Microscopic modeling and control logic for incident-responsive automatic vehicle movements in single-automated-lane highway systems

Automatic response to lane-blocking incidents is a critical issue in the field of automated highway systems (AHS). Accordingly, this paper presents a microscopic vehicular control methodology for automatic-control (AC) vehicular movements in response to lane-blocking incidents in the AHS environment. The embedded traffic control logic is based on the basic safety requirements for automatic-control lane traffic maneuvers responding to lane-blocking incidents in the single-automated-lane AHS environment. Accordingly, respective automated vehicular control models are proposed to deal with AC vehicles moving in three corresponding sequential phases, i.e., (1) AC platoon approaching the incident site from the blocked lane, (2) mandatory lane changing and mixed car following in the adjacent lane, and (3) AC platoon reforming downstream from the incident site in the blocked automated lane. Using a microscopic simulation model which embeds these proposed models, preliminary tests are conducted to investigate the relative performance of the proposed method in various traffic flow and control scenarios. The resulting numerical results, including simplified sensitivity analyses, indicate that the proposed microscopic traffic control logic permits regulating automatic-control vehicular movements in response to the effects of lane-blocking incidents on traffic flows either in control-free lanes or in the automatic-control lanes. Implications of the results and some findings are discussed for further research.     

Stability of interconnected impulsive switched systems subject to state dimension variation

The contribution of this article is twofold. First we deal with the stability of continuous-time interconnected impulsive switched systems for which the dimension of the system’s state vector may change at different modes. A dwell time condition is derived to ensure the exponential convergence of the state trajectories, and when the system is subject to a non-vanishing perturbation, a superior bound of the state trajectories is provided as well. The main advantage of the solution we propose is its direct application to practical fields such as metallurgy or traffic control through the use of semi-definite programming solvers. Second, we introduce in the framework a platoon of vehicles in automated highway systems where vehicles may join or leave the platoon. Then, we detail the longitudinal stability problem of such a system and illustrate the features of the proposed stability conditions through numerical simulations.     

Ein SIMULA-Modell zur Ereignissimulation von Stadtstraßennetzen

Zusammenfassung Die Grundkonzepte eines semimakroskopischen, stochastischen und ereignisorientierten Simulationsmodells für Stadtstraßennetze werden entwickelt. Dabei liegt das Schwergewicht auf dem Fahrverhaltensmodell, Fahrfolgeverhalten an Kreuzungen und Pulkauflösung. Das Programm wurde in SIMULA geschrieben und kann zur Simulation von Stadtstraßennetzen verwendet werden.

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Summary The fundamental concepts for a semimakroscopic, stochastic and eventoriented simulation model of the traffic in an urban area are developed. Special attention is paid to vehicle movement, queue discharge and platoon dispersion. The program was written in SIMULA and can be used for the simulation of urban networks up to 80 nodes.

     

An EM algorithm for platoon arrival processes in discrete time

The platoon arrival process (PAP), a special case of Markovian arrival process (MAP), occurs in several practical queueing systems. Developing procedures for estimating its parameters is essential in order to successfully use it for representing arrival processes in real systems. We present an EM-based procedure for estimating the parameters of a PAP.     

A cognitively based simulation of academic science

The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between the model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights. Isaac Naveh obtained a master’s degree in computer science at the University of Missouri. His research interests include hybrid cognitive models and multi-agent learning. Ron Sun is Professor of Cognitive Science at Rensselaer Polytechnic Institute, and formerly the James C. Dowell Professor of Engineering and Professor of Computer Science at University of Missouri-Columbia. He received his Ph.D in 1992 from Brandeis University. His research interest centers around studies of cognition, especially in the areas of cognitive architectures, human reasoning and learning, cognitive social simulation, and hybrid connectionist models. For his paper on integrating rule-based and connectionist models for accounting for human everyday reasoning, he received the 1991 David Marr Award from Cognitive Science Society. He is the founding co-editor-in-chief of the journal Cognitive Systems Research, and also serves on the editorial boards of many other journals. He is the general chair and program chair for CogSci 2006, and a member of the Governing Board of International Neural Networks Society. His URL is: http://www.cogsci.rpi.edu/~rsun     

A problem-structuring model for analyzing transportation–environment relationships

This study discusses a decision support framework that guides policy makers in their strategic transportation related decisions by using multi-methodology. For this purpose, a methodology for analyzing the effects of transportation policies on environment, society, economy, and energy is proposed. In the proposed methodology, a three-stage problem structuring model is developed. Initially, experts’ opinions are structured by using a cognitive map to determine the relationships between transportation and environmental concepts. Then a structural equation model (SEM) is constructed, based on the cognitive map, to quantify the relations among external transportation and environmental factors. Finally the results of the SEM model are used to evaluate the consequences of possible policies via scenario analysis. In this paper a pilot study that covers only one module of the whole framework, namely transportation–environment interaction module, is conducted to present the applicability and usefulness of the methodology. This pilot study also reveals the impacts of transportation policies on the environment. To achieve a sustainable transportation system, the extent of the relationships between transportation and the environment must be considered. The World Development Indicators developed by the World Bank are used for this purpose.     

