Electrogastrogram-Derived Features for Automated Sickness Detection in Driving Simulator

The rapid development of driving simulators for the evaluation of automated driving experience is constrained by the simulator sickness-related nausea. The electrogastrogram (EGG)-based approach may be promising for immediate, objective, and quantitative nausea assessment. Given the relatively high EGG sensitivity to noises associated with the relatively low amplitude and frequency spans, we introduce an automated procedure comprising statistical analysis and machine learning techniques for EGG-based nausea detection in relation to the noise contamination during automated driving simulation. We calculate the root mean square of EGG amplitude, median and dominant frequencies, magnitude of Power Spectral Density (PSD) at dominant frequency, crest factor of PSD, and spectral variation distribution along with newly introduced parameters: sample and spectral entropy, autocorrelation zero-crossing, and parameters derived from the Poincaré diagram of consecutive EGG samples. Results showed outstanding robustness of sample entropy with moderate robustness of autocorrelation zero-crossing, dominant frequency, and its median. Machine learning reached an accuracy of 88.2% and revealed sample entropy as one of the most relevant and robust parameters, while linear analysis highlighted spectral entropy, spectral variation distribution, and crest factor of PSD. This study clearly indicates the need for customized feature selection in noisy environments, as well as a complementary approach comprising machine learning and statistical analysis for efficient nausea detection

Assisted Partial Take-Over in Conditionally Automated Driving: A User Study

This paper discusses the concept of take-over (TO) in conditionally automated vehicles. Most of the current studies consider TO as a discrete event that is completed when the driver takes full control of the vehicle. Two problems with this approach are that the driver 1) needs time to gain sufficient situational awareness and 2) sometimes takes over only the lateral or only the longitudinal coordination of the vehicle, neglecting the other. To overcome these two problems and increase the quality (effectiveness, efficiency, and satisfaction) of TO, we propose two new approaches to the take-over process: partial take-overs (PTO) and assisted take-overs (ATO). The proposed PTO approach allows the driver to take over only the lateral or longitudinal coordination of the vehicle separately, instead of assuming a full TO. With ATO, the driver is monitored even after taking control of the vehicle and is assisted with automatic soft braking as well as additional warning and emergency braking if the time to collision falls below the appropriate critical levels. The approaches were evaluated in a user study with 44 participants in a driving simulator. We were able to confirm that the proposed ATO approach significantly improves the TO quality in terms of both effectiveness and efficiency without compromising driver satisfaction. Contrary to our expectations, the PTO approach did not have a significant effect on the effectiveness of TO, but only provided significantly lower reaction time to first braking and longer time to lane crossing. When combined, ATO and PTO were at least as useful as either approach individually and should be considered in future TOR user interfaces

Post-takeover proficiency in conditionally automated driving

In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads

The Architectural Design of a System for Interpreting Multilingual Web Documents in E-speranto

E-speranto is a formal language for generating multilingual texts on the World Wide Web. It is currently still under development. The vocabulary and grammar rules of E-speranto are based on Esperanto; the syntax of E-speranto, however, is based on XML (eXtensible Markup Language). The latter enables the integration of documents generated in E-speranto into web pages. When a user accesses a web page generated in E-speranto, the interpreter interprets the document into a chosen natural language, which enables the user to read the document in any arbitrary language supported by the interpreter. The basic parts of the E-speranto interpreting system are the interpreters and information resources, which complies with the principle of separating the interpretation process from the data itself. The architecture of the E-speranto interpreter takes advantage of the resemblance between the languages belonging to the same linguistic group, which consequently results in a lower production cost of the interpreters for the same linguistic group. We designed a proof-of-concept implementation for interpreting E-speranto in three Slavic languages: Slovenian, Serbian and Russian. These languages share many common features in addition to having a similar syntax and vocabulary. The content of the information resources (vocabulary, lexicon) was limited to the extent that was needed to interpret the test documents. The testing confirmed the applicability of our concept and also indicated the guidelines for future development of both the interpreters and E-speranto itself

