Development of a Driving Simulator with Analyzing Driver’s Characteristics Based on a Virtual Reality Head Mounted Display

Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality technology is now a promising alternative to the conventional driving simulations since it provides a more simple, secure and user-friendly environment for data collection. The driving simulator was used to assist novice drivers in learning how to drive in a very calm environment since the driving is not taking place on an actual road. This paper provides new insights regarding a driver’s behavior, techniques and adaptability within a driving simulation using virtual reality technology. The theoretical framework of this driving simulation has been designed using the Unity3D game engine (5.4.0f3 version) and programmed by the C# programming language. To make the driving simulation environment more realistic, the HTC Vive Virtual reality headset, powered by Steamvr, was used. 10 volunteers ranging from ages 19 - 37 participated in the virtual reality driving experiment. Matlab R2016b was used to analyze the data obtained from experiment. This research results are crucial for training drivers and obtaining insight on a driver’s behavior and characteristics. We have gathered diverse results for 10 drivers with different characteristics to be discussed in this study. Driving simulations are not easy to use for some users due to motion sickness, difficulties in adopting to a virtual environment. Furthermore, results of this study clearly show the performance of drivers is closely associated with individual’s behavior and adaptability to the driving simulator. Based on our findings, it can be said that with a VR-HMD (Virtual Reality-Head Mounted Display) Driving Simulator enables us to evaluate a driver’s “performance error”, “recognition errors” and “decision error”. All of which will allow researchers and further studies to potentially establish a method to increase driver safety or alleviate “driving errors”.

Calculate Target Position of Object in 3-Dimensional Area Based on the Perceived Locations Using EOG Signals

EOG is a biosignal which occurs during eye activities such as eye movement and blink. EOG has a linear relationship with gaze distance. Detection object position in 3-dimensional area using gaze motion was proposed in this research. To calculate the distance of gaze motion in pixel unit, affine transform method was developed. The homogeneous matrix from five geometry processes: transformation-1, rotation, transformation-2, shear, and dilatation was determined. To give tracking ability in 3-dimensional area, two cameras were attached each in front of and top side of object. The cameras were accessed by voluntary blink. The EOG characteristic of blink eye was determined based on the absolute ratio between positive peak and negative peak which was greater than 1. Every blink toggled the active camera. The position of object was given by the perceived locations from the two cameras. Every movement in pixel coordinate was converted into centimeter unit. Then, the perceived location was used to calculate to the base coordinate. The result shows that the blink method successfully accessed the camera. Both of the cameras could show the location of object from their side. Calculating the gaze distance using affine transform also gave a satisfied result. Using this method controlling a machine in 3-dimensional area by EOG could be developed.

Virtual Reality Driving Simulation for Measuring Driver Behavior and Characteristics

This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.

Evaluating Hazard Response Behavior of a Driver Using Physiological Signals and Car-Handling Indicators in a Simulated Driving Environment

Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with the advent of modernized driver assistance technologies. This paper sought to evaluate response of a driver using active-driving performance indicators like reaction time and physiological signal response (surface electromyogram), to understand hazard response behavior. Simulation of driving scenes was done using Unity3D engine and VR Head mounted display. The driver was presented with stimulus (collision objects) of different size and distance. From the results, an event scene that the driver considered hazardous was marked with increased electromyography response distinct from non-event scenes. From the results, we noted an increase in pedal misapplication during hazard response. The proposed approach is applicable in a real time driving analysis for on-road risk level classification.

End Point Force Control of a Flexible Timoshenko Arm

This paper discusses a force control problem for a flexible Timoshenko arm. The effect of shear deformation and the effect of rotary inertia are considered in Timoshenko beam theory. Most of the research about force control of the flexible arm is based on Euler Bernoulli beam theory. There are a few researches about force control of the flexible arm using Timoshenko beam theory. The aim of the force control is to control the contact force at the contact point. To solve this problem, we propose a simple controller using Timoshenko beam theory. Finally, we describe simulation results using a numerical inversion of Laplace transform carried out to investigate the validity of the proposed controller for the force control problem. The results of the time response show the transverse displacement, the angle of deflection, the slider position, the rotational angle and the contact force toward the desired their values.

Robot Control System Based on Electrooculography and Electromyogram

This paper describes a man-machine interface system using EOG and EMG. A manipulator control system using EOG and EMG is developed according to EOG and EMG. With the eye movement, the system enabled us to control a manipulator. EOG is using for moving the robot joint angles and EMG is using for object grasping. The EOG and EMG discrimination method is used to control the robot. The robot arm joint movements are determined by the EOG discrimination method where the polarity of eye gaze motion signals in each Ch1 and Ch2. The EMG discrimination method is used to control arm gripper to grasp and release the target object. In the robot control experiment, we are successfully control the uArmTM robot by using both EOG and EMG discrimination method as the control input. This control system brings the feasibility of man-machine interface for elderly person and handicapped person.

Autonomous oscillatory shape change of DEA induced by the charge–discharge process under a constant voltage

Despite the promising characteristics of Dielectric Elastomel Actuator(DEA)as a practical soft actuator,the need of high voltage for its operation prevents the successful fabrication of a practical DEA,that is,the high voltage generation takes a bulky and costly power supply.Induction of complex shape change motion of DEA such as oscillatory shape change takes even a more bulky and costly multipurpose power supply.It is a serious practical issue to be overcome.In our latest study,however,we could build a simple DEA system which exhibited a relatively complex and autonomous oscillatory shape change merely under a constant voltage,though the voltage needed was high.This successful outcome must broaden the potential usefulness of DEA as a practical soft actuator.