基于活动的交通需求计算过程模型研究综述

为适应现代城市快速发展的要求,研究人员对交通需求预测进行了广泛深入的研究,交通需求模型在建模方法和模型功能上发生了很大变化.基于活动的方法受到广泛重视,基于活动的交通需求模型研究成为热点.其中计算过程模型被认为是最有发展前景的.文中回顾了基于活动的方法的发展过程;介绍了基于活动的方法的理论基础;总结了基于活动的交通需求计算过程模型,并分析了其中4个模型的特点;探索了模型的改进途径,展望了模型的发展应用前景.     

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综合评述了活动－出行行为研究方法和存在的问题,引入贝叶斯结构学习和参数估计方法,辅以基于活动的出行行为分析理论、非集计建模方法和SP/RP数据融合方法,提出了基于贝叶斯结构学习和参数估计方法的出行行为与TDM策略互动关系分析方法的框架,探索了改进已有研究方法的途径。研究表明,贝叶斯理论可以将居民的个人属性及隐性非样本信息在出行行为预测中充分表达,并解决MNP等复杂非集计模型的参数标定问题。将贝叶斯理论与已有的出行行为分析方法相结合,可以使出行行为预测更为精确、全面和灵活,从而更加准确地描述活动－出行决策行为与TDM策略的互动响应关系,为制定有效的TDM策略,缓解城市交通供需矛盾提供理论依据。     

建成环境对步行和自行车出行的影响--以波哥大为例

哥伦比亚波哥大以可持续的城市交通系统闻名,包括其密集的自行车道网络以及Ciclovía系统——为骑车者和行人预留的道路空间,可在星期日和节假日休闲出行使用。探讨此类设施以及建成环境的其他属性——城市密度、混合用地、可达性以及与公共交通车站的距离——如何影响步行和自行车出行行为以及Ciclovía的使用。结果表明,道路设施设计要素例如道路密度、连通性、与Ciclovía车道的距离,与体力活动相关;而建成环境的其他属性如密度和用地混合程度,对体力活动影响甚微。这可能是由于波哥大建成区的大部分街区均在非机动交通出行占绝对优势的时期演变发展——紧凑、用地混合、交通可达性水平相似。由此可见,影响非机动交通出行的因素是设施设计而非一般的街区用地属性。     

"诗可以群"的诗学理论与先秦时期的文学活动

孔子对诗的"兴观群怨"的理论,是先秦时期重要的诗歌创作理论,也是历代诗歌批评史讨论的对象,并且贯穿于历代诗歌的创作实际中.但长期以来,人们往往把"诗可以群"从"兴"、"观"、"怨"中割裂开来,导致人们忽视了"诗可以群"的诗学理论与先秦时代文学活动的关系."诗可以群"的诗学理论反映了先秦时期文学活动的集体性.这一理论为我们研究文学觉醒的时间问题提供了一个窗口.     

线性计划方法及其应用研究

CPM作为十分有用的计划技术在建筑业得到了广泛的使用,但也存在一些不足．而线性计划方法作为一种新的计划技术,针对诸如高速公路、铁路工程等线状工程项目的特点,是编制其进度计划十分有效的工具,但目前在理论和应用研究方面还存在许多不足．因而,文章介绍了线性计划方法并对该方法提出了一些改进．同时,通过案例介绍了线性进度计划的绘制方法和步骤．     

Observing individual dynamic choices of activity chains from location-based crowdsourced data

The existing efforts on studying human mobility and activity using location-based crowdsourced data mainly focus on obtaining the activity chain pattern in a region at an aggregate level. To observe individual dynamic choices of activity chains, this paper presents a data-driven approach to estimating individual-specific activity chain set and corresponding choice probabilities for a given person over a 24-h period using crowdsourced data from location-based service apps. We detect an individual-specific stochastic activity set using a contextual-parcel data analysis. Based on the time geography theory, we refine a space-time bicone concept to construct an activity-travel space-time-state network from the stochastic activity set. These space-time bicone constraints define a set of potential activity choices to reduce the search space of activity location and duration choices. We construct an activity state transition graph from the space-time-state network and calculate a Markov matrix for activity choice probabilities. Furthermore, we calculate the probabilities of activity chain choices using the Markov matrix. We also visualize individual-specific activity chain set in a space-time-state network to show the dynamic choices of individual daily mobility and activity. We demonstrate the proposed approach through conducting numerical analyses using crowdsourced data from location-based service apps - Foursquare and Twitter to construct individual-specific activity choice sets and corresponding choice probabilities.     

