The benefits obtained from inconvenience, which we call the FUrther BENEfit of a Kind of Inconvenience (fuben-eki), are now being recognized in many research fields. To design systems that embody such benefits, this paper proposes fuben-eki cards. A set of them consists of principle cards and benefit cards. Each principle card shows a tenet to make a system inconvenient that leads to the positive outcomes shown on each benefit card. The results of evaluation experiments show that principle cards increased the number of ideas when they were used for the divergent thinking processes of a fuben-eki system design.
Electric Vehicles (EVs) and Plug-in Hybrid Vehicles (PHVs) are expected to be used as power-storage devices in Home Energy Management Systems (HEMSs) due to their high capacity batteries. When planning the charge and discharge of the vehicle's battery by the HEMS, the expected profile of car's departures and arrivals for home is required. This paper presents a real-time estimation method for the Profile of Departure and Arrival Times (PDATs) over one day. The PDAT prediction problem is formulated as a maximum-likelihood estimation problem with the probability based on the Statistics of Departure and Arrival Times (SDAT). In the proposed method, the maximum-likelihood estimation problem is decomposed to optimization subproblems, each of which is solved by a greedy algorithm. Due to this decomposition, it is possible to find a plausible solution of the PDAT with a reasonable computational cost. The utility of the proposed method is evaluated by numerical experiments with SDATs derived from the real data of three subjects who use gasoline vehicles.
This paper proposes a decentralized trajectory planning method by which vehicles stay connected and avoid collisions within a vehicle team by communicating through a multi-hop ad hoc wireless network. In order to maintain network connectivity, vehicles need to move carefully because of the limited wireless range. However, a vehicle formation often needs to make drastic changes, which risk breaking the network connectivity. On the other hand, vehicles may crash into each other if they stay too close in fear of breaking the network. The proposed method can fix this problem because it is based on a constraint of optimal control. Although the method plans discrete via-points, it guarantees continuous network connectivity and collision avoidance. The author presents the theoretical properties analyzed in this study and the computer simulation performed to validate the proposed method.
A collision avoidance system has a potential to reduce traffic accidents and expected to become widely used. From the driver's point of view, it is important to present a collision warning which does not disturb driver's concentration on driving. This paper describes the effectiveness of the collision avoidance system which uses the information displayed in driver's peripheral vision (peripheral vision information) in right turn at an intersection. In order to analyze the effectiveness of the peripheral vision information, the authors evaluated a response time to the information and an effect of over-trust behavior when the information was not presented. The analysis was conducted through a driving simulator experiment and the result showed that the peripheral vision information is effective to avoid a collision. Moreover, the over-trust behavior, the delay time of a response time when the information is not presented was reduced.
This paper discusses driver's emergency avoiding behavior while he or she is driving a car in a rural area. Based on behavioral data obtained from an experiment conducted in France with a high-fidelity driving simulator, the authors analyzed the driver behavior just before the collision. The results showed that the drivers tended to choose a “rational” behavior to avoid the collision by using the available visual cues even though the situation is extremely time critical, i.e., the time to collision was only approximately 1.5 seconds.
In the multi-objective optimization problem that appears naturally in the decision making process for the complex system, the visualization of the innumerable solutions called Pareto optimal solutions is important issue. This paper focuses on the Pareto optimal solution visualization method using the self-organizing maps which is one of promising visualization methods. The method has advantages in grasping the overall structure of the solutions and comparing the objective functions simultaneously. This method has been applied to some real problems, but its solution representation capability has not been studied well. This paper investigates the solution representation capability of the Pareto optimal solution visualization method using the SOM and points out its shortcomings. Then, two improvements are introduced to the visualization method. The effectiveness of the proposed method is confirmed via comparing it to the conventional visualization method using three indices evaluating the solution representation capability.
In this study, a binary manipulator is considered as a controlled plant. The control objective is to bring the end effector of the binary manipulator close to a given target point and orientation. One advantage of the binary manipulator is its high reliability owing to its hyper-redundancy. However, the inverse kinematics problem of the binary manipulator is a combinatorial optimization problem. The workspace of the binary manipulator is a discrete set. The number of reachable points grow exponentially with respect to the number of binary actuators. Therefore, compact representation of the workspace is necessary. This paper proposes an ellipsoidal outer-approximation of the workspace of the binary manipulator. This approximation can be calculated recursively, and it can be utilized for the inverse kinematics algorithm of binary manipulators. The validity of the proposed approximation method and inverse kinematics algorithm are verified via numerical experiments.
