A capacity maximization scheme for intersection management with automated vehicles

With the advent of connected and automated vehicle technology, in this paper, we propose an innovative intersection operation scheme named as MCross: Maximum Capacity inteRsection Operation Scheme with Signals. This new scheme maximizes intersection capacity by utilizing all lanes of a road simultaneously. Lane assignment and green durations are dynamically optimized by solving a multi-objective mixed-integer non-linear programming problem. The demand conditions under which full capacity can be achieved in MCross are derived analytically. Numerical examples show that MCross can almost double the intersection capacity (increase by as high as 99.51% in comparison to that in conventional signal operation scheme).     

高速路网不停车收费车道优化布设方法

合理设置高速公路收费站ETC (Electronic Toll Collection)车道数量，对高速公路通行效率至关重要。针对目前路网中ETC与MTC (Manual Toll Collection)车辆混行的情况，考虑ETC的普及率，结合多用户路网均衡模型和排队论方法，建立基于双层规划模型的高速路网ETC车道优化布设方法。上层模型以车辆总通行时间最小为目标，优化设置进出收费站的ETC车道数量；下层模型为多用户路网均衡模型，反映ETC和MTC车辆的路径和收费车道选择行为。下层模型通过设计收费站的等价拓扑结构，表征收费站的车道使用规则及车辆的收费车道选择行为，并采用排队论方法估计ETC和MTC车道的收费排队时间。根据模型的特点设计了基于主动集的启发式算法，利用参数二进制与拉格朗日函数法确定迭代下降方向，解决了下降方向与步长难以计算的问题；通过内嵌优化函数的方式，保证在主动集转化过程中上层约束均不会失效，且避免了迭代过程中的模型解退化问题。基于上海市绕城高速进行实证分析，结果表明：随着ETC普及率的提升，收费排队时长按照负指数趋势下降；与按比例布设ETC车道的方法相比，所提方法最高可降低57.4%的收费排队时间，且该方法可以避免ETC车道布设过多对于MTC车道通行能力挤压造成的负面效果。研究成果可以有效指导高速路网ETC车道的布设，提高路网通行效率。     

Detection of nonlinearity effects in structural integrity monitoring methods for offshore jacket-type structures based on principal component analysis

The detection of changes in the dynamic behavior of structures is an important issue in structural safety assessment. The development of detection methods assumes greater significance in the case of offshore platforms because the inherent problems are compounded by the harsh environment. Here, we describe an instrumented physical model for the structural health monitoring of an offshore jacket-type structure and the results of tests in several different damage scenarios. In a comparative investigation of two different methods, we discuss the difficulties of implementing damage detection techniques for complex structures, such as offshore platforms. The combined algorithm of a fuzzy logic system and a model updating method are briefly discussed, and a method based on stochastic autoregressive moving average with exogenous input is adopted for the structure. The consideration of uncertainties and the effects of nonlinearity were major objectives. So, the methods were also investigated based on the test scenarios consisting of the physical model with a geometric nonlinearity. The principal component analysis method was utilized for the detection of nonlinearity in the recorded data. The results show that the developed methods are suitable for damage classification, but the quality of the acquired signals must be considered an important factor influencing successful classification. The development of these methods may be extremely useful, as such technologies could be applied for offshore platforms in service, enabling damage detection with fewer false alarms.     

A proposed vision and vehicle-to-infrastructure communication-based vehicle positioning approach

It is essential to obtain accurate location of vehicles for new applications of Intelligent Transportation Systems. To remedy the defects of present Global Positioning System and vehicle-to-infrastructure (V-I) positioning technology, a new positioning approach based on vision and V-I communication is proposed. This approach aims at lane-level positioning with lower cost than conventional ones. In this approach, the position of the vehicle is represented by its lateral position (the lane number) and longitudinal position (the distance from entrance of the road) in a course coordinate system along the road; the specific lane the vehicle is occupying (the lane number) can be judged using the information of lane lines detected by vision systems; then the distance to the vehicle is obtained by a Road Side Unit (RSU) during the V-I communication; and the longitudinal position is calculated. The error of the approach on typical operating conditions is analyzed, indicating that the new approach can achieve the accuracy of less than 0.31 m for straight road and 0.58 m for typical arc road with ultra-wideband communication and ranging technologies and rational arrangement of RSUs. The feasibility of this approach is presented.     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.     

