Naturalistic observation of drivers' interactions while overtaking on an undivided road

Current models of driving behavior and designs of driver support systems are not taking adequately into account the interactions between drivers. Although a driver's intended maneuver may not be physically possible at a specific time point, it may still be safely executed if the driver's intention is successfully communicated to and interpreted by another driver, who alters the own future trajectory so as to enable the maneuver execution. This paper presents some empirical findings relevant to communicative and cooperative interactions between drivers along naturalistic overtaking maneuvers on an undivided road. The cues used by drivers to interpret other drivers' intention and the drivers' interactions were extracted through video observations of the maneuvers together with the frequency of such interactions per level of traffic risk. The findings show that drivers use formal and informal cues to anticipate other drivers' intention. A significant percentage of maneuvers were performed after facilitation by other drivers. Future studies should focus on this phenomenon while future models of driving behavior should incorporate communicative and cooperative interactions among drivers, so as to design adequate cooperative support systems to enhance road safety.     

Social policies and solidarity during the Greek Crisis

This article provides a succinct overview of the phenomenon of solidarization in crisis‐ridden Greece. Brief accounts of the pre‐ and post‐crisis situation in four core social policy areas (health, employment, housing, education) are combined with the presentation of four illustrative case studies, one for each of the aforementioned areas. Drawing on a broad range of primary and secondary data, including 20 in‐depth interviews with key stakeholders and end‐users of the actions examined, we argue that while the crisis provoked a further “residualization” of the institutionalized solidarity system, it also triggered the development of new solidarity ventures, both by state and non‐state actors, often even including partnerships between them. These ventures reflect the building of a bridge between institutionalized and informal solidarity in Greece and the shift towards a new type of mixed, although fragmented, mode of solidarity.     

The state and the development of an information society: Greek policy and experience

The paper looks into the dynamics of information society policy and its implementation in the Greek context. It argues that information society development is a contested process, influenced by pre‐existing state, economy and society relations. Based on this, it looks into the different aspects of the idiosyncratic path which the evolution of the Greek information society has followed, particularly after 2000. Using Bob Jessop's strategic‐relational approach (SRA) to the state as an analytical framework and drawing on a number of in‐depth interviews with relevant political actors, it provides insights into policy implementation by examining: the public management of information technology projects, how such projects were received in bureaucratic structures and practices, as well as the relationship between the state and the information and communication technology (ICT) sector in public procurement processes. The emphasis is on the period 2000–2008, during which a major operational programme on the information society in Greece was put into effect. The paper also touches upon the post‐2008 experience, suggesting that information society developments might include dynamics operating independently and even in contradiction to the state agenda.     

Tests of fit for normal inverse Gaussian distributions

Goodness-of-fit tests for the family of symmetric normal inverse Gaussian distributions are constructed. The tests are based on a weighted integral incorporating the empirical characteristic function of suitably standardized data. An EM-type algorithm is employed for the estimation of the parameters involved in the test statistic. Monte Carlo results show that the new procedure is competitive with classical goodness-of-fit methods. An application with financial data is also included.     

What does a motorcyclist look at while driving at urban arterials?

To design adequate measures for enhancing riders' safety, a necessary first step is to understand the riders' visual scanning strategies under different traffic conditions. This paper presents the preliminary analysis of eye tracking data collected by three riders in the Athens metropolitan area, riding along urban arterial motorways and along an undivided urban road. Apart from the fixation duration and location, the fixated road elements and specific objects were annotated and analysed. The mean duration of fixations was found to be higher on urban roads than on motorways for all traffic densities. Riding in the condition of restricted flow seems to be more demanding for the riders, since the mean duration of fixations was higher in restricted flow than in free or congested flow on motorway and also higher than in free flow on urban road. The riders' fixation locations differed between motorway and urban road, especially in the vertical plane. The analysis of fixated road elements and specific objects indicates the specific points of interest of riders in each case. Although results should be validated with data from more riders, they provide hints on direction of future research efforts to enhance riders' safety in urban environments.     

Finite normal mixture copulas for multivariate discrete data modeling

A new family of copulas is introduced that provides flexible dependence structure while being tractable and simple to use for multivariate discrete data modeling. The construction exploits finite mixtures of uncorrelated normal distributions. Accordingly, the cumulative distribution function is simply the product of univariate normal distributions. At the same time, however, the mixing operation introduces association. The properties of the new family of copulas are examined and a concrete application is used to show its applicability.     

Bayesian estimation in Kibble's bivariate gamma distribution

The authors describe Bayesian estimation for the parameters of the bivariate gamma distribution due to Kibble (1941). The density of this distribution can be written as a mixture, which allows for a simple data augmentation scheme. The authors propose a Markov chain Monte Carlo algorithm to facilitate estimation. They show that the resulting chain is geometrically ergodic, and thus a regenerative sampling procedure is applicable, which allows for estimation of the standard errors of the ergodic means. They develop Bayesian hypothesis testing procedures to test both the dependence hypothesis of the two variables and the hypothesis of equal means. They also propose a reversible jump Markov chain Monte Carlo algorithm to carry out the model selection problem. Finally, they use sets of real and simulated data to illustrate their methodology.     

A Bayesian model for ranking hazardous road sites

Summary.  Road safety has recently become a major concern in most modern societies. The identification of sites that are more dangerous than others (black spots) can help in better scheduling road safety policies. This paper proposes a methodology for ranking sites according to their level of hazard. The model is innovative in at least two respects. Firstly, it makes use of all relevant information per accident location, including the total number of accidents and the number of fatalities, as well as the number of slight and serious injuries. Secondly, the model includes the use of a cost function to rank the sites with respect to their total expected cost to society. Bayesian estimation for the model via a Markov chain Monte Carlo approach is proposed. Accident data from 519 intersections in Leuven (Belgium) are used to illustrate the methodology proposed. Furthermore, different cost functions are used to show the effect of the proposed method on the use of different costs per type of injury.     

Flexible Bivariate INAR(1) Processes Using Copulas

Multivariate count time series data occur in many different disciplines. The class of INteger-valued AutoRegressive (INAR) processes has the great advantage to consider explicitly both the discreteness and autocorrelation characterizing this type of data. Moreover, extensions of the simple INAR(1) model to the multi-dimensional space make it possible to model more than one series simultaneously. However, existing models do not offer great flexibility for dependence modelling, allowing only for positive correlation. In this work, we consider a bivariate INAR(1) (BINAR(1)) process where cross-correlation is introduced through the use of copulas for the specification of the joint distribution of the innovations. We mainly emphasize on the parametric case that arises under the assumption of Poisson marginals. Other marginal distributions are also considered. A short application on a bivariate financial count series illustrates the model.     

A New Family of Nonparametric Quantile Estimators

A new core methodology for creating nonparametric L-quantile estimators is introduced and three new quantile L-estimators (SV1 _p , SV2 _p , and SV3 _p ) are constructed using the new methodology. Monte Carlo simulation was used in order to investigate the performance of the new estimators for small and large samples under normal distribution and a variety of light and heavy-tailed symmetric and asymmetric distributions. The new estimators outperform, in most of the cases studied, the Harrell–Davis quantile estimator and the weighted average at X _([np]) quantile estimator.