The impact of a dedicated lane for connected and automated vehicles on the behaviour of drivers of manual vehicles

Connected and automated vehicles (CAVs) are expected to enhance traffic efficiency by driving at shorter time headways, and traffic safety by shorter reaction times. However, one of the main concerns regarding their deployment is the mixed traffic situation, in which CAVs and manually driven vehicles (MVs) share the same road.This study investigates the behavioural adaptation of MV drivers in car-following and lane changing behaviour when they drive next to a dedicated lane (DL) for CAVs and compares that to a mixed traffic situation. The expectation is that in a mixed traffic situation, the behavioural adaptation of MV drivers is negligible due to lower exposure time and scarce platoons, while concentrating the CAVs on one dedicated lane may cause significant behavioural adaptation of MV drivers due to a higher exposure time and conspicuity of CAV platoons.Fifty-one participants were asked to drive an MV on a 3-lane motorway in three different traffic scenarios, in a fixed-base driving simulator: (1) Base, only MVs were present in traffic, (2) Mixed, platoons of 2–3 CAVs driving on any lane and mixed with MVs, (3) DL, platoons of 2–3 CAVs driving only on a DL. The DL was recognizable by road signs and a buffer demarcation which separated the DL from the other lanes. A moderate penetration rate of 43% was assumed for CAVs.During the drives, the car following headways and the accepted merging gaps by participants were collected and used for comparisons of driving behaviour in different scenarios.Based on the results, we conclude that there is no significant difference in the driving behaviour between Base and Mixed scenarios at tested penetration rate, confirming our research expectation. However, in DL scenario, MV drivers drove closer to their leaders specially when driving on the middle lane next to the platoons and accepted shorter gaps (up to 12.7% shorter at on-ramps) in lane changing manoeuvres. Dedicating a lane to CAVs increases the density of CAV platoons on one lane and consequently their conspicuity becomes higher. As a result, MV drivers are influenced by CAV platoons on a DL and imitate their behaviour.The literature suggests that dedicating a lane to CAVs improves the traffic efficiency by providing more possibilities for platooning. This study shows that implementing such a solution will affect the driving behaviour of human drivers. This should be taken into consideration when evaluating the impacts of dedicated lanes on traffic efficiency and traffic safety.     

Enhancing dynamic graphical analysis with the Lisp-Stat language and the ViSta statistical program

Presented is a sample of computerized methods aimed at multidimensional scaling and psychometric item analysis that offer a dynamic graphical interface to execute analyses and help visualize the results. These methods show how the Lisp-Stat programming language and the ViSta statistical program can be jointly applied to develop powerful computer applications that enhance dynamic graphical analysis methods. The feasibility of this combined strategy relies on two main features: (1) The programming architecture of ViSta enables users to add new statistical methods as plug-ins, which are integrated into the program environment and can make use of all the functions already available in ViSta (e.g., data manipulation, editing, printing); and (2) the set of powerful statistical and graphical functions integrated into the Lisp-Stat programming language provides the means for developing statistical methods with dynamic graphical visualizations, which can be implemented as ViSta plug-ins.     

Classical item and test analysis with graphics: The ViSta-CITA program

Current advances in test development theory have mostly been influenced by item response theory. Notwithstanding this, classical test theory still plays a major part in the development of tests for applied educational and behavioral research. This article describes ViSta-CITA, a computer program that implements a set of classical item and test analysis methods that incorporate innovative graphics whose aim is to provide deeper insight into analysis results. Such an aim is achieved through the SpreadPlot, a graphical method designed to display multiple, simultaneous, interactive views of the analysis results. It behaves on a dynamic basis, so that users’ changes (e.g., selecting a subset of items) are automatically updated in the graphical windows showing the analysis results. Moreover, ViSta-CITA is freely available, and its code is open to modifications or additions by the user. Features such as these constitute useful tools for research and teaching purposes related to test development.     