An application of activity-based travel analysis to simulation of change in behaviour

People are liable to exaggerate their future use of new transport facilities when they are interviewed about it before it is in operation. This is often due to the fact that they have no real frame of reference for the study. In order to overcome this, we have tried to perfect an original behaviour-change simulation method (Section 1). It has been tested on a town on the outskirts of Lyons (France) and has provided interesting results. However, to use it as a forecasting tool, we have to make sure that the assertions by potential users when interviewed are consistent with actual behaviour when the new facilities become available (Section 2). This test was carried out when a new light rail line was introduced in Grenoble (France). A first survey was undertaken before the opening of the new line, and people's actual (new) behaviour was surveyed after the new line opened. It is therefore possible to analyse the validity of the simulation (Section 3).     

A retrospective and prospective survey of time-use research

The central basis of the activity-based approach to travel demand modeling is that individuals' activity-travel patterns are a result of their time-use decisions within a continuous time domain. This paper reviews earlier theoretical and empirical research in the time-use area, emphasizing the need to examine activities in the context or setting in which they occur. The review indicates the substantial progress made in the past five years and identifies some possible reasons for this sudden spurt and rejuvenation in the field. The paper concludes that the field of time-use and its relevance to activity-travel modeling has gone substantially past the "tip of the iceberg", though it certainly still has a good part of the "iceberg" to uncover. Important future areas of research are identified and discussed.     

Modelling behavioural rules for daily activity scheduling using fuzzy logic

The paper focuses on how trip time variability affects re-scheduling of daily activities. A delay in a trip or an early arrival can contribute to changes in the timing, location of the next activity, and to the deletion/addition of some activities. We propose the idea of using fuzzy logic rules to explain the effect of variability in travel time on the benefits perceived by an individual with the changes, and to model different actions that the individuals take in order to re-establish the steadiness of the existing timetable. The fuzzy model is used to handle the imprecision of the data which is unstructured text. The results show that large deviations in trip duration are more likely to induce significant changes in the timetable whereas small deviations are either ignored or translated into modified timing of the next activity. In choosing an action, greater importance is assigned to the flexibility of the following activity, to the magnitude of the trip time saving/delay, and to the duration of the next activity. Time savings are not favoured unless they can be readily transferred into additional activity time allocated to the next activity or to a new activity. The fuzzy rules based system is capable of predicting satisfactorily the strategy of coping with uncertainty in travel times and the satisfaction sensed with the change.     

选择性PDGF受体酪氨酸激酶抑制剂对兔PVR的治疗作用

目的　评价一种新的血小板源性生长因子 (platelet derivedgrowthfactor,PDGF)受体酪氨酸激酶抑制剂AG12 95对兔增殖性玻璃体视网膜病变 (proliferativevitreoretinopathy ,PVR)的治疗作用。 方法　兔结膜成纤维细胞 (rabbitconjunctivalfibroblastscells,RCF)培养 ,用MTT分析法检测PDGF AA和 BB以及AG12 95对兔RCF的增殖状况的影响。建立PVR动物模型 ,玻璃体腔内给予AG12 95 ,用牵引性视网膜脱离 (tractionalretinaldetach ment,TRD)的发生率判断药物的体内疗效。眼视网膜电生理检查和HE染色分析药物的毒性。结果　 10 μmol·L-1和 10 0 μmol·L-1两种浓度的AG12 95均可显著抑制由PDGF AA和 BB诱导的成纤维细胞的增生 ,10 0 μmol·L-1AG12 95可减缓兔TRD的发生 ,但其作用仅持续至第 2 1d。在AG12 95治疗组中 ,未发现明显的网膜毒性。结论　PDGF受体酪氨酸激酶抑制剂AG12 95可减缓兔TRD的发生。