GPS及其在公路测量中的应用

简要介绍了GPS全球定位系统组成原理,总结了GPS测量的特点以及GPS技术在公路测量中的应用。对GPS实时动态(PTK)定位技术在公路测量中的开发和应用进行了论述。     

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比较了传统运输节点与物流中心的差异，指出物流中心选址重要性和独有特征．综合分析了当前一些文献对物流中心选址方法的研究，指出这些方法可能存在的不足．分析了AHP方法的扩展ANP应用于物流中心选址的优点，指出从物流中心选址的外部动态环境和内部决策条件出发可以更加全面分析物流中心选址涉及到的各种因素及其内部关系，提出采用ANP方法进行物流中心选址的影响因素结构及其分析方法、具体分析步骤和要点．     

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国外已经广泛使用的SP调查方法在我国交通领域还鲜有应用，因此，本文首先介绍了交通SP（Stated Preference）调查和RP（Revealed Preference）调查的不同，并阐述了前者相对于后者的优越性。交通方式选择模型中，采用RP调查标定时间价值参数，通常会由于数据相关性较强而产生误差，进而影响到整个四阶段模型的精度。本文在构架交通方式选择模型的基础上，指出行为时间价值参数的重要性，并分析了其不易准确衡量的原因。在此基础上，以北京市市域交通模型为例，利用SP调查以较低的成本获取足够的数据，从而准确地标定了时间价值参数，提高了模型的精度。     

一类有竞争的物流配送中心选址模型

对已有多个配送中心存在的前提出，新增配送中心为获取最大市场占有量如何进行有效的选址决策问题进行了研究，建立了一个选址决策模型，把求解的问题归结为无约束的非线性规划问题，并给出了迭代算法，最后对如何解决考虑多种选址影响因素及多个新增配送中心的复杂情况进行了讨论。     

Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data

Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.     

A study of carpooling behaviour using a stated preference web survey in selected cities of India

This paper analyses how people perceive the idea of carpooling and evaluate preferences while making a decision to join a carpool. Analysing data from a web-based stated preference survey in India reveals that cognitive attitudes play a significant role in evaluating the perceived advantages and disadvantages of carpooling whereas intentions to carpool are associated with perceived negative evaluations. A factor analysis identifies two latent attitudinal factors: a ‘time–convenience’ factor that discourages carpooling and a ‘private–public cost’ factor that encourages carpooling. The study analyses the influential attributes – extra travel time, walking time to reach meeting point, waiting time at pickup point and cost savings – as explanatory variables for the utility of carpooling. Cost savings prove to be the most significant attribute when combined with other attributes, followed by extra travel time. The study provides the implications to policy-makers of designing promotional tools to improve the propensity of carpooling among single occupant vehicle drivers.     

Integrated optimization of location and signal timings for midblock pedestrian crosswalk

Finding the optimal location and signal timing plan is one of the most critical operational issues for a signalized midblock crosswalk on an arterial section, which is increasingly being installed in highly populated areas in developing countries such as China. This paper presents a multiobjective optimization model and an efficient solution algorithm for a one‐ or two‐stage midblock crosswalk on an arterial section. The proposed model aims to produce the optimal location and corresponding signal settings to balance the trade‐off between pedestrian delays and vehicular bandwidth when the signals of the crosswalk and adjacent intersections are coordinated. The proposed model has three distinguishing features: (i) the costs for both pedestrians and vehicles are considered in a unified framework; (ii) the location and signal settings of the midblock crosswalk are simultaneously optimized; and (iii) a multiobjective optimization approach is developed to study the effectiveness of the midblock crosswalk under conditions in which the priorities between pedestrian and vehicle flows differ. A nondominated sorting genetic algorithm II (NSGA II)‐based algorithm is developed to solve the model efficiently. The results of the case study showed that the proposed model would help traffic practitioners, researchers, and authorities properly locate and signalize a one‐ or two‐stage midblock pedestrian crosswalk on an arterial section. Copyright © 2015 John Wiley & Sons, Ltd.     

基于斜拉索张力测定的斜拉桥健康诊断

应用试验校正的高精度三维有限元模型,对斜拉桥主梁结构损伤位置识别的斜拉索张力指标进行了研究。模拟12种可能的损伤情况,研究了基于斜拉索局部模态基频构造索张力指标的方法,索张力指标对各损伤情况下损伤位置的识别效果和对损伤程度的敏感性。结果表明,用斜拉索局部模态基频所构造的张力指标对不同的损伤程度呈现较好的稳定性和灵敏性,对模拟的12种损伤情况的正确识别率可达75%。该方法的突出优点是只需测量斜拉索局部振动模态的基频,就能获得较好的损伤识别效果,比其他面向损伤检测的测量容易得多。该方法可十分方便地推广应用于悬索桥加劲梁结构的损伤定位,具有较高的实用价值。     

公路交通量及OD调查统计分析软件开发

公路交通量及起讫点(OD)调查的统计分析是开展公路网规划、公路建设项目可行性研究等工作的重要基础。一种统计分析软件的开发弥补了当前流行的交通分析软件在这一方面的不足,实现了公路交通量及OD调查的数据输入、交通流特性的统计分析、断面流量的生成、SQL查询、OD矩阵的操作等功能,提高了统计分析工作的效率和质量,为交通规划、建设与管理的科学决策提供了有力的数据处理工具。     

干线公路沥青路面养护大中修工程方案设计探讨

结合某干线路面大中修工程方案设计中的路况调查结果,对其路面使用品质加以评价,有利于得出合理的路面大中修方案。