Effectiveness of travel time reliability indicators in the light of the assessment of dynamic managed lane strategy

ABSTRACT

The aim of traffic management is to ensure a high quality of service for a maximum number of users by decreasing congestion and increasing safety. Uncertainty of travel times decreases the quality of service and leads end users to modify their plans regardless of the average travel time. Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and for the assessment of active traffic management operations. This article discusses the efficiency of certain reliability indicators in an ex-post assessment of a traffic management strategy. Ex-post assessment is based on an observational before–after study. As some factors other than the studied management strategy may intervene between the two periods, and as most reliability indicators require knowledge of the full travel time distribution and not only its average, a methodology is developed for the identification of the impact of these exogenous factors on the whole distribution. Many reliability indicators are split into different parts allowing the identification of the part due to the management strategy impact. The methodology is tested numerically on a managed lane operation consisting of Hard Shoulder Running (HSR) at rush hour on a section of a French motorway. The variation of some reliability indicators appears misleading, whereas the splitting of the indicators increases our understanding of the strategy and highlights its impact. The paper gives the reliability assessment of the HSR field test and discusses different reliability indicators to identify their potential performances and shortcomings.     

基于灰色理论的雪山梁隧道施工过程渗漏水水源识别研究

为了解决黄龙景区雪山梁隧道开挖过程中的涌水水源识别问题,结合黄龙景区雪山梁隧道的相关施工资料,依据已有的地质资料和涌突水预测,通过水分析化学实验,采用灰色理论计算方法研究不同水系之间的关联度;而后针对单一水源和混合水源分别进行试验和分析,得出雪山梁隧道出口段内渗漏水来源最可能为大气降水,关联度较高的还有淘金沟上游水系和隧道出口处水系;最后进行比对,得出隧道渗漏水主要来源是大气降水和淘金沟上游水体的结论,并依据现场资料及实地踏勘,验证了灰色理论分析结果的可靠性。     

基于小波和粒子群算法的HEV行驶状况辨识方法研究

针对混合动力汽车(HEV)行驶状况(道路坡度和整车载荷)变化难以有效识别,导致驱动系统控制策略不能有效满足驾驶员意图问题,以混联式HEV为研究对象,提出了基于小波滤波和粒子群算法的HEV行驶状况辨识方法。首先建立了汽车行驶状况辨识模型,采用最小二乘法确立了优化目标函数,其次研究了基于小波滤波和粒子群算法的HEV行驶状况辨识原理,最后进行了行驶状况粒子群智能算法辨识试验。在采集实车数据的基础上,对实车数据进行小波滤波,并运用行驶状况辨识方法对道路坡度和整车载荷进行了辨识,并对辨识结果进行小波滤波,结果表明,试验工况下整车载荷辨识的相对误差绝对平均值为2.71%,道路坡度辨识的相对误差绝对平均值为3.85%,验证了所提出方法的有效性。     

射频识别技术在物流工程中的应用研究

简要介绍了射频识别技术的工作原理和优点,综述了射频识别技术在国内各个领域的主要应用,最后指出了当前射频识别技术所存在的主要问题。     

自行车流视频识别判断方法研究

考虑算法的实时性,交通流个体识别往往采用轮廓特征来描述。由于自行车与行人的很多轮廓特征值相近,在复杂城市交通环境中,从慢行交通流中准确地识别出自行车是目前采用视频检测交通流的难点之一。通过现场视频检测获取足够的样本外轮廓数据,分析检测目标轮廓的高、宽、高宽比、面积等典型轮廓特征,发现目标轮廓高宽比特征能较好地识别出行人、自行车等慢行交通,并给出合适的取值范围。研究表明自行车高宽比能够较好地成为视频识别的依据,为自行车视频识别提供数据。