Link-level vulnerability indicators for real-world networks

It is computationally expensive to find out where vulnerable parts in a network are. In literature a variety of methods were introduced that use simple indicators (measured in real-life or calculated in a traffic simulator) to pre-determine the seriousness of the delays caused by the blocking of that link and thereafter perform a more detailed analysis. This article reviews the indicators proposed in the literature and assesses the quality of these indicators. Furthermore, a multi-linear fit of the indicators is made to find a better, combined, indicator to rank the links according to their vulnerability. The article shows that different indicators assess different links to be vulnerable. Also combined they cannot predict the vulnerability of a link. Therefore, it is concluded that to find vulnerable links, one has to look further than link-based indicators.     

Modeling travel time reliability of freeways using risk assessment techniques

Travel time reliability is considered to be one of the key indicators for the performance of transport systems and is measured in various ways. This paper synthesizes both reliability concepts: traffic breakdown, the indicator of the instability of travel times, is treated as the risk, whereas travel time variability, the indicator of the uncertainty of travel times, is considered as the consequence of this risk. An analytical formula, using risk assessment technique, explicitly expresses the cost of travel time unreliability as the sum of the products of the consequences (i.e. variability) and the corresponding probabilities of breakdown. It provides a novel measure of travel time reliability and is applicable in network performance evaluations. An empirical example based on a large dataset of freeway traffic flow data from loop detectors shows that the developed travel time reliability measure is both intuitively logical and consistent.     

A panel data switching regression model of mobility and car ownership

The objective of this paper is to present a panel data model of car ownership and mobility. Unobserved heterogeneity is controlled for by including correlated random effects in the equations describing car ownership and mobility. A mass-points approach is adopted to control for unobserved heterogeneity. The results show that decisions concerning the first car in the household are difficult to affect; a large number of households are inclined to keep one car. Second car ownership may be more sensitive to changes in the observed contributing factors. This suggests that in The Netherlands policies aimed at changing second car ownership will be more successful than those aimed at influencing decisions concerning the first car in households. A major part of the correlation between the unobservables in the car ownership and the mobility equations is attributable to random effects. The time-variant errors of the mobility equations are not significantly correlated to car ownership decisions. This implies that mobility can only be influenced to a small extent by policy makers without measures aimed at reducing (second) car ownership.     

The Dutch mobility panel: Experiences and evaluation

The aim of this paper is to give an overview of the history and research experiences of the Dutch National Mobility Panel. Attention is given to the sampling strategy, the policy goals, and the representativity of the panel. It also tries to evaluate the research outcomes in terms of the original objectives and in view of more general research and policy goals. In sections one and two, a historic overview is given, starting from the first ideas to implement a longitudinal research instrument in transportation planning. In section three, some attention is devoted to longitudinal versus cross-sectional analyses. In section four, the sample design is treated in some detail. Next, various forms of bias are discussed that affect the representativity of the panel. In the sixth section, an overview is given of the research conducted with the data. Some conclusions are given in the final section.     

基于模糊逻辑的车辆侧偏角估计方法

提出了一种基于模糊逻辑的汽车侧偏角估计方法。它利用模糊逻辑和汽车运动学模型,将汽车转向盘转角、车轮转速、汽车加速度和横摆角速度信息相融合,进行车辆侧偏角估计。试验结果显示,该方法的鲁棒性和精确性较好,而且响应频率较高,可以满足ESP的控制需要。     

Spatial structure and mobility

The aim of this paper is to contribute to a clearer understanding of the extent to which the spatial structure and planning of the residential environment can explain mobility, in general, and the choice of mode of transport, in particular, and what spatial planning and traffic management aspects play a significant role in this. The research showed that certain aspects of the planned environment do indeed have a clear impact on mobility. These effects are particularly apparent in trips made for shopping and social or recreational purposes. It is mainly personal characteristics that largely or almost entirely determine commuter traffic. An integral approach to the planning of residential areas is required to achieve any great changes in mobility. Only then may we expect spatial planning to have any significant impact on car use.     

Consistent link flow estimation from counts

Partly because of counting errors and partly because counts may be carried out on different days, traffic counts on links of a network are unlikely to satisfy the flow conservation constraint “flow IN = flow out” at every node of the network. Van Zuylen and Willumsen (1980) have described a method of eliminating inconsistencies in traffic counts when a single count is available for each link in the network. In this paper, the method is extended to the case when more than one count is available on some links of the network. In addition, an algorithm is described for application of the method.     

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车牌照匹配技术的广泛应用为行程时间样本数据的精确获取提供了一种可行的方式。但是,由于各种客观原因,采集到的原始数据夹杂着大量的噪声数据,只有剔除了这些噪声数据,行程时间样本数据才能更好地应用于行程时间分析与服务。本文对产生噪声数据的原因进行了详细的分析,回顾了现有的噪声剔除方法,并分析其可能存在的问题;基于交通信息提取计算模型,提出了一种噪声剔除的新方法。以荷兰代尔夫特的一条城市道路为研究对象,基于实际数据对新方法和现有方法进行了对比分析。结果表明,新方法能够更好地剔除噪声数据。