scholarly journals Driving simulator for performance monitoring with physiological sensors

2018 ◽  
Author(s):  
Diogo Raimundo ◽  
Andre Lourenco ◽  
Arnaldo Abrantes
Keyword(s):  
Performance Monitoring ◽  
Driving Simulator ◽  
Physiological Sensors

scholarly journals A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 399 ◽  
Author(s):  
David González-Ortega ◽  
Francisco Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Driving Simulator ◽  
Android Application ◽  
Game Engine ◽  
Vehicle Data ◽  
Driver Monitoring ◽  
Skin Response ◽  
Android App ◽  
Physiological Sensors ◽  
Electrocardiogram Ecg ◽  
Physiological Sensor

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

Detecting Drivers’ Stress in Emergency Using Physiological Sensors

2015 ◽  
Vol 742 ◽  
pp. 150-157
Author(s):  
Ying Chen
Keyword(s):  
Heart Rate ◽  
Stress State ◽  
Driving Simulator ◽  
Time Frame ◽  
Training System ◽  
Heart Rate Variability Analysis ◽  
Continuous Measure ◽  
Physiological Sensors ◽  
Emergency Scenarios ◽  
Driver Stress

This paper presented methods for collecting and analyzing heart rate data during virtual-world driving task in emergency to distinguish and assess a driver’s stress state. The primer study had developed the driver stress training system loaded on driving simulator to display 14 typical emergency scenarios in different road environment. Electrocardiogram was recorded continuously by Physiological Sensors while drivers followed a random simulated driving on the driving simulator. Data from 30 drivers of at least 10 times per scenario were collected for analysis. The data were analyzed in two ways of HRV (Heart Rate Variability) analysis. Analysis I used time domain indexes of data during the driving in the whole training to distinguish the stress occur during the time frame of the scenario with an accuracy of over 98% across multiple drivers and driving days. Analysis II compared frequency indexes of data in stress state in emergency and in clam, with a metric of observable stressors created by the scenarios. The results showed that heart rate metrics is most closely correlated with driver stress level for most drivers studied. These findings confirmed that heart rate signals can provide a metric of driver stress in future cars capable of physiological monitoring. Such measurement could be used to help manage non-critical and critical in-vehicle information systems and could also provide a continuous measure of how different road and traffic conditions affect drivers. Physiological sensors can be used in driving assistance system in future.

Driving Simulator System to Evaluate Driver’s Workload Using ADAS in Different Driving Contexts

2017 ◽  
Author(s):  
Giandomenico Caruso ◽  
Daniele Ruscio ◽  
Dedy Ariansyah ◽  
Monica Bordegoni
Keyword(s):  
Driving Simulator ◽  
Driving Simulation ◽  
Human Cognition ◽  
Driving Safety ◽  
Physiological Data ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
Dangerous Driving ◽  
Vehicle Technology ◽  
Physiological Sensors

The advancement of in-vehicle technology for driving safety has considerably improved. Current Advanced Driver-Assistance Systems (ADAS) make road safer by alerting the driver, through visual, auditory, and haptic signals about dangerous driving situations, and consequently, preventing possible collisions. However, in some circumstances the driver can fail to properly respond to the alert since human cognition systems can be influenced by the driving context. Driving simulation can help evaluating this aspect since it is possible to reproduce different ADAS in safe driving conditions. However, driving simulation alone does not provide information about how the change in driver’s workload affects the interaction of the driver with ADAS. This paper presents a driving simulator system integrating physiological sensors that acquire heart’s activity, blood volume pulse, respiration rate, and skin conductance parameters. Through a specific processing of these measurements, it is possible to measure different cognitive processes that contribute to the change of driver’s workload while using ADAS, in different driving contexts. The preliminary studies conducted in this research show the effectiveness of this system and provide guidelines for the future acquisition and the treatment of the physiological data to assess ADAS workload.

Recent Developments of Ambulatory Assessment Methods

2014 ◽  
Vol 25 (4) ◽  
pp. 279-287 ◽  
Author(s):  
Stefan Hey ◽  
Panagiota Anastasopoulou ◽  
André Bideaux ◽  
Wilhelm Stork
Keyword(s):  
Real Time ◽  
Information And Communication Technologies ◽  
New Technologies ◽  
Psychological Research ◽  
Ambulatory Assessment ◽  
Emotional States ◽  
Recent Developments ◽  
Potential Applications ◽  
Information And Communication ◽  
Physiological Sensors

Ambulatory assessment of emotional states as well as psychophysiological, cognitive and behavioral reactions constitutes an approach, which is increasingly being used in psychological research. Due to new developments in the field of information and communication technologies and an improved application of mobile physiological sensors, various new systems have been introduced. Methods of experience sampling allow to assess dynamic changes of subjective evaluations in real time and new sensor technologies permit a measurement of physiological responses. In addition, new technologies facilitate the interactive assessment of subjective, physiological, and behavioral data in real-time. Here, we describe these recent developments from the perspective of engineering science and discuss potential applications in the field of neuropsychology.

Research on vehicle-based driver status/performance monitoring, Part III

1996 ◽  
Author(s):  
Walter W. Wierwille ◽  
Mark G. Lewin ◽  
Rollin J. Fairbanks
Keyword(s):  
Performance Monitoring

A solution to the rear-vision problem in a fixed-base driving simulator

2004 ◽  
Author(s):  
Guihua Yang ◽  
Farnaz Baniahmad ◽  
Beverly K. Jaeger ◽  
Ronald R. Mourant
Keyword(s):  
Driving Simulator ◽  
Fixed Base
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