平面交叉口禁止左转效应分析

合理组织平面交叉口中的左转车流问题,与行车安全和通行能力有直接关系。禁止左转是平面交叉口组织的一个重要方式,它可能带来的交通效应与多种因素有关。从左转的交通特性出发,研究禁止左转后交叉口延误变化的机理和交通流的重新组织方式,得到禁止左转后交叉口延误变化的计算模型。通过模型分析认为,交叉口饱和度、路网密度和左转车流比例是影响交通效应的重要边界条件,并分析了这些边界条件对于禁止左转产生效应的影响方式。     

采用内点约束的最优冲突解脱方法

在自由飞行中,为了保证任何两架飞机之间的距离不能小于给定的安全间隔,采用内点约束条件和最优控制中的庞特里亚金极小值原理,研究了自由飞行中飞机的控制向量受约束时的平面冲突解脱问题,考虑了只改变速度大小和只改变速度方向的解脱策略。不同的策略具有不同的控制变量,各变量有不同的约束范围。采用极小值原理解得最优控制变量,并由内点约束条件获得解脱开始时间、约束时间及控制变量转换时间。计算结果表明改变速度大小策略的协作解脱耗费是单机解脱的1／10,而改变速度方向的策略在两机夹角过小时单机解脱耗费为协作解脱的1／3。     

闽南港口物流功能系统化简析

从系统的角度对闽南港口物流存在重复建设,缺乏分工协作的现状进行分析和对比,对各港口的优势和劣势做出比较,应用赫希曼一赫芬达尔指数(Hirshmann-Herfindahl index)反映了闽南地区各港口之间的港口体系空间结构的集散状况,提出各港口应从自身实际出发,在闽南港口物流系统下分工合作,充分发挥闽南港口物流的有利条件,促进闽南港口物流的发展.     

Digging Deep: Managing Social and Policy Dimensions of Geoduck Aquaculture Conflict in Puget Sound,Washington

Shellfish aquaculture can result in conflicts among stakeholders who perceive impacts and tradeoffs regarding sense of place, aesthetic, recreational, economic, and ecological values. Pacific geoduck clams (Panopea generosa Gould 1850) are grown in intertidal plots using gear- and labor-intensive techniques that result in a high value export product. A confluence of issues has resulted in on-going social and legal tensions surrounding geoduck aquaculture in southern Puget Sound, Washington (WA), USA. Using interviews and document analysis, we explored stakeholder perspectives and policy issues related to geoduck aquaculture in southern Puget Sound. Twenty-three stakeholders were interviewed, including state agency employees, representatives of the aquaculture industry, nongovernmental organizations, landowners, a tribal member, and an academic. Nine state hearings board decisions on challenges to aquaculture permits were also analyzed. Stakeholders articulated a variety of perspectives regarding aesthetic, recreational, land-use, ecological, political, regulatory, and economic aspects of geoduck aquaculture activities. Hearings board cases addressed similar issues (aesthetic, ecological, and recreational), as well as challenges to restrictions on aquaculture. Potential strategies for managing this conflict include emphasizing best management practices, identifying and incorporating best available science, joint fact-finding approaches, and initiating and improving communication among all stakeholders.     

Classification modeling approach for vehicle dynamics model‐integrated traffic simulation assessing surrogate safety

To assess safety impacts of untried traffic control strategies, an earlier study developed a vehicle dynamics model‐integrated (i.e., VISSIM‐CarSim‐SSAM) simulation approach and evaluated its performance using surrogate safety measures. Although the study found that the integrated simulation approach was a superior alternative to existing approaches in assessing surrogate safety, the computation time required for the implementation of the integrated simulation approach prevents it from using it in practice. Thus, this study developed and evaluated two types of models that could replace the integrated simulation approach with much faster computation time, feasible for real‐time implementation. The two models are as follows: (i) a statistical model (i.e., logit model) and (ii) a nonparametric approach (i.e., artificial neural network). The logit model and the neural network model were developed and trained on the basis of three simulation data sets obtained from the VISSIM‐CarSim‐SSAM integrated simulation approach, and their performances were compared in terms of the prediction accuracy. These two models were evaluated using six new simulation data sets. The results indicated that the neural network approach showing 97.7% prediction accuracy was superior to the logit model with 85.9% prediction accuracy. In addition, the correlation analysis results between the traffic conflicts obtained from the neural network approach and the actual traffic crash data collected in the field indicated a statistically significant relationship (i.e., 0.68 correlation coefficient) between them. This correlation strength is higher than that of the VISSIM only (i.e., the state of practice) simulation approach. The study results indicated that the neural network approach is not only a time‐efficient way to implementing the VISSIM‐CarSim‐SSAM integrated simulation but also a superior alternative in assessing surrogate safety. Copyright © 2014 John Wiley & Sons, Ltd.     

车路协同无信号交叉口的矩形冲突检测及消解

针对车路协同环境下的冲突问题，建立了以系统反应时间代替驾驶员反应时间的自动驾驶车辆制动距离模型，以此作为安全距离改进了矩形冲突检测模型，并根据轨迹优化的研究思路，提出了以矩形冲突检测模型为基础的冲突消解算法，对非通行优先权车辆进行速度引导，避免车辆冲突。在车联网开源框架 Veins 的基础上，将交通仿真器 SUMO和网络仿真器 OMNeT++双向耦合，并对冲突检测模型与消解模型进行验证。仿真结果显示，该冲突检测及消解模型具有可行性，与传统无信号交叉口四路停车让行规则相比，模型中的速度引导方案能减少合流冲突车辆 8.6%的平均行驶时间，减少交叉冲突车辆 8.3%的平均行驶时间；合流冲突和交叉冲突中车辆的平均速度分别提高了61.4%和105.0%。在实际应用中，冲突消解模型可以为不同速度范围内的自动驾驶车辆提供速度参考，降低无信号交叉口车辆发生碰撞的概率，提高无信号交叉口的通行效率。