Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

A new car-following model with consideration of the traffic interruption probability

In this paper, we present a new car-following model by taking into account the effects of the traffic interruption probability on the car-following behaviour of the following vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg-de Vries （KdV） equation is constructed and solved, and three types of traffic flows in the headway sensitivity space-stable, metastable, and unstable--are classified. Both the analytical and simulation results show that the traffic interruption probability indeed has an influence on driving behaviour, and the consideration of traffic interruption probability in the car-following model could stabilize traffic flow.

A cellular automata model of traffic flow with variable probability of randomization

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver＇s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram （flow^tensity relationship） is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation.

Continuum modeling for two-lane traffic flow with consideration of the traffic interruption probability

Considering the effects that the probability of traffic interruption and the friction between two lanes have on the car-following behaviour, this paper establishes a new two-lane microscopic car-following model. Based on this microscopic model, a new macroscopic model was deduced by the relevance relation of microscopic and macroscopic scale parameters for the two-lane traffic flow. Terms related to lane change are added into the continuity equations and velocity dynamic equations to investigate the lane change rate. Numerical results verify that the proposed model can be efficiently used to reflect the effect of the probability of traffic interruption on the shock, rarefaction wave and lane change behaviour on two-lane freeways. The model has also been applied in reproducing some complex traffic phenomena caused by traffic accident interruption.

A new car-following model with driver's anticipation effect of traffic interruption probability

Traffic interruption phenomena frequently occur with the number of vehicles increasing.To investigate the effect of the traffic interruption probability on traffic flow,a new optimal velocity model is constructed by considering the driver anticipation term in the interruption case for car-following theory.Furthermore,the effect of driver anticipation in the interruption case is investigated via linear stability analysis.Also,the MKdV equation is obtained concerning the effect of driver anticipation in the interruption case.Moreover,numerical simulation states that the driver anticipation term in the interruption case contributes to the stability of traffic flow.

Development of damage probability matrices based on Greek earthquake damage data

A comprehensive study is presented for empirical seismic vulnerability assessment of typical structural types, representative of the building stock of Southern Europe, based on a large set of damage statistics. The observational database was obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake. After analysis of the collected observational data, a unified damage database has been created which comprises 180,945 damaged buildings from/after the near-field area of the earthquake. The damaged buildings are classified in specific structural types, according to the materials, seismic codes and construction techniques in Southern Europe. The seismic demand is described in terms of both the regional macroseismic intensity and the ratio αg/ao, where αg is the maximum peak ground acceleration （PGA） of the earthquake event and ao is the unique value PGA that characterizes each municipality shown on the Greek hazard map. The relative and cumulative frequencies of the different damage states for each structural type and each intensity level are computed in terms of damage ratio. Damage probability matrices （DPMs） and vulnerability curves are obtained for specific structural types. A comparison analysis is fulfilled between the produced and the existing vulnerability models.

Expressway Traffic Flow Model Study Based on Different Traffic Rules

In this paper, two cellular automata traffic models are proposed to simulate the operation of an expressway. The results show that the flow rate and the average velocity are generally equal in the same density which is different among the lanes. The analysis of lane changing times and the velocity total deviation show some characteristics which are difficult to explain phase transitions under fundamental diagram theory. Therefore,the concept of lane changing probability is introduced, and it is concluded that the speed-limit rule can reduce the motivation of lane changing effectively.

Traffic Assignment Forecast Model Research in ITS

As an important role in the development of ITS, traffic assignment forecast is always the research focus. Based on the analysis of classic traffic assignment forecast models, an improved traffic assignment forecast model, multi-ways probability and capacity constraint (MPCC) is presented. Using the new traffic as- signment forecast model to forecast the traffic volume will improve the rationality and veracity of traffic as- signment forecast.

Design and Simulation of Intelligent Optical WDM Switching Node Based on Erlang Traffic Model

In this paper we propose a new architectural switching nodes consisting of two processing nodes that follow Erlang B and Erlang C traffic respectively. The developed model is used to best utilize the given number of output channels to achieve the least blocking probability. An appropriate mathematical model has been further devised and its call blocking probability has been enunciated. Performance of the model has been evaluated for different values of blocking probabilities. It has been observed that the performance of the network is well satisfactory for different design parameters.

