Denso Corporation

Yuusuke Matsumoto

Taku Sakima

Naoki Kawasaki

Syunya Kumano

Masayoshi Takeda

Akitoshi Minemura

Shunya Kumano

Kazuhisa Ishimaru

Itsuki Chiba

A lateral position of a vehicle is estimated by collating a position of a lane division line in map data with a relative position of the lane division line with respect to the vehicle indicated by a recognition result by a peripheral monitoring sensor. The lateral position of the vehicle is precluded from being specified using the estimated lateral position of the vehicle in response to a lateral deviation between (i) a position of a landmark in the map data and (ii) a translated landmark position being equal to or greater than a first threshold value. The translated landmark position is a position on map deviated from the estimated lateral position of the vehicle assumed to be the lateral position of the vehicle on map by a relative position of the landmark with respect to the vehicle indicated by the recognition result by the peripheral monitoring sensor.

Vehicular position specification apparatus and vehicular position specification method

A vehicle position estimation device is configured to acquire a distance from a road edge to a subject vehicle using at least one of an imaging device or a distance measuring sensor, acquire position information of lane boundary lines detected by analyzing the images captured by the imaging device; acquire map information including a lane quantity of a traveling road of the subject vehicle from a map storage, calculate, as a roadside area width, a lateral direction distance between an outermost detection line, which is an outermost boundary line among the detected boundary lines, and the road edge, and specify a traveling lane of the subject vehicle based on (i) the distance from the road edge to the subject vehicle, (ii) the roadside area width, and (iii) the lane quantity included in the acquired map information.

Vehicle position estimation device and traveling position estimation method

A course estimator has a first estimating means, a second estimating means and a determining means. The first estimating means obtains first information and estimating a first radius of a first forward traveling path on the basis of the obtained first information, the first forward traveling path being a part of a forward traveling path to which a vehicle is going to travel. The second estimating means obtains second information and estimating a second radius of a second forward traveling path on the basis of the obtained second information, the second forward traveling path being a part of the forward traveling path to which a vehicle is going to travel, the second forward traveling path being farther from the vehicle than the first traveling being. The determining means determines whether or not there is a changing point where road shapes change between the first forward traveling path and the second forward traveling path on the basis of comparison of the estimated first radius and the estimated second radius.

Course estimator and method of estimating a state of a course of a vehicle and a non-transitory computer-readable storage medium for the same

In an obstacle detection apparatus, a signal output unit is configured to output a signal if an obstacle meets at least one preset signal output condition. A condition setting unit is configured to set at least one element of the at least one signal output condition to a value in dependence on a user entry value. A misalignment detection unit is configured to detect misalignment of an axial direction of a sensor with a longitudinal direction of a vehicle carrying the apparatus. In the apparatus, an allowable range limiting unit is configured to, if a degree of misalignment exceeds a predetermined misalignment threshold, limit an allowable range of values of the at least one element of the at least one preset signal output condition so as to make the at least one preset signal output condition less prone to be met.

Obstacle detection apparatus

A driving support apparatus installed in a host vehicle calculates an overlap ratio relating to a target object positioned ahead of the host vehicle within the same traffic lane, as the ratio of the width of the target object to its lateral distance from a lane marker line of the traffic lane, and also detects the motion condition of the object (i.e., stationary, moving towards, or in the same direction as the host vehicle, or moving laterally with respect to the forward direction of the host vehicle). An amount of compensation for retarding or advancing the commencement of a collision avoidance operation by the driving support apparatus is determined based on the overlap ratio and/or the motion condition of the target object.

Vehicle driving support apparatus for executing collision avoidance operations based on position and motion condition of target object

A method and an apparatus are provided to recognize a shape of a road on which a vehicle is traveling. Road edge shapes on a left side and a right side of the vehicle are recognized, from positions of roadside objects detected based on detection information from an on-board radar. Lane shapes that are shapes of lane boundary lines on the left side and the right side of the vehicle are recognized, from positions of lane boundary lines detected based on an image captured by an on-board camera. For each of the left side and the right side, such that the recognized road edge shape and the recognized lane shape are compared with each other, and the road shape is identified based on the comparison results.

Method and apparatus for recognizing road shape

In an apparatus for controlling a vehicle to track another vehicle, a controller causes the controlled vehicle to track one of other vehicles as a target vehicle if one of the other vehicles meets a target-vehicle selecting condition. The target-vehicle selecting condition is required for selecting one of the other vehicles as the target vehicle. The controller recognizes an environment of a predicted travel road on which the controlled vehicle is predicted to travel using conditions of the predicted travel lane. The controller determines whether the predicted travel road allows lane changes based on the recognized environment of the predicted travel road. The controller adjusts the target-vehicle selecting condition based on a result of the determination.

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Aichi-ken, Japan

Yuusuke Matsumoto