Mitsubishi Electric Corporation

Mitsubishi Denki Kabushiki Kaisha

Yasushi Obata

Hiroshi Kameda

Yuki Takabayashi

Tetsutaro Yamada

Kyosuke Konishi

Satoshi Yasuda

Yoshiaki Yokoyama

Takashi Matsuzaki

Taizo Isono

Tomoyuki Koyanagi

Toshihiko Arioka

Tetsuji Harada

Akitoshi Mitsuishi

A plurality of candidate estimated paths () for a vehicle () to travel to an intermediate destination () while avoiding a moving object present by estimation time is generated depending on cost information of lanes (), and an estimated path selected from the plurality of candidate estimated paths () is set as a path of the vehicle () for each estimation time.

Path estimation device and path estimation method

A detection area determining unit () determines a detection area where there is a possibility that a tsunami occurs. A current velocity estimating unit () estimates, as a sea-surface velocity of current in the detection area, a value obtained by smoothing sea-surface velocity of currents corresponding to cells included in the detection area. A tsunami detecting unit () detects occurrence of the tsunami in the detection area, based on the sea-surface velocity of current estimated by the current velocity estimating unit ().

Radar apparatus

An information acquiring unit for acquiring direction information indicating the direction in which a target is to be searched for and observation accuracy information indicating the observation accuracy in the direction, and a beam arrangement determining unit for determining an arrangement of beams to be emitted by an antenna from the direction information and the observation accuracy information acquired by the information acquiring unit are provided, and a beam controlling unit controls the directions of the beams to be emitted by the antenna in accordance with the arrangement of beams determined by the beam arrangement determining unit.

Radar and beam control method

The route prediction system according to the invention includes a measurement unit to measure an area including a host vehicle and other moving vehicles, a vehicle detection unit to detect the host vehicle and at least two of the surrounding vehicles having collision possibilities on the basis of observation results observed by the observation unit, a hypothesis generation unit to generate plural hypotheses for the at least two of the surrounding vehicles detected by the vehicle detection unit to avoid collision, a likelihood calculation unit to calculate a likelihood indicating probability of occurrence of each of the plural hypotheses generated by the hypothesis generation unit, and a predicted route analysis unit to analyze, on the basis of the likelihood calculated by the likelihood calculation unit, predicted routes of the at least two of the surrounding vehicles, and output the analysis result. With such a configuration, in a case where plural vehicles may collide in future, predicted routes of the plural surrounding vehicles can be calculated without contradiction, improving performance on predicting the routes of the surrounding vehicles.

Route prediction system

A configuration includes: a target-motion prediction unit () that calculates predicted movement ranges of one or more other vehicles () based on target tracking; an inter-target collision possibility estimator () that estimates a collision possibility based on overlap of predicted movement ranges of the other vehicles (); a target-motion re-prediction unit () that again calculates predicted movement ranges to avoid collision when the collision possibility between the other vehicles () exists; an own-motion prediction unit () that calculates a predicted movement range of a user's vehicle () based on an observation result; and an own-collision possibility estimator () that estimates collision possibilities between the user's vehicle () and the other vehicles () based on overlap of the final predicted movement ranges of the other vehicles () and the predicted movement range of the user's vehicle ().

Collision avoidance device

An observer measures a flow velocity of sea surface with beam, and a coastal wave height. A predictor predicts a next time state vector, from a state vector including flow velocity of each range cell of beam, a wave height difference between range cells, and a coastal wave height. First calculator calculates a prediction error covariance matrix from a smoothing error covariance matrix. Second calculator calculates a gain matrix using results obtained by the observer and the first calculator. Third calculator calculates a smoothing error covariance matrix using results by the observer, the second calculator, and the first calculator. The state vector is smoothed for each wave height difference, from results by the observer, the predictor, and the second calculator. The wave height of each range cell is calculated by adding the wave height and the wave height difference in toward-offshore direction, using the wave height difference smoothing.

State estimation device

A radar device including an up-chirp tracking filter that performs a tracking process using a beat frequency at the time of an up-chirp to acquire a beat frequency, a down-chirp tracking filter that performs a tracking process using a beat frequency at the time of a down-chirp to acquire a beat frequency, target detectors that calculate distance and speed estimated values of the target for the chirps from beat frequency time series data about the chirps; an identical target determinator that determines whether or not the target detected for each of the chirps is an identical target using the distance and speed estimated values, and a distance and speed calculator that calculates a distance and a speed of the target using the beat frequency of the target which is determined to be an identical target.

Radar device

A radar (peripheral object observation device) repeatedly observes a relative position of an object relative to the moving object, which is located in the vicinity of a moving object. A stationary object identification unit (stationary object determination unit) determines whether or not the object the relative positions of which have been observed by the radar is still. A road approximate curve temporary computation unit (object correlation unit) determines a plurality of the relative positions of an identical object observed by the radar from among the relative positions observed by the radar. A road approximate curve main computation unit (approximate curve computation unit) computes an approximate curve that approximates the configuration of a road on which the moving object is located, based on a result of the determination by the stationary object identification unit and a result of the determination by the road approximate curve computation unit.

Road configuration estimation apparatus, computer program, and road configuration estimation method

A candidate-itemset generating unit generates a candidate-itemset composed of at least one candidate item to be included in the left hand side or the right hand side of the association rule. A candidate-itemset verifying unit selects itemsets having frequencies (appearing times in the database) more than the minimum frequency out of the candidate-itemsets, as large-itemsets. A candidate rule generating unit generates candidate association rules based on a large-itemset of k&minus;1 long and a large-itemset of 1 long. A chi-square testing unit generates an association rule set based on the candidate association rules by performing a chi-square test in which a &khgr; statistics and a significant level are used as parameters.

Method and apparatus for discovering association rules

A data mining apparatus is disclosed for finding a useful association rule from among a large number of association rules discovered through data mining by setting evaluation criteria of the association rules which differ depending on the user's purpose. The data mining apparatus includes an association rule generator which forms and outputs an association rule file based on data items stored in a data base, an evaluation criterion assignor which outputs an evaluation criterion file based on the evaluation criterion assigned by the user, an association rule evaluator which calculates an evaluation value based on the evaluation criterion file and updates information about the association rules in the association rule file. The data mining apparatus further includes a performance result display which displays the re-evaluated value information of the association rules in the association rule file, re-arranges display order, limits the association rules to be displayed, and then displays the re-arranged and limited association rules.

Growing community of inventors

Tokyo, Japan

Yasushi Obata