In Vehicle-to-Home (V2H) systems, charge/discharge scheduling of in-vehicle battery installed in Electric Vehicles (EVs) or Plug-in Hybrid Vehicles (PHVs) is very important in order to operate the battery as an storage and a source of electricity for the car owner's home. This significance of the battery is similarly applied to apartment buildings not only to homes. In this paper, the authors proposed an Energy Management System (EMS) for apartment buildings based on model-predictive control (MPC) using group optimization with electricity interchange from in-vehicle batteries, and the authors investigate and verify the usefulness of the proposed system for apartment buildings where households have various patterns in profiles of electricity consumption and vehicle use.
In wind-based energy operations, turbine performance, part deterioration rates and regular maintenance costs play a significant role in the economic viability of such projects. Problems to determine in advance the optimal future state of variables such as generator torque or blade pitch angle may be framed as anticipatory control problems, though successful application in real-world operations requires reliable forecasts of the future state of local wind speed. The authors propose a general probabilistic forecasting approach within the geographically robust CRPS minimization estimation framework suited to make use of AMeDAS weather variable observations, with the chief goal of evaluating the utility of the AMeDAS observations in the context of a rotor speed control problem where one seeks to maximize long-term power output at a specific turbine. Tested over a full year's worth of observations from sites across Japan, and using deterministic and non-deterministic evaluation metrics compared against standard references, the capacity of the proposed model as a forecaster at the 10-minute horizon was verified, and in doing so confirmed the potential wide-scale utility of the AMeDAS network in this and related anticipatory control problems.
Scheduled liner service is a proper system for mass transportation and it is employed by wide range of transportation modes, such as railway, airline, maritime container shipping and bus. To get more customers, providers of the liner services are required to organize effective routes and networks of the service incorporating the characteristic of the passenger's route selection. This paper tackles to the problem of generating Public Transit Network as one of scheduled liner service. The method generating PTN is based on Multi Agent System that incorporates the characteristic of passenger's route selection. And it is also reported that the developed method successfully output best solution for a benchmark problem.
Heart rate monitoring has huge potential in disease prevention, stroke prediction, and mental stress/workload assessment. Although most conventional heart rate monitoring systems are wearable devices, such devices may be obtrusive and disturb our daily life. This work proposes a new large, thin and flat/curved surface-type heart rate sensor. Building the proposed sensor into the surfaces of daily devices, such as a steering wheel or a computer mouse, allows daily heart rate to be monitored unobtrusively, without changing the users behavior. Experiments on subjects evaluated the heart rate monitoring performances of flat, curved, and mouse-embedded prototypes. The results confirm PPG measurement accuracies equivalent to those of the conventional point sensor.
For medical or sports applications, human motor control is frequently analyzed. This study focuses on dart throwing motion and investigate the human motor skill to achieve precision control and force generation. The joint coordination is related to stability and accuracy of movements for precision control. On the other hand, the joint correlation is related to transfer of forces and movements for force generation. Uncontrolled manifold (UCM) analysis was applied to evaluate the joint coordination and elucidate the joint which the throwers decrease the variability. In the experiment, ten young people who did not play dart on regular basis participated and performed dart throws at five different throwing distances. Based on the result of UCM analysis, it was found that throwers had less variability on the finger position rather than wrist, elbow, and shoulder positions. In order to evaluate the joint correlation, normalized correlation coefficient between arm and lower body was computed at different throwing distances. This analysis showed that the correlation between elbow and ankle, and between elbow and knee, were increased at long throwing distance. From our results, in dart throwing motion, we elucidated that the longer throw induced the new motor control strategy of precision control and force generation.
This paper proposes a very simple user-state recognizer for mobile applications. The proposed method copes with the limitation in available electric power by using only a single three-axis accelerometer which is equipped with almost any mobile phone. In order to keep a high accuracy in recognition with a low computational complexity, the authors employ the wavelet transform and the singular value decomposition as feature extraction, and a multi-layer perceptron as a classifier. In the experiment, the algorithm could classify user contexts into walking, running, standing still and being in a moving train with an accuracy of over 90%.