The value of cognitive foundations for dynamic social theory

It is possible to develop models of social behavior that are predicated on detailed mechanical models of cognition. Cognitively based social models are potentially unified theoretical frameworks that can be used to explain a wide variety of social phenomena. Moreover, if a knowledge representation scheme and a knowledge acquisition scheme are specified in the underlying cognitive model then it is possible to produce a dynamic social model. The resulting social model can thus be used to predict and explain not only conditions for specific behaviors but changes in those behaviors over time.

Constructuralism is a theory of social behavior that rests on a cognitive model. The cognitive model specified has a knowledge representation scheme, knowledge acquisition procedures, and control procedures for shifting cognitive attention. The resulting social model is a dynamic model that can be used to explain both conditions for the occurrence of a behavior and social and individual changes that accrue do to a series of behaviors. The explanatory breadth of the model is illustrated by looking at predictions about a variety of social phenomena including: development of shared knowledge, identical behavior by members of the society, foreign language acquisition, clique formation, civil disobedience, and diffusion of innovative information.     

A cognitive model of spatial path-planning

Planning a path to a destination, given a number of options and obstacles, is a common task. We suggest a two-component cognitive model that combines retrieval of knowledge about the environment with search guided by visual perception. In the first component, subsymbolic information, acquired during navigation, aids in the retrieval of declarative information representing possible paths to take. In the second component, visual information directs the search, which in turn creates knowledge for the first component. The model is implemented using the ACT-R cognitive architecture and makes realistic assumptions about memory access and shifts in visual attention. We present simulation results for memory-based high-level navigation in grid and tree structures, and visual navigation in mazes, varying relevant cognitive (retrieval noise and visual finsts) and environmental (maze and path size) parameters. The visual component is evaluated with data from a multi-robot control experiment, where subjects planned paths for robots to explore a building. We describe a method to compare trajectories without referring to aligned points in the itinerary. The evaluation shows that the model provides a good fit, but also that planning strategies may vary with task loads.     

A Bayesian causal map for inflation analysis: The case of Turkey

This paper proposes the use of Bayesian Causal Maps (BCM’s) to analyze the complex structure of inflation in Turkey. In this study, a model of inflation is initially structured using a cognitive mapping technique; the dependent probabilities of the concepts are then calculated based on the detailed analysis of past data. Finally, a BCM is used to analyze the complex structure of inflation in Turkey. As a result, it will be possible to see the structure of the inflation model and to understand the basic consequences of any strategic change that may occur in the system.     

在线知识社区中基于个体异质性的知识与社会系统协同演化研究

在Web 2.0环境下,在线知识社区(Online Knowledge Community, OKC)已成为人们进行学习、利用、分享、传播知识的重要平台。然而,现有关于OKC的研究较多关注其中社会系统对个体知识建构、群体知识建构的影响,缺少从OKC演化的视角,以用户为基础对OKC中社会系统与知识系统间双向交互影响规律的研究。为此,本文将个体异质性作为影响因素引入到OKC的研究中,在一个开放的在线知识社区中模拟个体的观点、认知结构以及个体间形成的社会关系与知识系统的共同演化。将个体间以信任为基础形成的关系网络视为OKC中的社会系统,将群体依据自身认知结构表达出的全部观点视为社区中的知识系统,进而采取了社会科学计算实验的研究方法构建了一个OKC中社会系统与知识系统协同演化模型,并在模型中引入了个体的内在和外在异质性作为影响因素。研究结果表明OKC中个体的学习能力、容忍度、活跃度等个体因素,对其中知识观点的传播与社区中社会网络的演化影响显著。本研究希望能够为OKC中知识的自组织、序化的研究提供理论支持。     

多种分布下选择后变量显著性分析及其在CEPS数据中的应用

在使用变量选择方法选出模型后,如何评价模型中变量系数的显著性是统计学重点关注的前沿问题之一.文章从适应性Lasso变量选择方法的选择结果出发,在考虑实践中误差分布多样性的前提下,基于选择事件构造了模型保留变量系数的条件检验统计量,并给出了该统计量的一致收敛性质的证明过程.模拟研究显示,在多种误差分布下所提方法均可进一步优化变量选择结果,有较强的实用价值.应用此方法对CEPS学生数据进行了实证分析,最终选取了学生认知能力等10个变量作为影响中学生成绩的主要因素,为相关研究提供了有益的参考.     