Bayesian inference for graphical factor analysis models

We generalize factor analysis models by allowing the concentration matrix of the residuals to have nonzero off-diagonal elements. The resulting model is named graphical factor analysis model. Allowing a structure of associations gives information about the correlation left unexplained by the unobserved variables, which can be used both in the confirmatory and exploratory context. We first present a sufficient condition for global identifiability of this class of models with a generic number of factors, thereby extending the results in Stanghellini (1997) and Vicard (2000). We then consider the issue of model comparison and show that fast local computations are possible for this purpose, if the conditional independence graphs on the residuals are restricted to be decomposable and a Bayesian approach is adopted. To achieve this aim, we propose a new reversible jump MCMC method to approximate the posterior probabilities of the considered models. We then study the evolution of political democracy in 75 developing countries based on eight measures of democracy in two different years. We acknowledge support from M.U.R.S.T. of Italy and from the European Science Foundation H.S.S.S. Network. We are grateful to the referees and the Editor for many useful suggestions and comments which led to a substantial improvement of the paper. We also thank Nanny Wermuth for stimulating discussions and Kenneth A. Bollen for kindly providing us with the data-set.     

Logistic growth curve analysis in associative learning data

We propose an alternative statistical method, logistic growth curve analysis, for the analysis of associative learning data with two or more comparison groups. Logistic growth curve analysis is more sensitive and easier to interpret than previously published methods such as χ² or ANOVA, which require the data to be collapsed into individual total scores or proportion of responses over time. Additionally, this type of analysis better fits the typical graphical representation of associative learning data. An analysis is presented where associative learning data from honeybees are analyzed using the three techniques, and the accessibility and power of the logistic growth curve analysis is highlighted. Accepted after revision: 14 November 2000 Electronic Publication     

A noniterative method of joint correspondence analysis

Correspondence analysis leads to a graphical representation of the associations between categories of the row and column variables of a contingency table. Greenacre's (1988) formulation of joint correspondence analysis is a multivariate extension which finds the optimal joint display of contingency tables between all pairs of variables in a set. Greenacre presented a discrepancy function and an alternating least squares algorithm for its minimization. Boik (1996) presented an alternative algorithm, also of the alternating least squares type, for minimizing the same discrepancy function. In this paper, a noniterative procedure, not based on the minimization of any discrepancy function, is described.     

Support vector machines categorize the scaling of human grip configurations

In previous work (Cesari & Newell, 2002), we used a graphical dimensional analysis to show that grip transitions obey the body-scaled relation K = lnL(o) + InM(o)h/(a + bM(h) + cL(h)), where L. and Mo are the object's length and mass, and Lh and Mh the length and mass of the grasper's hand. However, the generality of the equation was limited by the ad hoc graphical method that defined the lines for grip separation and by the assumption that these lines be negatively sloped and parallel to one another. This article reports an independent test of this relation by the geometrical and statistical categorization of body-scaled invariants for the transition of human grip configurations through support vector machines (SVMs). The SVM analysis confirmed the fit of linear, negatively sloped, and approximately parallel transition boundaries in the scaling of human grip configuration within a single hand. The SVM analysis has provided a theoretical refinement to the scaling model of human grip configurations.     

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.     

Decompositions and biplots in three-way correspondence analysis

In this paper correspondence analysis for three-way contingency tables is presented using three-way generalisations of the singular value decomposition. It is shown that in combination with Lancaster's (1951) additive decomposition of interactions in three-way tables, a detailed analysis is possible of the deviations from independence. Finally, biplots are shown to produce powerful graphical representations of the results from three-way correspondence analyses. An example from child development is used to illustrate the theoretical developments.     

Rotation in Correspondence Analysis from the Canonical Correlation Perspective

Psychometrika - Correspondence analysis (CA) is a statistical method for depicting the relationship between two categorical variables, and usually places an emphasis on graphical representations....     

A graphical method to aid the sequential analysis of observational data

In this paper, two methods of sequential analysis are applied to hypothetical observational data. The first method employs the conventional “conditional probability” approach, illustrated using the GSEQ program (Bakeman & Quera, 1995). In order to overcome some of the difficulties associated with the conditional probability approach, the second method employs a new “normalized and pooled” approach. Essentially, by normalizing periods of time preceding, during, and following each occurrence of a nominated “given” behavior, the proportion of time units devoted to a “target” behavior can be estimated and then pooled across all occurrences of the given behavior. A summary diagram representing the likelihood that the target behavior precedes, occurs concurrently with, and follows the given behavior can then be constructed. Elements of this summary diagram can also be quantified. Given the graphical nature of the output, and its ease of use, the normalized and pooled approach may help to promote the use of sequential analysis in applied settings.     