Traffic danger detection by visual attention model of sparse sampling

A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.

Survivability evaluation for networks carrying complex traffic flows

The capability of a system to fulfill its mission promptly in the presence of attacks,failures,or accidents is one of the qualitative definitions of survivability.In this paper,we propose a model for survivability quantification,which is acceptable for networks carrying complex traffic flows.Complex network traffic is considered as general multi-rate,heterogeneous traffic,where the individual bandwidth demands may aggregate in complex,nonlinear ways.Blocking probability is the chosen measure for survivability analysis.We study an arbitrary topology and some other known topologies for the network.Independent and dependent failure scenarios as well as deterministic and random traffic models are investigated.Finally,we provide survivability evaluation results for different network configurations.The results show that by using about 50%of the link capacity in networks with a relatively high number of links,the blocking probability remains near zero in the case of a limited number of failures.

Effects of Potential Lane-Changing Probability on Uniform Flow

In this paper, we use the car-following model with the anticipation effect of the potential lane-changing probability （Acta Mech. Sin. 24 （2008） 399） to investigate the effects of the potential lane-changing probability on uniform flow. The analytical and numerical results show that the potential lane-changing probability can enhance the speed and flow of uniform flow and that their increments are related to the density.

基于网络编码的机密业务多路径光传输方法

随着互联网应用发展,越来越多具有安全需求的机密业务在空分复用弹性光网络中传输时,面临被攻击或窃听的安全风险.为了确保机密业务的传输安全性和减少频谱资源的浪费,提出一种空分复用弹性光网络中基于网络编码的机密业务多路径光传输方法 .在机密业务的路由阶段,该方法通过设计评估链路被窃听概率、路径跳数和路径上空闲频谱资源的路径代价函数,为机密业务选择最小路径代价的两路径或三路径传输策;在纤芯选择中,设计路径碎片率和负载失衡的评估值,为机密业务选择满足业务带宽需求的碎片率低和负载均衡的纤芯;在频谱分配中,设计满足网络编码条件的频谱碎片和负载感知的频谱分配方法,通过滑动频谱窗方法,为机密业务寻找能网络编码、且导致纤芯的频谱碎片化程度小和负载均衡的频谱块.仿真结果表明,与其他采用网络编码的路由频谱分配算法相比,在负载大于200爱尔兰时,本文所提方法能有效降低机密业务阻塞率和提高频谱资源使用率.

基于前景理论的疫后旅游景区交通方式选择行为

基于有限理性的前景理论构建了旅客出行方式选择模型,通过对某景区旅游者的个人信息、出行基本情况以及出行意向进行了调查分析,揭示出其出行行为的特点。并且进一步运用前景理论研究旅游者的出行方式选择行为,在完全理性和有限理性的条件下分别计算了各异质类旅客对不同客运方式的模糊选择概率。在此基础上,建立了基于有限理性作用下旅客个体出行决策的模型,得出了各异质类旅客对不同客运方式的出行偏好。通过比较不同类型旅客的出行偏好,可分析出高收入和务工旅客更倾向于驾车出行,而学生游客更倾向于乘坐大巴。相关研究的结论对于旅游景区周边交通设施的规划和建设有一定的指导意义,可更好地服务和满足游客的出行需求。

