First attempt to build realistic driving scenes using video-to-video synthesis in OpenDS framework

Existing programmable simulators enable researchers to customize different driving scenarios to conduct in-lab automotive driver simulations. However, software-based simulators for cognitive research generate and maintain their scenes with the support of 3D engines, which may affect users' experiences to a certain degree since they are not sufficiently realistic. Now, a critical issue is the question of how to build scenes into real-world ones. In this paper, we introduce the first step in utilizing video-to-video synthesis, which is a deep learning approach, in OpenDS framework, which is an open-source driving simulator software, to present simulated scenes as realistically as possible. Off-line evaluations demonstrated promising results from our study, and our future work will focus on how to merge them appropriately to build a close-to-reality, real-time driving simulator

Building BROOK: A multi-modal and facial video database for Human-Vehicle Interaction research

With the growing popularity of Autonomous Vehicles, more opportunities have bloomed in the context of Human-Vehicle Interactions. However, the lack of comprehensive and concrete database support for such specific use case limits relevant studies in the whole design spaces. In this paper, we present our work-in-progress BROOK, a public multi-modal database with facial video records, which could be used to characterise drivers' affective states and driving styles. We first explain how we over-engineer such database in details, and what we have gained through a ten-month study. Then we showcase a Neural Network-based predictor, leveraging BROOK, which supports multi-modal prediction (including physiological data of heart rate and skin conductance and driving status data of speed) through facial videos. Finally we discuss related issues when building such a database and our future directions in the context of BROOK. We believe BROOK is an essential building block for future Human-Vehicle Interaction Research. More details and updates about the project BROOK is online at https: //unnc-idl-ucc.github.io/BROOK/

Building BROOK: A multi-modal and facial video database for Human-Vehicle Interaction research

With the growing popularity of Autonomous Vehicles, more opportunities have bloomed in the context of Human-Vehicle Interactions. However, the lack of comprehensive and concrete database support for such specific use case limits relevant studies in the whole design spaces. In this paper, we present our work-in-progress BROOK, a public multi-modal database with facial video records, which could be used to characterise drivers' affective states and driving styles. We first explain how we over-engineer such database in details, and what we have gained through a ten-month study. Then we showcase a Neural Network-based predictor, leveraging BROOK, which supports multi-modal prediction (including physiological data of heart rate and skin conductance and driving status data of speed) through facial videos. Finally we discuss related issues when building such a database and our future directions in the context of BROOK. We believe BROOK is an essential building block for future Human-Vehicle Interaction Research. More details and updates about the project BROOK is online at https: //unnc-idl-ucc.github.io/BROOK/

PRESTK : situation-aware presentation of messages and infotainment content for drivers

The amount of in-car information systems has dramatically increased over the last few years. These potentially mutually independent information systems presenting information to the driver increase the risk of driver distraction. In a first step, orchestrating these information systems using techniques from scheduling and presentation planning avoid conflicts when competing for scarce resources such as screen space. In a second step, the cognitive capacity of the driver as another scarce resource has to be considered. For the first step, an algorithm fulfilling the requirements of this situation is presented and evaluated. For the second step, I define the concept of System Situation Awareness (SSA) as an extension of Endsley’s Situation Awareness (SA) model. I claim that not only the driver needs to know what is happening in his environment, but also the system, e.g., the car. In order to achieve SSA, two paths of research have to be followed: (1) Assessment of cognitive load of the driver in an unobtrusive way. I propose to estimate this value using a model based on environmental data. (2) Developing model of cognitive complexity induced by messages presented by the system. Three experiments support the claims I make in my conceptual contribution to this field. A prototypical implementation of the situation-aware presentation management toolkit PRESTK is presented and shown in two demonstrators.In den letzten Jahren hat die Menge der informationsanzeigenden Systeme im Auto drastisch zugenommen. Da sie potenziell unabhängig voneinander ablaufen, erhöhen sie die Gefahr, die Aufmerksamkeit des Fahrers abzulenken. Konflikte entstehen, wenn zwei oder mehr Systeme zeitgleich auf limitierte Ressourcen wie z. B. den Bildschirmplatz zugreifen. Ein erster Schritt, diese Konflikte zu vermeiden, ist die Orchestrierung dieser Systeme mittels Techniken aus dem Bereich Scheduling und Präsentationsplanung. In einem zweiten Schritt sollte die kognitive Kapazität des Fahrers als ebenfalls limitierte Ressource berücksichtigt werden. Der Algorithmus, den ich zu Schritt 1 vorstelle und evaluiere, erfüllt alle diese Anforderungen. Zu Schritt 2 definiere ich das Konzept System Situation Awareness (SSA), basierend auf Endsley’s Konzept der Situation Awareness (SA). Dadurch wird erreicht, dass nicht nur der Fahrer sich seiner Umgebung bewusst ist, sondern auch das System (d.h. das Auto). Zu diesem Zweck m¨ussen zwei Bereiche untersucht werden: (1) Die kognitive Belastbarkeit des Fahrers unaufdringlich ermitteln. Dazu schlage ich ein Modell vor, das auf Umgebungsinformationen basiert. (2) Ein weiteres Modell soll die Komplexität der präsentierten Informationen bestimmen. Drei Experimente stützen die Behauptungen in meinem konzeptuellen Beitrag. Ein Prototyp des situationsbewussten Präsentationsmanagement-Toolkits PresTK wird vorgestellt und in zwei Demonstratoren gezeigt

Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems

While emerging technology for self-driving automation in vehicles progresses rapidly, the transition to an era of roads full of fully connected and automated vehicles (CAVs) may take longer than expected. Until then, it is inevitable that CAVs should coexist and interact with drivers of non-autonomous vehicles (NAVs) in urban roads. During this period of transition, it is critical to provide road safety with the mixed vehicular traffic and uncertainty caused by human drivers. To investigate the issues caused by the coexistence and interaction with humans, we propose to build a component-based and interactive intelligent transportation cyber-physical systems (ITCPS) framework. Our design of the interactive ITCPS framework aims to provide a standardized structure for users by defining core components. The framework is specified by behavior models and interfaces for the desired ITCPS components and is implemented as a form of human and hardware-in-the-loop system. We developed an intersection crossing assistance service and an automatic emergency braking service as an example of practical applications using the framework. To evaluate the framework, we tested its performance to show how effectively it operates while supporting real-time processing. The results indicate that it satisfies the timing requirements of vehicle-to-vehicle (V2V) communication and the limited processing time required for performing the functions of behavior models, even though the traffic volume reaches the road capacity. A case study using statistical analysis is conducted to assess the practical value of the developed experimental environment. The results of the case study validate the reliability among the specified variables for the experiments involving human drivers. It has shown that V2V communication support has positive effects on road safety, including intersection safety, braking events, and perception-reaction time (PRT) of the drivers. Furthermore, V2V communication support and PRT are identified as the important indicators affecting road safety at an un-signalized intersection. The proposed interactive framework is expected to contribute in constructing a comprehensive environment for the urban ITCPS and providing experimental support for the analysis of human behavior in the coexistence environment. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida