An activity-episode generation model that captures interactions between household heads: development and empirical analysis

In this paper, we develop an approach for modeling the daily number of non-work, out-of-home activity episodes for household heads that incorporates in its framework both interactions between such members and activity setting (i.e. independent and joint activities). Trivariate ordered probit models are estimated for the heads of three household types – couple, non-worker; couple, one-worker; and couple, two-worker households – using data from a trip diary survey that was conducted in the Greater Toronto Area (GTA) during 1987. Significant interactions between household heads are found. Moreover, the nature of these interactions is shown to vary by household type implying that decision-making structures and, more generally, household dynamics also vary by household type. In terms of predictive ability, the models incorporating interactions are found to predict more accurately than models excluding interactions. The empirical findings emphasize the importance of incorporating interactions between household members in activity-based forecasting models.     

加强高校财务管理的再思考

加强高校财务管理的总体思路是:落实科学发展观,以增加经费投入为中心,建立健全财务管理规章制度,完善创新财务管理机制,加强财会机构、队伍建设,提高财务管理水平,促进高等教育事业科学发展。本文探索了高校财务管理面临问题的出路和解决途径。     

通过性交通需求预测方法研究

在分析通过性交通需求量影响因子的基础上,得到通过性交通需求量与道路等级、道路长度和道路负荷度（V／C）的关系,即通过性交通需求预测模型。研究结果表明,随着道路等级的提高、道路长度的增加以及道路负荷度的增大,通过性交通需求量增大。该结论可为交通影响评价过程中的背景交通需求预测提供理论依据和数据支撑,完善了交通影响评价方法。     

即墨市出租车发展规模需求分析

通过开展面向居民、驾驶员、出租企业等不同群体的问询访谈及非法营运客运车辆摸底调研,分析现状出租车运营服务水平及供需状况。在出租车发展规模影响因素分析的基础上,结合规范法、供需平衡法和调查分析法三种方法,以即墨市为例对出租车发展需求进行综合分析,并提出近期出租车扩容相关保障措施,可为相关城市出租车合理规模的确定提供方法借鉴。     

分层流体中拖曳球体尾流及辐射内波试验研究

在大型分层流水池中采用 PIV 方法对跃变分层流体中小球尾流场进行了测量,获得了不同拖曳速度工况下跃层处的尾流及内波流场,对体效应稳态内波和尾流效应非稳态内波的特征有了形象直观的了解,获得了内波流场速度大小随内傅氏数的变化规律。     

盾构施工穿越PBA工法车站站台层的数值模拟研究

以北京地铁马连洼车站为工程背景,采用ANSYS软件模拟盾构穿越PBA工法车站的施工过程,通过数值计算结果分析,研究盾构施工隧道穿越PBA车站时地表沉降、车站结构应力变化规律,可得下列结论：盾构在扣拱后的导洞下部掘进时对地表的沉降影响很小;盾构隧道掘进对上部导洞初支结构内力影响非常小;站厅层施工对盾构施工隧道影响较小,后续施工对管片轴力的影响要大于对管片弯矩的影响.计算结果表明：在条件受限时,采用先隧后站的施工方法既可以缩短工期,同时也能保证结构的安全.     

乘客差异化需求对公交出行满意度的影响

中国对于公交出行满意度的研究主要集中在服务质量指标的制定、乘客意向信息采集等方面,对出行满意度的影响因素缺少深入分析。结合安徽省铜陵市居民公交出行意向调查数据,对通勤乘客和非通勤乘客的公交出行服务需求特征进行分析。在此基础上构建结构方程模型,探究乘客公交出行满意度的影响因素。模型结果表明,通勤乘客更重视公交服务的经济性、便捷性和可达性,而非通勤乘客更重视可靠性和舒适性;经济性和可达性需求对通勤乘客满意度有显著积极影响,而便捷性、可靠性和舒适性需求对所有公交乘客满意度均有显著消极影响。由此,针对两类乘客分别提出提升公交出行满意度的措施。     

Random parameter models for estimating statewide daily bicycle counts using crowdsourced data

Persistent lack of non-motorized traffic counts can affect the evidence-based decisions of transportation planning and safety-concerned agencies in making reliable investments in bikeway and other non-motorized facilities. Researchers have used various approaches to estimate bicycles counts, such as scaling, direct-demand modeling, time series, and others. In recent years, an increasing number of studies have tried to use crowdsourced data for estimating the bicycle counts. Crowdsourced data only represents a small percentage of cyclists. This percentage, on the other hand, can change based on the location, facility type, meteorological, and other factors. Moreover, the autocorrelation observed in bicycle counts may be different from the autocorrelation structure observed among crowdsourced platform users, such as Strava. Strava users are more consistent; hence, the time series count data may be stationary, while bicycle demand may vary based on seasonal factors. In addition to seasonal variation, several time-invariant contributing factors (e.g., facility type, roadway characteristics, household income) affect bicycle demand, which needs to be accounted for when developing direct demand models. In this paper, we use a mixed-effects model with autocorrelated errors to predict daily bicycle counts from crowdsourced data across the state of Texas. Additionally, we supplement crowdsourced data with other spatial and temporal factors such as roadway facility, household income, population demographics, population density and weather conditions to predict bicycle counts. The results show that using a robust methodology, we can predict bicycle demand with a 29% margin of error, which is significantly lower than merely scaling the crowdsourced data (41%).     

城市道路场景下驾驶注意力需求的影响因素研究

为探索城市道路场景下影响驾驶注意力需求的交通因素,搭建包含多种交通变量的城市道路交通场景,对30位被试进行驾驶模拟器视线遮挡实验。以视线遮挡概率表示驾驶注意力需求等级,采用逐步逻辑回归方法建立各交通变量对驾驶注意力需求等级模型,并分析其影响方式。结果显示,遮挡概率沿驾驶路线波动较大,不同交通变量对驾驶注意力的需求不同。十字路口、公交车站、路边停放车辆、跟车距离、会车距离和弯道曲率等对驾驶注意力需求影响显著。越接近十字路口遮挡概率越小,到达十字路口时几乎没有遮挡。说明被试会主动适应外界交通环境对注意力的需求,有选择的获取与驾驶有关的交通变量信息,并预测各个交通变量的发展趋势。研究结果有助于提高驾驶分心预警系统的环境敏感性。     

环渤海地区LNG码头布局关键问题和选址研究

通过系统分析环渤海地区天然气运输及储备体系发展和建设特点,提出该区域LNG码头布局关键问题。首次提出环渤海地区LNG码头布局应将冬季4个月需求指标作为码头能力供给的主要依据,并提出区域LNG泊位布局规模等指标。在此基础上,围绕“十四五”期环渤海地区天然气供应迫切需要,提出区域LNG码头布局和选址思路,结合港址条件推荐重点发展的港址。