面向新型混合交通流的智能交叉口网络布局优化

考虑网联自动驾驶车辆(Connected Autonomous Vehicle, CAV)应用先进的车联网与自动驾驶技术，可以采用智能交叉口的组织形式，大幅提升交叉口的通行效率，为降低CAV与人工驾驶车辆(Human-driven Vehicle, HV)混行条件下城市交通系统的整体出行成本，提出智能交叉口在城 市交通网络中的布局优化问题，建立数学优化模型并求解。首先，基于对两类车辆行驶特性的分析，建立混合用户均衡模型，描述CAV与HV的路径选择行为；其次，从交通规划者的角度，以系统最优为目标，整合混合用户均衡模型，建立面向新型混合交通流的智能交叉口网络布局优化模型，并利用改进的遗传算法求解；最后，选取Sioux-Falls交通网络作为案例分析，验证模型与算法的有效性，并研究CAV渗透率变化对优化结果的影响。研究表明，智能交叉口在城市路网中的合理规划极大地提高了新型混行场景下城市交通系统的出行效率，同时，大幅降低了由于网联自动 驾驶单方面技术优势带来的CAV与HV的出行效率差距，增进了出行公平性。     

Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

编组站综合集成自动化系统实施过程中几个问题的探讨

本文介绍了成都北站综合自动化实施过程中遇到的道岔过电流保护设计、微机监测传输、尾部停车器逻辑设计和站场维修电话解决方案的实施经验和建议。     

船舶总纵极限强度模糊可靠性研究

本文以模糊数学和结构可靠性基本理论为基础,分析了传统随机可靠性理论的不足,并在常规模糊可靠性理论研究的基础上,利用模糊集合与普通集合之间的转换关系,研究了模糊变量组合时的可靠性计算方法,拓展了模糊可靠性理论的使用范围.通过对模糊可靠度计算结果分析发现,模糊可靠性理论使设计更加科学,更加符合工程实际;模糊变量组合在船舶总纵极限强度可靠性上的应用,避免了传统计算方法由于变量统计数据不足而导致的偏差,减少了很多繁复的数学运算.算例分析验证了本文方法的准确性和实用性.     

交通需求OD估计与预测的现状研究分析

目前，对于静态OD矩阵估计问题已经有很多研究者，对于动态OD前沿的研究工作则非常有限。关于对OD估计和预测的研究可分为封闭网络和开放网络。介绍了研究封闭网络的Bell，Van der Zijpp，Chang and Wu和Chang and Tao等人的方法，以及研究开放网络动态估计的3种方法，即Cascetta、Okutani、Ashok和Ben—Akiva等人的方法。并指出可以将OD估计问题陈述为具有不同误差特性、多个来源的不同类型信息的综合性和一致性的结合体，此联合估测就是经济计量学的混合估计的问题。     

复突触神经网络模型及其稳定性研究

传统的Hopfield网络在联想记忆、优化计算方面发挥了重要作用,但该网络存在一个弊端,即它只能处理线性或二次的最优化问题。因此,本文首先对Hopfield神经网络进行了扩展,将其称为复突触神经网络(或模型),扩展的网络不仅可以解决目标函数或约束中含有高阶的最优化问题,而且还可以处理目标函数含有对数、三角形式等较复杂函数的最优化问题;然后给出了该网络稳定的充分条件并给出了证明,同时对网络中的权矩阵是否对称也进行了讨论;最后结合典型的模糊c均值聚类问题验证了该模型的有效性。     

薄壁箱梁剪滞剪切效应自振特性分析

在推导考虑剪力滞、剪切变形双重效应的单元刚度矩阵与等效结点荷载矩阵的基础上[1],进一步推导出考虑双重效应的单元质量矩阵,从而形成完整的薄壁箱梁考虑双重效应的矩阵分析体系,可方便地纳入矩阵位移法程序系统,为常见的薄壁连续梁等复杂结构的剪力滞效应分析提供一种计算手段。利用自编程序ZLBOX对薄壁箱型简支梁和悬臂梁考虑剪力滞、剪切变形双重效应时的自振特性进行了分析,所得结果与ANSYS实体单元计算结果符合良好。计算结果表明,剪力滞、剪切变形双重效应使薄壁箱梁的自振频率降低,剪力滞效应占双重效应的85%以上,双重效应对高阶频率的影响比低阶频率的影响大。     

Estimation of origin‐destination matrices for a multimodal public transit network

This paper presents a procedure for the estimation of origin‐destination (O‐D) matrices for a multimodal public transit network. The system consists of a number of favored public transit modes that are obtained from a modal split process in a traditional four‐step transportation model. The demand of each favored mode is assigned to the multimodal network, which is comprised of a set of connected links of different public transit modes. An entropy maximization procedure is proposed to simultaneously estimate the O‐D demand matrices of all favored modes, which are consistent with target data sets such as the boarding counts and line segment flows that are observed directly in the network. A case study of the Hong Kong multimodal transit network is used to demonstrate the effectiveness of the proposed methodology.     

清水冲刷河床调整过程试验研究

通过沙质河床清水冲刷水槽试验,对河床纵剖面的调整、沙波尺度、粗化层厚度及其与沙波运动关系、粗化层级配、推移质级配等进行了观测分析,进一步揭示了清水冲刷,河床重建平衡的机理。水槽试验表明,沙质河床清水冲刷,上游河段比降调平,床沙粗化,沙波发育,河床阻力增大,水深增大,流速减小,导致河床供沙能力削弱,输沙能力降低,冲刷向不冲刷转化。     

一种自学习策略及其在模糊控制与神经网络控制中的应用

提出一种新的自学习控制策略。模糊控制与神经网络控制的仿真研究证实该策略具有易于实现、在线学习、跟踪控制和一定通用性的优点，并具有满意的学习功能。