analysis for evaluating the impacts of intelligent speed adaptation

Road safety is a policy priority due to the high casualties and costs associated with road accidents. Since speed is a major cause of road accidents, in‐vehicle speed limiters or Intelligent Speed Adaptation (ISA), seems a promising solution. ISA implementation, however, is hindered by large uncertainties, for example about the impacts of ISA, the way users might respond to ISA, and the relationship between speed and accidents. Traditional Multi‐Criteria Analysis (MCA) has limitations in handling these uncertainties. We present an MCA approach based on exploratory modeling, which uses computational experiments to explore the multiple outcomes of ISA policies (safety, emissions, throughput, and cost) across a range of future demand scenarios, functional relationships for performance criteria, and user responses to ISA. As an illustration, by testing the impacts of different ISA penetration levels on two driver groups, we show that when compliance with ISA is expected to be low, a policy aimed only at novice drivers outperforms other ISA policies on safety improvement.     

Modeling a rail transit alignment considering different objectives

An optimization model for station locations for an on-ground rail transit line is developed using different objective functions of demand and cost as both influence the planning of a rail transit alignment. A microscopic analysis is performed to develop a rail transit alignment in a given corridor considering a many-to-one travel demand pattern. A variable demand case is considered as it replicates a realistic scenario for planning a rail transit line. A Genetic Algorithm (GA) based on a Geographical Information System (GIS) database is developed to optimize the station locations for a rail transit alignment. The first objective is to minimize the total system cost per person, which is a function of user cost, operator cost, and location cost. The second objective is to maximize the ridership or the service coverage of the rail transit alignment. The user cost per person is minimized separately as the third objective because the user cost is one of the most important decision-making factors for planning a transit system from the users’ perspective. A transit planner can make an informed decision between various alternatives based on the results obtained using different objective functions. The model is applied in a case study in the Washington, DC area. The optimal locations and sequence of stations obtained using the three objective functions are presented and a comparative study between the results obtained is shown in the paper. In future works we will develop a combinatorial optimization problem using the aforementioned objectives for the rail transit alignment planning and design problem.     

Cost-saving properties of schedule coordination in a simple trunk-and-feeder transit system

The paper explores how the coordination of vehicle schedules in a public transit system affects generalized costs. We consider an idealized system that delivers its users to a common destination by requiring each to transfer from a feeder- to a trunk-line vehicle. Continuum models are used first to analyze cases in which the trunk-line vehicle schedule is given exogenously. We find that when feeder vehicles are dispatched in coordination with this exogenous trunk-line schedule, the reduction in user cost often outweighs the added cost to the feeder operation. In cases when the frequencies of trunk and feeder services can be established jointly, the models show that coordination can be Pareto improving, meaning that operator and user costs both diminish. Conditions that give rise to these cost savings are specified. Practical implications are discussed.     

A dynamic station strategy to improve the performance of flex-route transit services

As an innovative combination of conventional fixed-route transit and demand responsive service, flex-route transit is currently the most popular type of flexible transit services. This paper proposes a dynamic station strategy to improve the performance of flex-route transit in operating environments with uncertain travel demand. In this strategy, accepted curb-to-curb stops are labeled as temporary stations, which can be utilized by rejected requests for their pick-up and drop-off. The user cost function is defined as the performance measure of transit systems. Analytical models and simulations are constructed to test the feasibility of implementing the dynamic station strategy in flex-route transit services. The study over a real-life flex-route service indicates that the proposed dynamic station strategy could reduce the user cost by up to 30% without any additional operating cost, when an unexpectedly high travel demand surpasses the designed service capacity of deviation services.     

Unreliable trains and induced rescheduling: implications for cost-benefit analysis

This paper is concerned with the assessment of generalized user cost reductions in the cost-benefit analysis (CBA) of transport policies that aim at reducing unreliability. In particular, we investigate the implications of railway passengers’ anticipating departure behavior when train services were unreliable. A simple model is established to describe and predict such anticipating behavior. Our numerical example shows how travelers’ anticipating departures and scheduling costs depend on the level of unreliability. The possible bias incurred by ignoring the reliability and schedule delay costs reductions in the traditional CBA can be quite substantial. Given our assumptions and parameterization, the underestimation of ignoring these costs could range from 33 to 75% of total generalized user cost reductions.     

Morning commute in a single-entry traffic corridor with no late arrivals

This paper analyzes a model of early morning traffic congestion, that is a special case of the model considered in Newell (1988). A fixed number of identical vehicles travel along a single-lane road of constant width from a common origin to a common destination, with LWR flow congestion and Greenshields’ Relation. Vehicles have a common work start time, late arrivals are not permitted, and trip cost is linear in travel time and time early. The paper explores traffic dynamics for the social optimum, in which total trip cost is minimized, and for the user optimum, in which no vehicle’s trip cost can be reduced by altering its departure time. Closed-form solutions for the social optimum and quasi-analytic solutions for the user optimum are presented, along with numerical examples, and it is shown that this model includes the bottleneck model (with no late arrivals) as a limit case where the length of the road shrinks to zero.     

Bounded rationality and irreversible network change

A network change is said to be irreversible if the initial network equilibrium cannot be restored by revoking the change. The phenomenon of irreversible network change has been observed in reality. To model this phenomenon, we develop a day-to-day dynamic model whose fixed point is a boundedly rational user equilibrium (BRUE) flow. Our BRUE based approach to modeling irreversible network change has two advantages over other methods based on Wardrop user equilibrium (UE) or stochastic user equilibrium (SUE). First, the existence of multiple network equilibria is necessary for modeling irreversible network change. Unlike UE or SUE, the BRUE multiple equilibria do not rely on non-separable link cost functions, which makes our model applicable to real-world large-scale networks, where well-calibrated non-separable link cost functions are generally not available. Second, travelers’ boundedly rational behavior in route choice is explicitly considered in our model. The proposed model is applied to the Twin Cities network to model the flow evolution during the collapse and reopening of the I-35 W Bridge. The results show that our model can to a reasonable level reproduce the observed phenomenon of irreversible network change.     

A bi-objective user equilibrium model of travel time reliability in a road network

Travel time, travel time reliability and monetary cost have been empirically identified as the most important criteria influencing route choice behaviour. We concentrate on travel time and travel time reliability and review two prominent user equilibrium models incorporating these two factors. We discuss some shortcomings of these models and propose alternative bi-objective user equilibrium models that overcome the shortcomings. Finally, based on the observation that both models use standard deviation of travel time within their measure of travel time reliability, we propose a general travel time reliability bi-objective user equilibrium model. We prove that this model encompasses those discussed previously and hence forms a general framework for the study of reliability related user equilibrium. We demonstrate and validate our concepts on a small three-link example.