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This paper presents a probabilistic cutting plane technique for solving a robust feasibility problem which is to find a solution satisfying a parameter-dependent convex constraint for all possible parameter values. The proposed algorithm employs random samples of the parameter and maximum volume ellipsoid centers of candidates of the solution set. It is shown that the numbers of updates and random...
To reduce rear-end crash of automobiles, it is important to judge necessity of deceleration assistance as earlier as possible and initiate the assistance naturally. On the other hand, we have derived a mathematical model of driver's perceptual risk of proximity in car following situation and successfully derived driver deceleration model to describe deceleration patterns and brake initiation timing...
To prevent crashes of automobiles, many driver assistance systems have been proposed. Several warning systems have been proposed to reduce driver cognitive and judgment load. Such warning systems should have ability to evaluate collision risk and to start warning appropriate timing. Inversely, the system's efficacy can be decreased if the driver feels annoyance and/or mistrust with inappropriate warning...
This paper shows the versatility of the Particle Swarm Optimization, which attracts a lot of attention recently in the evolutionary computation area due to its empirical evidence of its superiority, in the area of continuous-time system identification. First, a method to identify (possibly nonlinear) continuous-time systems is shown, which uses the Particle Swarm Optimization to minimize the mean...
This paper gives an overview on probabilistic approach to robust optimization and chance constrained optimization. The problems are to minimize a linear objective function subject to a parameter dependent convex constraint, where a probability measure is introduced onto the parameter set. Two randomized techniques, the scenario optimization and the sequential optimization, are summarized, where characteristics...
In order to realize intelligent agent such as autonomous mobile robots, reinforcement learning is one of necessary techniques in behavior control system. However, applying the reinforcement learning to actual sized problem, the ldquocurse of dimensionalityrdquo problem in partition of sensory states should be avoided maintaining computational efficiency. Furthermore the robot task is desired to be...
Deceleration patterns of an expert driver will be formulated as an example of comfortable braking pattern. The difficulty of its formulation is how to extract characteristics of the deceleration behavior. This research focuses on visual control of vehicles in car following. We have hypothesized that driver evaluate risk of collision based on the area change of the preceding car on the retina and determines...
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