Concepts, ontologies, and knowledge representation

Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to kno

Assessing drivers\u27 physiological responses using consumer grade devices

The ability to measure drivers’ physiological responses is important for understanding their state and behavior under different driving conditions. Such measurements can be used in the development of novel user interfaces, driver profiling, advanced driver assistance systems, etc. In this paper, we present a user study in which we performed an evaluation of two commercially available wearable devices for assessment of drivers’ physiological signals. Empatica’s E4 wristband measures blood volume pulse (BVP), inter-beat interval (IBI), galvanic skin response (GSR), temperature, and acceleration. Bittium’s Faros 360 is an electrocardiographic (ECG) device that can record up to 3-channel ECG signals. The aim of this study was to explore the use of such devices in a dynamic driving environment and their ability to differentiate between different levels of driving demand. Twenty-two participants (eight female, 14 male) aged between 18 and 45 years old participated in the study. The experiment compared three phases: Baseline (no driving), easy driving scenario, and demanding driving scenario. Mean and median heart rate variability (HRV), standard deviation of R–R intervals (SDNN), HRV variables for shorter time frames (standard deviation of the average R–R intervals over a shorter period—SDANN and mean value of the standard deviations calculated over a shorter period—SDNN index), HRV variables based on successive differences (root mean square of successive differences—RMSSD and percentage of successive differences, greater than 50 ms—pNN50), skin temperature, and GSR were observed in each phase. The results showed that motion artefacts due to driving affect the GSR recordings, which may limit the use of wrist-based wearable devices in a driving environment. In this case, due to the limitations of the photoplethysmography (PPG) sensor, E4 only showed differences between non-driving and driving phases but could not differentiate between different levels of driving demand. On the other hand, the results obtained from the ECG signals from Faros 360 showed statistically significant differences also between the two levels of driving demand

Assessing Drivers’ Physiological Responses Using Consumer Grade Devices

The ability to measure drivers’ physiological responses is important for understanding their state and behavior under different driving conditions. Such measurements can be used in the development of novel user interfaces, driver profiling, advanced driver assistance systems, etc. In this paper, we present a user study in which we performed an evaluation of two commercially available wearable devices for assessment of drivers’ physiological signals. Empatica’s E4 wristband measures blood volume pulse (BVP), inter-beat interval (IBI), galvanic skin response (GSR), temperature, and acceleration. Bittium’s Faros 360 is an electrocardiographic (ECG) device that can record up to 3-channel ECG signals. The aim of this study was to explore the use of such devices in a dynamic driving environment and their ability to differentiate between different levels of driving demand. Twenty-two participants (eight female, 14 male) aged between 18 and 45 years old participated in the study. The experiment compared three phases: Baseline (no driving), easy driving scenario, and demanding driving scenario. Mean and median heart rate variability (HRV), standard deviation of R–R intervals (SDNN), HRV variables for shorter time frames (standard deviation of the average R–R intervals over a shorter period—SDANN and mean value of the standard deviations calculated over a shorter period—SDNN index), HRV variables based on successive differences (root mean square of successive differences—RMSSD and percentage of successive differences, greater than 50 ms—pNN50), skin temperature, and GSR were observed in each phase. The results showed that motion artefacts due to driving affect the GSR recordings, which may limit the use of wrist-based wearable devices in a driving environment. In this case, due to the limitations of the photoplethysmography (PPG) sensor, E4 only showed differences between non-driving and driving phases but could not differentiate between different levels of driving demand. On the other hand, the results obtained from the ECG signals from Faros 360 showed statistically significant differences also between the two levels of driving demand

A user study of directional tactile and auditory user interfaces for take-over requests in conditionally automated vehicles

General introduction of unconditionally and conditionally automated vehicles is expected to have a highly positive impact on the society, from increased accessibility to mobility and road traffic safety, to decreased environmental and economic negative impacts. However, there are several obstacles and risks slowing down the adoption of this technology, which are primarily related to the human–machine interaction (HMI) and exchange of control between the vehicle and the human driver. In this article, we present key takeaways for HMI design of take-over requests (TOR) that the vehicle issues to inform the driver to take over control of the vehicle. The key takeaways were developed based on the results of a user study, where directional tactile-ambient (visual) and auditory-ambient (visual) TOR user interfaces (UI) were evaluated with regards to commonly used take-over quality aspects (attention redirection, take-over time, correct interpretation of stimuli, off-road drive, brake application, lateral acceleration, minimal time-to-collision and occurrence of collision). 36 participants took part in the mixed design study, which was conducted in a driving simulator. The results showed that drivers’ attention was statistically significantly faster redirected with the auditory-ambient UI, however using the tactile-ambient UI resulted in less off-road driving and slightly less collisions. The results also revealed that drivers correctly interpreted the directional TOR stimuli more often than the non-directional one. Based on the study results, a list of key takeaways was developed and is presented in the conclusion of the paper. The results from this study are especially relevant to the TOR UI designers and the automotive industry, which tend to provide the most usable UI for ensuring safer end efficient human-vehicle interaction during the TOR task