The Effectiveness of Alternative Preference Elicitation Methods in the Analytic Hierarchy Process

This study compares alternative preference elicitation methods that are currently available in software implementations of the analytic hierarchy process. For the simple problem used in this study, the elicitation methods may be sorted from least to most accurate as follows: (1) direct estimation, (2) graphical multiple bars, (3) graphical pairwise, (4) numeric pairwise and (5) verbal pairwise. However, the most accurate methods are not the easiest to use. Furthermore, actual accuracy differed substantially from users’ perceptions, indicating a need to assist the users in the selection of an appropriate elicitation method. © 1997 John Wiley & Sons, Ltd.     

An R package for state-trace analysis

State-trace analysis (Bamber, Journal of Mathematical Psychology, 19, 137-181, 1979) is a graphical analysis that can determine whether one or more than one latent variable mediates an apparent dissociation between the effects of two experimental manipulations. State-trace analysis makes only ordinal assumptions and so, is not confounded by range effects that plague alternative methods, especially when performance is measured on a bounded scale (such as accuracy). We describe and illustrate the application of a freely available GUI driven package, StateTrace, for the R language. StateTrace automates many aspects of a state-trace analysis of accuracy and other binary response data, including customizable graphics and the efficient management of computationally intensive Bayesian methods for quantifying evidence about the outcomes of a state-trace experiment, developed by Prince, Brown, and Heathcote (Psychological Methods, 17, 78-99, 2012).     

Reversed dimensional analysis in psychophysics

It is argued that dimensional analysis (from physics) can be applied in psychophysics in the same manner as in physics, provided that the dimensions of sensations are interpreted in the sense of reversed dimensional analysis, which allows for extracting dimensions from data. A dimension obtained by this method, referred to as phenomenological dimension, is similar to a fractal dimension. The examples discussed show that, if the dimension of sensation in Stevens' psychophysical law for time duration (psi = Cphin, n approximately 1.15) is interpreted as a phenomenological dimension, such a dimension can be traced even in short-term memory data. It is suggested that dimensions obtained via reversed dimensional analysis may serve as a link between physical and psychological variables and as a basis for developing the notion of dimension in psychology.     

风险寻求中的图形表征效应

在负性风险信息沟通中,采用文本表征与图形表征,结果发现图形表征方式更能引起风险回避行为。基于此,本研究以获益方案作为风险沟通信息,分别采用文本表征与图形表征来探索信息表征方式对风险寻求的影响。结果显示:在文本表征方式中,个体决策主要受备择方案之间风险大小的影响;而图形表征方式中,个体不仅受备择方案之间风险大小的影响,而且更受备择方案之间获益大小的影响。结果说明:相对文本表征,图形表征方式更能引起决策者为了获益而冒更大的风险,从而表现出风险寻求偏好,从而证实"图形效应"在风险决策中存在普遍性,为我们风险决策信息提供依据。     

RTSYS: A DOS application for the analysis of reaction time data

RTSYS is a menu-driven DOS application for the manipulation, analysis, and graphical display of reaction time data. It can be used either in a single-task environment under DOS, with access to a set operating system commands, or as an application under Windows. All functions have context-sensitive help. RTSYS fits the ex-Gaussian distribution to reaction time data without the difficulties usually associated with numerical parameter estimation. Distribution fitting and flexible censoring and rescaling options allow RTSYS to address the problems of reaction time distribution skew and outlying responses with reasonable sample sizes. RTSYS can automatically process multiple input files from experiments with arbitrary designs and produce formatted output of statistics for further processing by graphical and inferential statistical packages. The present article reviews and explains techniques used by RTSYS and provides an overview of the operation of the program.     

An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents’ preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables while the latter is used for identifying relatively homogeneous clusters of respondents. The proposed method offers an integrated graphical display that provides information on cluster-based structures inherent in multivariate categorical data as well as the interdependencies among the data. An empirical application is presented which demonstrates the usefulness of the proposed method and how it compares to several extant approaches. The work reported in this paper was supported by Grant 290439 and Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the first and third authors, respectively. We wish to thank Ulf B?ckenholt, Paul Green, and Marc Tomiuk for their insightful comments on an earlier version of this paper. We also wish to thank Byunghwa Yang for generously providing us with his data.     

InterFace: A software package for face image warping,averaging, and principal components analysis

We describe InterFace, a software package for research in face recognition. The package supports image warping, reshaping, averaging of multiple face images, and morphing between faces. It also supports principal components analysis (PCA) of face images, along with tools for exploring the “face space” produced by PCA. The package uses a simple graphical user interface, allowing users to perform these sophisticated image manipulations without any need for programming knowledge. The program is available for download in the form of an app, which requires that users also have access to the (freely available) MATLAB Runtime environment.