Computing solutions to algebraic problems using a symbolic versus a schematic strategy

To improve access to algebraic word problems, primary aged students in Singapore are taught to utilise schematic models. Symbolic algebra is not taught until the secondary school years. To examine whether the two methods drew on different cognitive processes and imposed different cognitive demands, we used functional magnetic resonance imaging to examine patterns of brain activation whilst problem solvers were using the two methods. To improve our ability to detect differences attributable to the two methods, rather than participant’s abilities to use the two methods, we used adult problem solvers who had high levels of competency in both methods. In a previous study, we focused on the initial stages of problem solving: translating word problems into either schematic or symbolic representations (Lee et al. in Brain Res 1155:163–171, 2007). In this study, we focused on the later stages of problem solving: in computing numeric solutions from presented schematic or symbolic representations. Participants were asked to solve simple algebraic questions presented in either format. Greater activation in the symbolic method was found in the middle and medial frontal gyri, anterior cingulate, caudate, precuneus, and intraparietal sulcus. Greater activation in the model condition was found largely in the occipital areas. These findings suggest that generating and computing solutions from symbolic representations require greater general cognitive and numeric processing resources than do processes involving model representations. Differences between the two methods appear to be of both a quantitative and qualitative nature.     

A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information

The efficiency of banks has a critical role in development of sound financial systems of countries. Data Envelopment Analysis (DEA) has witnessed an increase in popularity for modeling the performance efficiency of banks. Such efficiency depends on the appropriate selection of input and output variables. In literature, no agreement exists on the selection of relevant variables. The disagreement has been an on-going debate among academic experts, and no diagnostic tools exist to identify variable misspecifications. A cognitive analytics management framework is proposed using three processes to address misspecifications. The cognitive process conducts an extensive review to identify the most common set of variables. The analytics process integrates a random forest method; a simulation method with a DEA measurement feedback; and Shannon Entropy to select the best DEA model and its relevant variables. Finally, a management process discusses the managerial insights to manage performance and impacts. A sample of data is collected on 303 top-world banks for the periods 2013 to 2015 from 49 countries. The experimental simulation results identified the best DEA model along with its associated variables, and addressed the misclassification of the total deposits. The paper concludes with the limitations and future research directions.

     

A fuzzy approach for selecting project membership to achieve cognitive style goals

Decision makers select employees for a project to match a particular set of goals pertaining to the multiple criteria mix of skills and competencies needed. Cognitive style influences how a person gathers and evaluates information and consequently, provides skills and competencies toward problem solving. The proposed fuzzy set-based model facilitates the manager’s selection of employees who meet the project goal(s) for the preferred cognitive style. The paper presents background information on cognitive styles and fuzzy logic with an algorithm developed based on belief in the fuzzy probability of a cognitive style fitting a defined goal. An application is presented with analysis and conclusions stated.     

Cognitive trajectory of proof by contradiction for transition-to-proof students

History and research on proof by contradiction suggests proof by contradiction is difficult for students in a number of ways. Students’ comprehension of already-written proofs by contradiction is one such aspect that has received relatively little attention. Applying the cognitive lens of Action-Process-Object-Schema (APOS) Theory to proof by contradiction, we constructed and tested a cognitive model that describes how a student might construct the concept ‘proof by contradiction’ in an introduction to proof course. Data for this study was collected from students in a series of five teaching interventions focused on proof by contradiction. This paper will report on two participants as case studies to illustrate that our cognitive trajectory for proof by contradiction is a useful model for describing how students may come to understand the proof method.     

Modeling Relationships among Multiple Graphical Structures

Many researchers have investigated the social and cognitive processes underlying organizational behavior, with particular interest in understanding the interaction between the social and cognitive dimensions. Because of the widespread use of graphs as models of social and cognitive structures, these studies frequently encounter the problem of analyzing collections of graphical structures. Such analyses have used a variety of approaches to address specific aspects of such structures. However, no single unified approach has emerged that supports the several different types of analyses required. The purpose of this paper is to define such an approach, based on a mathematical model for capturing the relationships among multiple graphs, and to demonstrate its application to the investigation of social and cognitive structures in organizations.     

基于因子分析的元认知外语教学策略研究

从心理学、第二语言习得理论出发,研究了场独立与场依存认知风格的外语学习者特点,应用因子分析数学模型,进行了培养元认知策略意识及发展双重认知风格等教学策略的教学实验,仿真实验表明了该方法的实用性和有效性.     

The Structure of Cognitive Agency

Credit theories of knowledge have to explain the conditions under which beliefs are attributable to cognitive agents. The most promising way to explain these conditions is to offer an account of cognitive agency that is a plausible development of the uncontroversial notion that we are believing subjects. This article develops and defends a Structuralist model of cognitive agency.     

Introducing technology in algebra in Hong Kong: addressing issues in learning

A review of recent studies in Hong Kong suggests that possible problems in secondary school algebra may be due to the procedural paradigm orientation in the curriculum and the conventional style of teaching in the classroom which do not provide sufficient opportunities for students to develop conceptual understanding. Based on the works of a number of projects in the West, it is hypothesized that the introduction of technology in lessons which embody a cognitive model in their design and delivery will provide a viable alternative for enhancing algebraic thinking. The key features of the cognitive model are concrete preparation, cognitive conflict, construction, metacognition and bridging, imbedded in a ‘mediation’ style of teaching. These features are exemplified by detailed accounts of classroom episodes from a Hong Kong lesson supported by the use of graphics calculators. Results indicate that while the approach places particular demands on teachers (a tension between a transmission style of teaching and mediating) there is real potential for supporting more dynamic student constructions.