Nuio Tsuchida

Modeling and Recognition of Driving Behavior Based on Stochastic Switched ARX Model

This paper presents the development of the modeling and recognition of human driving behavior based on a stochastic switched autoregressive exogenous (SS-ARX) model. First, a parameter estimation algorithm for the SS-ARX model with multiple measured input-output sequences is developed based on the expectation-maximization algorithm. This can be achieved by extending the parameter estimation technique for the conventional hidden Markov model. Second, the developed parameter estimation algorithm is applied to driving data with the focus being on drivers collision avoidance behavior. The driving data were collected using a driving simulator based on the cave automatic virtual environment, which is a stereoscopic immersive virtual reality system. Then, the parameter set for each driver is obtained, and certain driving characteristics are identified from the viewpoint of switched control mechanism. Finally, the performance of the SS-ARX model as a behavior recognizer is examined. The results show that the SS-ARX model holds remarkable potential to function as a behavior recognizer.

Modeling and Recognition of Human Driving Behavior based on Stochastic Switched ARX model

This paper presents a development of the modeling of the human driving behavior based on the expression as Stochastic Switched ARX model (SS-ARX) focusing on the driver’s collision avoidance behavior. First, the parameter estimation technique for the SS-ARX model is introduced based on the EM algorithm. This can be achieved by extending the parameter estimation technique for conventional Hidden Markov Model (HMM). Second, the parameter estimation technique is applied to the collected driving data, and find parameter set for each driving data. The driving data are collected by using the three-dimensional driving simulator based on CAVE, which provides stereoscopic immersive vision. Finally, the performance of the SS-ARX model in the case of using as the recognizer is examined. The results show the high potential ability of the SS-ARX model as the behavior recognizer.

Acquisition and Modeling of Driving Skills by Using Three Dimensional Driving Simulator

This paper presents the analysis of the stopping maneuver of the human driver by using a new three-dimensional driving simulator that uses CAVE, which provides stereoscopic immersive vision. First of all, the difference in the driving behavior between 3D and 2D virtual environments is investigated. Secondly, a GMDH is applied to the measured data in order to build a mathematical model of driving behavior. From the obtained model, it is found that the acceleration information has less importance in stopping maneuver under the 2D and 3D environments.

Hardware for image rotation by twice skew transformations

Image processing systems in real time are going to be used in various fields, in both factories and offices. However, these performances are not sufficient when a very short processing time is required. This paper presents quite a new method of high-speed image rotation. Here an image is rotated only by twice skew transformations, whereby each pixel is shifted in parallel with each coordinate axis. With this algorithm, an image can be rotated very quickly, since such a parallel shifting is performed by simple address controlling, i.e., brief additions of address values. The processing time to rotate a gray scaled image made up of 256 × 256 pixels is about 5 s, even by an 8 bit microcomputer. Furthermore, we propose a hardware for image rotation based on this algorithm. In the case of the hardware, the processing time to rotate an image made up of 516 × 516 pixels is estimated to be about 10 ms, when a high-speed 16 bit microcomputer is used for data setting.

A tactile sensor system for universal joint sections of manipulators

It is very difficult to place tactile sensors around revolute joints of manipulators, since those joints and surrounding surfaces are not stationary and thus they remain insensitive to contact with obstacles. This interferes with the introduction of sensors for collision avoidance control in manipulators. This paper deals with a tactile sensor system for universal joint sections of manipulators in order to detect collisions with obstacles. Its unique characteristic is the ability to detect, in one sampling period, the positions of more than one collision despite having only one signal line. It is achieved by making use of the resonance phenomenon of the sensor circuit, and all sensor elements can be distinguished from one another by frequency division. The structure of the sensor and the method to detect the label number and position of the sensor elements that are in contact with obstacles are described, followed by analysis of the circuits and experimental results of the sensor system. >

A GaAs Micro Solar Cell with Output Voltage over 20 V

Twenty-four micro-solar cells connected in series have been fabricated on semi-insulating (SI) GaAs substrates for application in the fields of micro-electromechanical systems. The array was formed in an area of 0.8×1.0 mm2, and exhibited an open-circuit voltage of 22.5 V under illumination of 5 mW at the wavelength of 815 nm. Calculation and experiment has demonstrated that, unlike conventional solar cells, the shunt resistance deteriorates the output characteristics far more seriously than the series resistance in the case of micro-solar cells. Leakage currents in both the unit diode and the substrate were evaluated separately. A quantitative estimate based on the measurements revealed that photocurrents generated in the surface of the SI substrate could function as a vital shunt resistance. Light-blocking metal films were successfully employed to obtain high output voltage.

Modeling of Human Behavior in Man-Machine Cooperative System Based on Hybrid System Framework

Recently, the demand for a man-machine cooperative system, where the machine assists the human operator, is rapidly growing in the industrial fields. To meet this demand, the human model is required to design the suitable assist controller in the man-machine cooperative system. This paper presents a new human behavior model based on a piece-wise affine model which is a class of hybrid dynamical system, and apply it to a sliding task. Since the human behavior is considered to consist of several primitive motions expressed by continuous dynamics and a decision-making expressed by the discrete switch, it seems to be natural to introduce the hybrid system modeling. Particularly, the decision strategy for the number of discrete modes is addressed by using a hierarchical clustering technique, and the measured data are classified into several modes. Then, each primitive motion in each mode is identified based on the affine model. Finally, the switching conditions among modes are identified by applying support vector machine to the classified data. The obtained piece-wise affine model can quantitatively represent both primitive motions and decision-making in the human behavior

Performance of induction motor with free-rotating magnets inside its rotor

This paper presents a new induction motor that has free-rotating magnets inside a rotor. The magnets can revolve freely against the rotor with the shaft. In this motor, the airgap flux is provided by both rotating permanent magnets and the stator coil current. A prototype motor was fabricated by modifying the rotor of a conventional three-phase four-pole 400 W squirrel-cage induction motor. The experimental results of a prototype motor showed superior performance in comparison to conventional motors in terms of the power factor, efficiency and torque characteristics. The power factor can be controlled to be unity, leading or lagging by changing the supply frequency and/or source voltage. The efficiency of the motor, over a wide output power range, is remarkably higher than that of the same size conventional induction motor. A high torque can be obtained in a high speed area.

Behavior modeling in man-machine cooperative system based on stochastic switched dynamics

This paper presents a new mathematical model for the human behavior called stochastic switched linear dynamical (SS-LD) model. The SS-LD model can be regarded as a natural extension of the conventional hidden Markov model (HMM), where different linear dynamical model is allocated to each discrete state of the HMM to represent continuous dynamics. Then, the parameter identification technique for SS-LD model is developed based on the EM algorithm. Finally, we apply the proposed behavior model to a typical man-machine cooperative system, and the usefulness of the proposed model is verified through some experiments

Iron Concentrations in GaAs Diffused from a Spin-on Film

Secondary ion mass spectroscopy (SIMS) has revealed that spin-on-film diffusion can produce very flat profiles of iron in GaAs, and the concentrations in the range of 1015-1017 cm-3 are consistent with the solubility of iron at the diffusion temperatures of 650-900° C. The iron accumulation region at the surface is markedly reduced in comparison with that in the conventional method. This technique is useful for introduction of a controlled amount of deep acceptor levels of iron into GaAs.