A large-scale real-life crowd steering experiment via arrow-like stimuli

We introduce "Moving Light": an unprecedented real-life crowd steering experiment that involved about 140.000 participants among the visitors of the Glow 2017 Light Festival (Eindhoven, NL). Moving Light targets one outstanding question of paramount societal and technological importance: "can we seamlessly and systematically influence routing decisions in pedestrian crowds?" Establishing effective crowd steering methods is extremely relevant in the context of crowd management, e.g. when it comes to keeping floor usage within safety limits (e.g. during public events with high attendance) or at designated comfort levels (e.g. in leisure areas). In the Moving Light setup, visitors walking in a corridor face a choice between two symmetric exits defined by a large central obstacle. Stimuli, such as arrows, alternate at random and perturb the symmetry of the environment to bias choices. While visitors move in the experiment, they are tracked with high space and time resolution, such that the efficiency of each stimulus at steering individual routing decisions can be accurately evaluated a posteriori. In this contribution, we first describe the measurement concept in the Moving Light experiment and then we investigate quantitatively the steering capability of arrow indications.Comment: 8 page

Bank Networks from Text: Interrelations, Centrality and Determinants

In the wake of the still ongoing global financial crisis, bank interdependencies have come into focus in trying to assess linkages among banks and systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discourse. We present a text-to-network process, which has its basis in co-occurrences of bank names and can be analyzed quantitatively and visualized. To quantify bank importance, we propose an information centrality measure to rank and assess trends of bank centrality in discussion. For qualitative assessment of bank networks, we put forward a visual, interactive interface for better illustrating network structures. We illustrate the text-based approach on European Large and Complex Banking Groups (LCBGs) during the ongoing financial crisis by quantifying bank interrelations and centrality from discussion in 3M news articles, spanning 2007Q1 to 2014Q3.Comment: Quantitative Finance, forthcoming in 201

Impact of Advanced Synoptics and Simplified Checklists During Aircraft Systems Failures

AbstractNatural human capacities are becoming increasingly mismatched to the enormous data volumes, processing capabilities, and decision speeds demanded in todays aviation environment. Increasingly Autonomous Systems (IAS) are uniquely suited to solve this problem. NASA is conducting research and development of IAS - hardware and software systems, utilizing machine learning algorithms, seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. IAS offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. A human-in-the-loop test was conducted in NASA Langleys Integration Flight Deck B-737-800 simulator to evaluate advanced synoptic pages with simplified interactive electronic checklists as an IAS for routine air carrier flight operations and in response to aircraft system failures. Twelve U.S. airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to failures. These data are fundamental to and critical for the design and development of future increasingly autonomous systems that can better support the human in the cockpit. Synoptic pages and electronic checklists significantly improved pilot responses to non-normal scenarios, but implementation of these aids and other intelligent assistants have barriers to implementation (e.g., certification cost) that must overcome

Quantifying Information Leaks Using Reliability Analysis

acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4We report on our work-in-progress into the use of reliability analysis to quantify information leaks. In recent work we have proposed a software reliability analysis technique that uses symbolic execution and model counting to quantify the probability of reaching designated program states, e.g. assert violations, under uncertainty conditions in the environment. The technique has many applications beyond reliability analysis, ranging from program understanding and debugging to analysis of cyber-physical systems. In this paper we report on a novel application of the technique, namely Quantitative Information Flow analysis (QIF). The goal of QIF is to measure information leakage of a program by using information-theoretic metrics such as Shannon entropy or Renyi entropy. We exploit the model counting engine of the reliability analyzer over symbolic program paths, to compute an upper bound of the maximum leakage over all possible distributions of the confidential data. We have implemented our approach into a prototype tool, called QILURA, and explore its effectiveness on a number of case studie

Model of Coordination Flow in Remote Collaborative Interaction

© 2015 IEEEWe present an information-theoretic approach for modelling coordination in human-human interaction and measuring coordination flows in a remote collaborative tracking task. Building on Shannon's mutual information, coordination flow measures, for stochastic collaborative systems, how much influence, the environment has on the joint control of collaborating parties. We demonstrate the application of the approach on interactive human data recorded in a user study and reveal the amount of effort required for creating rigorous models. Our initial results suggest the potential coordination flow has - as an objective, task-independent measure - in supporting designers of human collaborative systems and in providing better theoretical foundations for the science of Human-Computer Interaction

Fine-grained traffic state estimation and visualisation

Tools for visualising the current traffic state are used by local authorities for strategic monitoring of the traffic network and by everyday users for planning their journey. Popular visualisations include those provided by Google Maps and by Inrix. Both employ a traffic lights colour-coding system, where roads on a map are coloured green if traffic is flowing normally and red or black if there is congestion. New sensor technology, especially from wireless sources, is allowing resolution down to lane level. A case study is reported in which a traffic micro-simulation test bed is used to generate high-resolution estimates. An interactive visualisation of the fine-grained traffic state is presented. The visualisation is demonstrated using Google Earth and affords the user a detailed three-dimensional view of the traffic state down to lane level in real time

Towards a new ITU-T recommendation for subjective methods evaluating gaming QoE

This paper reports on activities in Study Group 12 of the International Telecommunication Union (ITU-T SG12) to define a new Recommendation on subjective evaluation methods for gaming Quality of Experience (QoE). It first resumes the structure and content of the current draft which has been proposed to ITU-T SG12 in September 2014 and then critically discusses potential gaming content and evaluation methods for inclusion into the upcoming Recommendation. The aim is to start a discussion amongst experts on potential evaluation methods and their limitations, before finalizing a Recommendation. Such a recommendation might in the end be applied by non -expert users, hence wrong decisions in the evaluation design could negatively affect gaming QoE throughout the evaluation