海浪统计资料对船舶波浪弯矩设计值的影响

对船舶,特别是超规范船舶,进行结构的直接计算设计时,首先要知道波浪弯矩设计值。 要确切地做到这一点,设计人员应合理地选择船舶航行海域的海浪长期统计资料,然后根据船 舶的装载工况和实际可能达到的航速,借用线性理论或非线性理论进行波浪弯矩的长期预报 来确定设计值。本文就一艘大型集装箱船舶,按五个典型海域的海浪统计资料,对波浪弯矩及 波浪合成弯矩作了长期预报计算,并与 ＩＡＣＳ的统一纵强度要求ＵＲ—Ｓ１１的结果作了比较和 分析,给出了对船舶结构直接计算设计有指导意义的几点结论。     

城市综合交通调查的规范与创新

城市综合交通调查在中国已有30余年的广泛实践,当前的信息化和大数据背景下正历经发展与变革.在分析城市综合交通调查现状问题的基础上,提出制定《城市综合交通体系规划交通调查导则》(以下简称《导则》)的必要性.从目标与总体框架、调查项目分类、术语定义、调查内容与问题选项分类、调查流程规范几个层面对《导则》的主要思想与关键内容进行解析.提出城市综合交通调查未来发展方向应是将信息化技术与传统调查手段结合,提高调查效率与质量,关注信息化手段未能涵盖的交通特征.     

Optimizing the locations of electric taxi charging stations: A spatial–temporal demand coverage approach

Vehicle electrification is a promising approach towards attaining green transportation. However, the absence of charging stations limits the penetration of electric vehicles. Current approaches for optimizing the locations of charging stations suffer from challenges associated with spatial–temporal dynamic travel demands and the lengthy period required for the charging process. The present article uses the electric taxi (ET) as an example to develop a spatial–temporal demand coverage approach for optimizing the placement of ET charging stations in the space–time context. To this end, public taxi demands with spatial and temporal attributes are extracted from massive taxi GPS data. The cyclical interactions between taxi demands, ETs, and charging stations are modeled with a spatial–temporal path tool. A location model is developed to maximize the level of ET service on the road network and the level of charging service at the stations under spatial and temporal constraints such as the ET range, the charging time, and the capacity of charging stations. The reduced carbon emission generated by used ETs with located charging stations is also evaluated. An experiment conducted in Shenzhen, China demonstrates that the proposed approach not only exhibits good performance in determining ET charging station locations by considering temporal attributes, but also achieves a high quality trade-off between the levels of ET service and charging service. The proposed approach and obtained results help the decision-making of urban ET charging station siting.     

基于数据融合的公交客流规模测算方法

公交客流规模测算往往存在调查成本受限和准确度要求较高的矛盾.提出基于公交IC卡历史数据与人工补充调查数据的数据融合测算方法,以准确推算公交客流规模.首先根据公交线路的基本属性,采用聚类分析方法划分线路类型,从每一类中选择具有代表性的线路.基于IC卡数据分析公交客流时变特征,运用有序样本聚类Fisher算法将线路小时刷卡量进行聚类分析.划分刷卡量相似时段,进而采用优化方法确定调查抽样率,确定相应的调查车辆进行人工补充调查,最终经过数据融合计算获得公交客流规模.基于上海市某辖区IC卡数据进行案例分析,测算得到三类公交线路的日均客流量.     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.     

基于切片技术的点云数据预处理研究

针对扫描点云杂乱无序的特点，讨论了点云数据预处理的问题，提出了一种新的基于点云切片的数据预处理迭代算法．通过对点云最小包围盒进行均匀分割及分割后点云的密度分析，对密度过大的分割块进行迭代分割，建立了3个方向的点云切片和截面线．结果不仅大大减少了点云数据量，并且在点云密度过大的区域很好地保持了模型的原始特征，同时将原始的无序数据点集转化为具有层列结构的有序组织形式，确定了各点之间的相互关系，为后续曲线曲面拟合做了很好的准备．     

电子战仿真异构数据库数据集成应用研究

在分析异构数据源集成的基本模式的基础上，提出基于数据仓库技术实现电子战仿真异构数据库数据集成的解决方案，规划系统数据集成应用模式，设计电子战仿真试验数据仓库模型、数据抽取和转换的流程图，并分析数据转换规则。