Development of distress condition index of asphalt pavements using LTPP data through structural equation modeling

Traditional pavement distress index such as the Pavement Condition Index (PCI) developed by U.S. Army Corps of Engineers determines coefficients of distresses based on subjective ratings. This study proposed an asphalt pavement distress condition index based on various types of distress data collected from the Long-Term Pavement Performance (LTPP) database through Structural Equation Modeling (SEM). The SEM method treated the overall distress index as a latent variable while various distresses were treated as endogenous and other influence factors such as age, layer thickness, material type, weather, environment and traffic, were exogenous observed variables. The SEM method modeled the contributions of various distresses as well as the influence of other factors on the overall pavement distress condition. Influences of age, layer thickness, material type, environment and traffic on the latent distress condition were in accordance with previous studies. Compared with previous attempts to model latent pavement condition index utilizing SEM method, more pavement condition measurements and influencing factors were included. Specifically, this study adopted the robust maximum likelihood estimator (MLR) to estimate parameters for non-normally distributed data and derived the explicit expression of latent variables with intercepts. A multiple regression prediction model was built to calculate an overall condition index utilizing those measured distress data. The established pavement distress index prediction model provided a rational estimation of weighting coefficients for each distress type. The prediction model showed that alligator cracking, longitudinal cracking in wheel path, non-wheel path longitudinal cracking, transverse cracking, block cracking, edge cracking, patch and bleeding were significant for the latent pavement distress index.     

Determinants of new vehicle registrations in EU countries: a panel cointegration analysis

This paper investigates the determinants of new vehicle registrations in European Union (EU) countries by focusing on four particular segments – passenger cars, light commercial vehicles, commercial vehicles, and heavy commercial vehicles. A panel cointegration analysis for a panel of 13 EU countries during the period from January 1999 to August 2010 shows that new vehicle sales have long-run cointegration relations with vehicle prices, consumer confidence, income, interest rates, fuel prices, industrial production, and trade. More effective factors in determining new vehicle sales appear to be trade, interest rates, and industrial production.     

计量标准型一次抽样检验法在检测实验室耗材采购验证中的应用

为了对检测实验室质量控制的一个重要环节——耗材的质量控制提供一种有效的方法,通过制定合理的抽样检验方案,对技术指标进行检验。根据《计量标准型一次抽样检验程序及表》（GB/T 8054—2008）,分别使用S法、σ法确定抽样方案,对技术指标进行抽样检验。应用结果表明,将计量标准型一次抽样检验方法有效应用于实验室耗材采购验证,具有一定的科学性和经济性,对于经常使用品种较多、批量较大耗材的检测实验室,这种验证方法具有推广性。     

可交换随机序列和的中心极限定理的收敛速度

讨论了一类重要的相依随机变量序列－可交换随机变量序列部分和的中心极限问题。在与独立同分布随机变量序列部分和的中心极限问题相同的条件下，利用可交换随机变量的结构定理和Ｂｅｒｒｙ－Ｅｓｓｅｅｎ方法，获得了可交换随机变量序列部分和收敛于标准正态分布的最优收敛速度。     

Developing a chaotic pattern of dynamic Hazmat routing problem

The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat). In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.     

Car sharing in Norwegian urban areas: Examining interest,intention and the decision to enrol

This article’s objective is to investigate the effects of sociodemographic and residential built environments, directly and indirectly through personality traits, attitudes and car ownership, on willingness to use car sharing in the case of Norway. This is done by examining multiple dimensions of the adoption process: the stated general interest and intention to participate in car sharing among non-members, as well as the decision to enrol as a car sharing user by comparing members to non-members. In this study, we analyse web survey data from 2414 residents from urban areas in Norway, using three structural equation models. Our findings indicate that the adoption of car sharing is complexly related to car ownership, with a noteworthy discrepancy indicating greater car sharing interest, but lower car sharing membership rates among car owners. We also find that environmental concerns exert a clear positive effect on all three dimensions of the adoption process. Being careful with money is linked negatively to interest and intention to participate, while being sociable and agreeable exerts no effect. Car sharers’ sociodemographic profiles are typically that of early adopters, but many of the effects, especially on interest, are mediated by car ownership, environmental consciousness and/or being careful with money, rather than directly on the sociodemographic profiles. Finally, we find car sharing to be more prominent in denser areas, but we did not discover a clear connection with access to public transport.     

Traffic accident risk perception among drivers: a latent variable approach

ABSTRACT

Governments require decision tools to deal with road traffic accidents, a pandemic resulting in millions of deaths around the world. Evidence shows that human factors are one of the major causes of road accidents, and there is much interest in identifying variables that may have an impact on drivers’ perception of risk. To this aim, we design a stated choice experiment with eight hypothetical driving scenarios considering attributes that have been strongly associated with increased accident risks: (i) driving speed, (ii) driving the wrong way in a one-way street, (iii) overtaking on a bend, and (iv) driving under the influence of alcohol or drugs. Data from a sample of survey respondents are used to estimate a hybrid discrete choice model incorporating two latent variables, Driver Concentration and Safe Driving. Our results may contribute to the design of public policies geared to prevent accidents by encouraging safer driving behaviour.     

Residential location and transit-oriented development in a new rail corridor

The relationship of form, use, and density in urban development and their influence on human behavior and travel is a key element of many land use and transport policies. Prior research indicates high-density urban development leads to decreased travel and thus sustainable mobility; however, personal attitudes seem to have greater effect on mobility than does the urban form. This research evaluates how households consider transit-oriented development (TOD) characteristics in their location decisions with regard to new Mandurah railway line stations opened in December 2007 in Perth, Western Australia. The results indicate that the choice of residence reflects neighborhood and housing attributes, with significant heterogeneity in the populations of the three precincts in terms of their valuation of various housing characteristics, proximity to urban facilities, and transport. There is also significant variation in households’ attitudes to natural and artificial environments. A better understanding of the complex relationships among environment, travel, socio-demographic characteristics, and household attitudes can help transport planners leverage the benefits of TOD and improve the quality of urban design and community life.     

基于慢变量的交通客流预测模型

从影响交通客流分布的最主要因素——人口、能耗、区域面积出发,提出交通质量的概念,并基于它提出了新的交通发生(吸引)模型,参照万有引力定律对重力模型进行了改进。用实例将预测模型与传统的预测模型相比,说明模型的可行性和有效性。