Abstract: An auto clean machine comprising: a height computing device; and an obstacle determining device. The height computing device is turned on to compute a height or an overhang height of an obstacle when the obstacle determining device determines the obstacle exists in a predetermined region of the auto clean machine. The height computing device does not compute the height and the overhang height when the obstacle determining device does not determine the obstacle exists in the predetermined region.

Abstract: The present disclosure provides a probabilistic decision engine for autonomous vehicles. Briefly described, one embodiment comprises taking a network connection matrix (based on maps and graph theory) and a cost matrix (with entries of the cost's mean values and probability distributions) as input and generates the probability distribution of optimal routes as output. The disclosed probabilistic decision engine comprises a stochastic network standardization module, a stochastic network decomposition module and a probabilistic optimization kernel. A deterministic network reduction method is first used to derive a standard reduced network, augmented by the stochastic network reduction. The standard network is then decomposed into a series of stochastic subnetworks by using the convolution, probability density function (PDF) shifting, and PDF reshaping techniques. A pure-analytical probabilistic solver is finally used to solve the stochastic optimization problem.

Abstract: The driving assistance device includes a movement detecting unit detecting an attitude changing movement for changing the attitude of a driver seat or a steering wheel of a vehicle capable of traveling in an automated driving mode in which a driver need not perform driving operations during traveling, a hold detecting unit detecting whether or not the steering wheel is held by the driver, and a hold requesting unit starting a holding request asking the driver to hold the steering wheel if the movement detecting unit has detected the attitude changing movement in the automated driving mode and if the hold detecting unit has not detected hold of the steering wheel.

Abstract: A LiDAR sensor three-dimensionally scans laser light outward of the vehicle and receives reflected light. A LiDAR data analyzer groups three-dimensional points of the reflected light acquired by the LiDAR sensor into clusters. A precise docking control start determination unit compares shapes and reflectance distributions between at least one of the clusters obtained by the LiDAR data analyzer and a reference cluster representing a stop target to determine whether or not the at least one cluster includes the stop target.