考虑地震动空间变化的区域公路网连通可靠性研究

区域公路网是社会交通大动脉和地震灾害救援生命线,连通可靠性反映了地震灾害发生后公路网的通行能力,地震动受震源位置及震中距的影响而具有显著的空间变化,对公路网的震后破坏状态具有重要影响。以邯郸地区公路网为研究对象,通过设定震源位置与震级,研究地震动空间变化影响下的区域公路网连通可靠性。首先,设定邯郸市1830年磁县大地震及一个虚拟地震为地震情景,分别设置震级为M6.0、6.5、7.0和7.5,基于地震动衰减关系表达地震动空间变化,得到公路单元对应的PGA。然后,结合地震易损性模型分析公路单元震后通行概率。最后,针对区域公路网空间范围大的典型特征,优化城市道路所用的最大可能状态算法,对邯郸地区公路网进行连通可靠性评估。结果表明,区域尺度下公路网络单元和节点数量多、空间展布复杂,其抗震连通可靠性与既有公路分布、区域城市位置等因素密切相关,地震动空间变化显著影响公路单元的震后破坏状态和通行概率,研究成果可为区域尺度公路网地震灾害评估及抗震韧性研究提供参考。

左转专用短车道信号交叉口通行能力分析

针对信号交叉口左转专用短车道排队阻塞导致的时空资源浪费、通行能力降低等问题,本文分析排队阻塞车流形成与消散过程,从车流到达分布理论和概率论2个角度建立了排队阻塞概率模型。考虑到不同流向的放行顺序,结合交通流波动理论,建立了3种不同相位方案下排队阻塞时进口道通行能力模型。通过VISSIM对模型进行检验,并对模型影响因素进行敏感性分析,观察不同影响因素下通行能力变化趋势。结果表明,模型能更加准确地计算不同信号控制条件下左转专用短车道通行能力;左转专用短车道下,短车道容量、信号周期、绿信比、车流比例、车流平均到达率对通行能力起主要影响。

带有最优流量信息中断期望影响的一类新格子模型

交通中断是导致交通扰动的一个重要因素.为研究最优流量信息中断的期望行为对交通流稳定性的影响,基于Nagatani’s模型考虑最优流量中断概率的影响,提出一类新的格子流体力学模型.首先,根据线性稳定分析方法,得到新模型的线性稳定条件;其次,通过非线性稳定理论,获得该模型的modified Korteweg-de Vries(mKdV)方程,并根据求解方程得到的扭结-反扭结孤立波解描述交通堵塞的演变过程;最后,通过仿真算例验证了理论分析结果.结果表明,考虑最优流量中断期望影响的新格子流体力学模型比Nagatani’s模型更稳定,当添加最优流量信息中断的期望影响时,交通流的稳定性得到显著提高.

基于半动态交通均衡的电动汽车充电负荷概率分布建模

传统电动汽车充电负荷建模通常采用对电动汽车个体进行抽样模拟的方式,未能从分析机理的角度描述电动汽车群体相互作用形成的宏观运行状态。为此,提出一种基于半动态交通均衡模型和组合荷电状态(combined states of the charge,CSOC)概率计算的电动汽车充电负荷概率分布计算方法。首先,分析电动汽车的交通特性和充电特性,并提出一种可行路径集构建方法;然后,引入交通均衡理论进行电动汽车空间分布建模,建立考虑随机效用的半动态交通均衡模型,实现宏观交通流均衡分配。进一步地,从理论层面分析电动汽车群的荷电状态变化,建立基于CSOC的充电负荷概率分布计算模型。最后,分别在13节点路网和实际大路网中验证所提方法的有效性,并分析了电动汽车渗透率和路网结构对充电负荷概率分布的影响。

机场空中交通环境质量优化路径研究

机场空中交通环境质量的提升对实现机场的可持续发展、推动民航业发展绿色转型具有重要的意义。针对现有研究较少从多因素角度开展机场空中交通环境质量评价并对机场整体环境质量进行优化的缺陷,从大气污染物、航空器噪声和碳排放三个角度识别机场空中交通环境质量的影响因素,基于解释结构模型构建机场空中交通环境质量的优化路径;通过建立机场空中交通运行的概率场景,基于宽容分层序列法构建机场空中交通环境质量优化模型,并结合遗传算法进行求解。以南京禄口国际机场为例进行实证分析,结果表明:机型比例和航线结构是影响机场空中交通环境质量的关键因素,优化后机场空中交通环境质量内梅罗指数降低了32.5%,可有效改善机场空中交通环境质量。