基于偏差分析的交通事件自动检测算法

高速公路事件检测是交通管理与控制中十分重要的环节。将交通流动态预测与事件检测相结合,探讨了基于偏差分析的事件识别方法。该方法对3个主要的交通流参数,交通量、地点车速和时间占有率进行动态预测,对预测值与实际值的偏差进行统计分析,明确了事件检测的具体步骤和事件发生概率的计算模型。该方法不受检测路段具体位置和时间的限制,具有较高的检测率和较小的误报率,有助于管理人员制定决策。     

大型图的割集算法研究

割集的概念与性质在网络问题的研究中受到广泛重视,但目前的割集搜索算法可操作性较差.提出了一种适合大型图的割集搜索算法CSA-CJ,利用二进制数分割无向图的顶点集,通过对子图各顶点的关联集的运算产生相应的割集.该算法简单适用,易于用计算机实现,尤其适合于大型图的割集搜索.     

简支组合梁抗火设计简化方法

根据现行《建筑钢结构防火技术规范》（CECS200：2006）中简支组合梁抗火承载力验算方法,提出了简支组合梁抗火设计的临界温度法,给出了临界温度的计算方法。对影响简支组合梁临界温度的参数分析研究发现：在确定的荷载比下简支组合梁的钢梁截面、材料强度、有效宽度等对简支组合梁的临界温度的影响较小,而耐火极限和楼板厚度对简支组合梁临界温度影响较大。给出了一般简支组合梁在不同楼板厚度、不同耐火极限下,不同荷载比对应的临界温度,可供工程设计使用。     

高速公路事故响应控制模式构建

为优化高速公路发生交通事故后的入口匝道调节率,以达到减缓交通拥挤、降低事故冲击的目的,对高速公路交通事故发生后的车流行为进行了研究,以车流行为改变引起的检测信号为基础,建立了控制所需的行为参数集;利用控制理论,构建了高速公路事故动态随机响应控制模式,并利用卡尔曼滤波和线性二次高斯方法求解,通过实例演算进行评析。研究结果表明:提出的控制模式与无控制和定时控制相比较,对中等流量具有较好的控制效果,对较高流量和较低流量具有一定的控制效果,对较高流量和中等流量下的通过率有一定的改善。该控制模式可运用于高速公路智能控制系统之中,提高事故条件下的道路交通服务水平。     

An Exploration of the Relationship between Timing and Duration of Maintenance Activities

The timing and duration of an activity episode are two important temporal aspects of activity-travel behavior. Understanding the causal relationship between these two variables would be useful in the development of activity-based travel demand modeling systems. This paper investigates the relationship between these two variables by considering two different causal structures – one structure in which time-of-day choice is determined first and influences duration and a second structure in which activity duration is determined first and affects time-of-day choice. These two structures are estimated within a discrete-continuous simultaneous equations framework employing a full-information maximum likelihood methodology that allows error covariance. The estimation is performed separately for commuter and non-commuter samples drawn from a 1996 household travel survey data set from the Tampa Bay area in Florida. The results of the model estimation effort show that the causal structure in which activity duration precedes or affects activity timing (time of day choice) performs better for the non-commuter sample. For the commuter sample, the findings were less conclusive with both causal structures offering equally good statistical measures of fit. In addition, for the commuter sample, all error correlations were found to be zero. These two findings suggest that time of day choice and activity episode duration are only loosely related for the commuter sample, possibly due to the relatively non-discretionary and inflexible work activity and travel.     

基于实测数据评估交通事件检测中神经网络应用性的研究

神经网络为交通事件自动检测技术摆脱传统方法探测率低、误报率高的状况提供了新的解决思路。在以往局限于仿真数据研究的基础上,本文利用I-880数据库实测交通事件数据对神经网络在交通事件自动检测中的实际应用进行了研究,结果表明:神经网络应用于交通事件自动检测技术中,具有较高的探测率和较低的误报率,但该算法可移植性较差,在实际应用中要予以考虑。     

Understanding time use: Daily or weekly data?

The appropriate duration of time diaries as a source of time use data is analyzed in a structured way. Nine detailed European surveys based on seven-days diaries are used in order to study different dimensions of data quality, duration and variability of activities, and modeling capabilities. Pseudo diaries of 1, 2 (one week, one weekend) and 3 (one week, both weekend) days are constructed to further analyze these issues, selecting the seven-days diaries data as a benchmark. Comparative results show that two and three-days weighted surveys seem to be an adequate surrogate for the information obtained in weekly surveys that capture a basic work–leisure cycle.     

Heterogeneous hazard model of PEV users charging intervals: Analysis of four year charging transactions data

Public charging infrastructure represents a key success factor in the promotion of plug-in electric vehicles (PEV). Given that a large initial investment is required for the widespread adoption of PEV, many studies have addressed the location choice problem for charging infrastructure using a priori simple assumptions. Ideally, however, identifying optimal locations of charging stations necessitates an understanding of charging behavior. Limited market penetration of PEV makes it difficult to grasp any regularities in charging behavior. Using a Dutch data set about four-years of charging transactions, this study presents a detailed analysis of inter-charging times. Recognizing that PEV users may exhibit different charging behavior, this study estimates a latent class hazard duration model, which accommodates duration dependence, unobserved heterogeneity and the effects of time-varying covariates. PEV users are endogenously classified into regular and random users by treating charging regularity as a latent variable. The paper provides valuable insights into the dynamics of charging behavior at public charging stations, and which strategies can be successfully used to improve the performance of public charging infrastructure.     

Commuting and wellbeing: a critical overview of the literature with implications for policy and future research

ABSTRACT

This review provides a critical overview of what has been learnt about commuting’s impact on subjective wellbeing (SWB). It is structured around a conceptual model which assumes commuting can affect SWB over three time horizons: (i) during the journey; (ii) immediately after the journey; and (iii) over the longer term. Our assessment of the evidence shows that mood is lower during the commute than other daily activities and stress can be induced by congestion, crowding and unpredictability. People who walk or cycle to work are generally more satisfied with their commute than those who travel by car and especially those who use public transport. Satisfaction decreases with duration of commute, regardless of mode used, and increases when travelling with company. After the journey, evidence shows that the commute experience “spills over” into how people feel and perform at work and home. However, a consistent link between commuting and life satisfaction overall has not been established. The evidence suggests that commuters are generally successful in trading off the drawbacks of longer and more arduous commute journeys against the benefits they bring in relation to overall life satisfaction, but further research is required to understand the decision making involved. The evidence review points to six areas that warrant policy action and research: (i) enhancing the commute experience; (ii) increasing commute satisfaction; (iii) reducing the impacts of long duration commutes; (iv) meeting commuter preferences; (v) recognising flexibility and constraints in commuting routines and (vi) accounting for SWB impacts of commuting in policy making and appraisal.     

先进出行信息下事故对行程时间可靠性的影响

定义路径行程时间可靠性为在交通事故期间内平均路径行驶时间小于事故前路径出行时间乘以可接受拥堵水平的概率,由此导出路网行程时间可靠性.假定事故持续时间服从正态分布并将研究时域划分成相同的时段,在先进出行信息下,利用元胞传输模型进行路段流量加载,给出了每一个时段内路径行程时间的递推式,并在每一个时段内更新1次路径出行时间,出行者根据更新的出行时间运用Logit模型进行路径决策,最后基于Monte-Carlo法模拟求解路网行程时间可靠性.算例结果表明,行程时间可靠性随事故持续时间和方差及需求的增加而减小;可靠性随可接受拥堵水平的增加而增加;在拥堵网络中,包含事故路段的OD间需求越高,可靠性越低.