Mitsubishi Electric Corporation

Olympus Optical Company, Ltd.

Olympus Medical Systems Corporation

Olympus Corporation

Other

Mazda Motor Corporation

Mitsubishi Electric Cornoration

Meiji Dairies Corporation

Koji Iida

Noritaka Kokido

Takuya Taniguchi

Tomoyuki Takashino

Naomi Sekino

Toru Nagase

Norihiko Hareyama

Masanori Mori

Takashi Abe

Hiroshi Tsuchita

Shinichi Tateiwa

Kenichi Kimura

Eiji Murakami

Takahisa Aoyagi

Koji Yamauchi

Takayuki Moritani

Noriyoshi Yamashina

Mai Wakamatsu

Takeaki Nakamura

Ryota Sekiguchi

Tomohisa Sakurai

Tomohiro Akiyama

Shinji Hatta

Katsumi Sasaki

Kenji Noda

Hideto Yoshimine

Toshihiko Hashiguchi

Seiichi Hosoda

Toshiya Sugai

Nariaki Takehara

Hiroyuki Takahashi

Akihisa Ogawa

Makoto Inaba

Tetsuji Haga

Satomi Sakao

Taisuke Sato

Kiyotoshi Sakashita

Yoshihiro Yamamoto

Eiji Kanehira

Kouji Yamauchi

Hideaki Tamazumi

Yasuhiko Kikuchi

Junki Tamaru

Hiroyuki Ueda

Toru Shimizu

There are included an own vehicle position sensor which detects the position of an own vehicle; a reference path acquisition unit which acquires a reference path on which the own vehicle travels; a reference path determination unit which determines whether or not the own vehicle is traveling on the reference path; a temporary vehicle path calculation unit which, when it is determined by the reference path determination unit that the own vehicle is not traveling on the reference path, calculates a temporary vehicle path from at least two points, a travel start point of the own vehicle and an end point of the reference path; and a vehicle path setting unit which sets either the temporary vehicle path calculated by the temporary vehicle path calculation unit or the reference path on which it is determined by the reference path determination unit that the own vehicle is traveling as the vehicle path of the own vehicle.

Vehicle control device and vehicle control method

Provided are a lane separation line detection correcting device/method and an automatic driving system for stabilizing the behavior of a vehicle by correcting overestimated curvature information resulting from an erroneous detection of a curvature of a lane separation line. A travel speed detecting circuit detects, for example, a target travel speed as vehicle sensor information. A maximum curvature estimating circuit estimates, based on the target travel speed, a maximum curvature of a road along which an own vehicle is traveling. A curvature correcting circuit corrects a curvature of a lane separation line input thereto based on the maximum curvature. A control unit controls steering of the own vehicle based on the lane separation line having a corrected curvature. As a result, vehicle steering can be automatically controlled so as to prevent the own vehicle while traveling from departing from a driving lane.

Lane separation line detection correcting device, lane separation line detection correcting method, and automatic driving system

An extraction unit () extracts as a stationary object-detection point, a detection point on a stationary object among a plurality of detection points around a vehicle (), the plurality of detection points being detected by an outside-detection sensor () at a plurality of detection timings. A grouping unit () groups two or more stationary object-detection points deduced as detection points on a same stationary object, among a plurality of stationary object-detection points extracted by the extraction unit () at the plurality of detection timings.

Object recognition apparatus, object recognition method, and computer readable medium

An object recognition device is configured to: classify, under a state in which not all object data in a detection data group have been received and a part of the object data have been received by a current processing time, the part of the object data into pieces regarded as ready for association determination and pieces not regarded as ready for the association determination, to thereby associate the object data regarded as ready for the association determination and the prediction data individually with each other and set, as pending object data, the object data not regarded as ready for the association determination; and associate, under a state in which the remaining object data in the detection data group have been received by the next processing time after the current processing time, the remaining object data and the pending object data individually with the prediction data.

Object recognition device and object recognition method

There are provided an object recognition apparatus that raises the recognition accuracy for a surrounding object and a vehicle control apparatus, and an object recognition method and a vehicle control method. An object recognition apparatus receives object data, which is a state value of the object, from a first sensor for detecting a surrounding object; compares estimation data obtained through estimation of a state value of the object, based on recognition data calculated in a past period, with the object data, and determines whether or not the object data is data in a low-resolution state; then, in accordance with the determination result, calculates the state value of the object by use of object data and estimation data and then generates the state value as recognition data, so that the recognition accuracy for an object is raised.

Object recognition apparatus, vehicle control apparatus, object recognition method, and vehicle control method

An obstacle recognition device includes: a first sensor and a second sensor, which are configured to detect an object near a vehicle; a calculation unit configured to calculate, based on first detection data on a first object detected by the first sensor and second detection data on a second object detected by the second sensor, an index value for identifying whether the two objects are the same object; a determination unit configured to determine whether the two objects are the same object by comparing the index value with a threshold value set in advance; and a correction unit configured to calculate, when the determination unit has determined that the two objects are the same object, a detection error between the two sensors based on the two detection data, and generate corrected detection data so as to remove the detection error.

Obstacle recognition device and obstacle recognition method

Provided is an object recognition device capable of preventing a change of fusion data from a previous value to a current value that exceeds a tolerable range. The object recognition device is configured to execute specialized tracking processing when a change of the fusion data from the previous value to the current value exceeds a tolerable range, and generate tracking data that is equivalent to prediction data in the specialized tracking processing by setting an adjustment physical quantity for solving a fusion data discontinuity state.

Provided is an object detection device including: a detection unit configured to detect objects for every detection period to output detection information containing a reliability for each of the detected objects; a determination unit configured to: increment a detection count for each of the objects; calculate, for each of the objects, a sum of latest N reliabilities in the detection period; and determine, as a normally recognized object, an object for which the sum is equal to or larger than a first threshold value, which is set in advance depending on the detection count; and a control unit configured to output, as normally detected object information, detection information on the normally recognized object.

Object detection device and object detection method

Provided are an object recognition device and the like configured to associate, for detected object data and detected ego vehicle data that are received from respective sensors in a period from a previous processing time to a current processing time, an object data time with each piece of the detected object data, and an ego vehicle data time with each piece of the detected ego vehicle data, predict the detected ego vehicle data at the object data time to generate a result of the prediction as corrected ego vehicle data, and predict updated object data at the object data time to generate a result of the prediction as predicted object data.

Object recognition device, object recognition method, and vehicle control system

Growing community of inventors

Tokyo, Japan

Koji Iida