Aisin Aw Co., Ltd.

Toyota Jidosha Kabushiki Kaisha

Kiyokazu Okada

Masaki Nakamura

Motohiro Nakamura

Makoto Hasunuma

Takayuki Miyajima

Satoshi Hirano

Koichi Nakao

Tomoaki Ishikawa

Motoki Kanba

Hidenobu Suzuki

Osamu Aisaka

Kenichi Murata

Daisuke Tanizaki

Kiyohide Kato

Naoto Miura

Devices, methods, and programs access map information including link information related to links that constitute a road, acquire a current location of a vehicle at unit time intervals, and acquire traffic information, which includes a distributed traffic congestion level of each link at predetermined time intervals. Each time the vehicle exits a link, the devices, methods, and programs sequentially store the exited link in an exited link train based on the map information. If the traffic information has been received, the devices, methods, and program store the distributed traffic congestion level included in the received traffic information as a traffic congestion level in association with a portion of the exited link train within a range from the current location at a received time point when the traffic information has been received to a location that is a predetermined distance behind the current location at the received time point.

Traffic information creating device, traffic information creating method and program

Devices, methods, and programs determine whether a vehicle has exited a link based on map information. If so, the devices, methods, and programs acquire a travel traffic congestion level of the exited link based on travel information within the exited link, and determine whether the travel traffic congestion level of the exited link coincides with a distributed traffic congestion level at a time when the vehicle exited. If not, the devices, methods, and programs determine whether the traffic information has been updated and the distributed traffic congestion level has been changed within the exited link, and if so, acquire a distribution time rate of each distributed traffic congestion level within the exited link. The devices, methods, and programs determine a traffic congestion level of the exited link based on the distribution time rate of each acquired distributed traffic congestion level and the travel traffic congestion level of the exited link.

A driving assistance apparatus is configured such that, in a case in which determination has been made there is a road marking within a predetermined range from a vehicle, the road marking is detected based upon an image acquired by a rear-side camera. In a case in which there is a single control target solely associated with the road marking thus detected, or in a case in which there are multiple control targets associated with the road marking, and the difference in the marking-target distance is equal to or greater than a driving control threshold distance, the target-vehicle distance, which is the distance between the vehicle and the control target that is a target for guidance and vehicle control, is calculated. The driving assistance apparatus performs guidance and vehicle control according to the control target based upon the target-vehicle distance thus calculated.

Driving assistance apparatus

A route guidance system includes: a current position detecting unit; a display condition determination processing unit that determines, for each of pieces of lane data that correspond to a lane list display section set in a forward direction of a vehicle position, whether a display condition for creating a lane list is satisfied, based on the pieces of lane data; a display setting processing unit that sets a piece of the lane data that satisfies the display condition as a display target; and a list display processing unit that displays the lane list based on the piece of the lane data that has been set as the display target. Thus, the piece of the lane data that satisfies the display condition is set as the display target, and the lane list is displayed based on the piece of the lane data that has been set as the display target. Consequently, the size of the lane list can be prevented from becoming too large.

Route guidance system and route guidance method

A feature extraction method includes: the step of grouping a cluster of features, in which an internal of the respective features is less than or equal to a predetermined grouping interval, to form a feature group, for a plurality of features of which feature information including at least information of a position and a feature type is included in a predetermined feature information storage unit; the step of excluding the feature, not suitable for use in an image recognition process of the feature with respect to image information, from the cluster of the features within the feature group; and the step of extracting a part or all of one or more of the features within the feature group remaining as a result of the exclusion step as a target feature suitable for the use in the image recognition process.

Feature extraction method, and image recognition method and feature database creation method using the same

A lane determining device includes: a feature information obtaining unit for obtaining feature information F of a target feature existing in each lane in the traveling direction of a vehicle, based on vehicle position information; an image recognizing unit for conducting image recognition processing of a feature type of the target feature in a vehicle lane, with respect to image information; and a lane accuracy determining unit for determining a vehicle lane accuracy for the respective lanes based on a type of a recognized feature fa shown in an image recognition result, feature types Ftto Ftof the target feature of the respective lanes shown in the feature information F, in accordance with a level of probability for each of the feature types Ftto Ftof the target feature of the respective lanes is recognized as the type of the recognized feature fa.

Lane determining device, lane determining method and navigation apparatus using the same

An accuracy error for measuring the position of an own vehicle is calculated based on the information of an execution history of map matching and the information of an update history of a map database. In addition, a predetermined map is referred to based on the calculated accuracy error, and an accuracy error level for performing positioning is specified from among plural stepwise levels. Then, the control level of assist control executed according to the position of the own vehicle is changed so as to correspond to the specified accuracy error level.

Support control device

Based on positioning accuracy of an own vehicle required for appropriately carrying out assistance control carried out according to a position of the own vehicle, an execution condition for map matching correcting the position of the own vehicle is set. Specifically, setting is made in such a manner that, as the positioning accuracy is higher and an error thereof is smaller, an execution frequency of map matching becomes higher. Then, map matching is carried out according to the thus-set execution condition.

Vehicle positioning information updating system

An object recognition device detects a position of a vehicle based on a running path obtained by GPS, vehicle speed, steering angle, etc., and also detects the position of the vehicle based on a result of recognition of an object obtained using a captured image of a camera. The device computes a positioning accuracy in detecting the vehicle position, which accuracy mostly deteriorates as a movement distance of the vehicle increases. Positional data of the object on the road to be recognized is stored in a map database beforehand. A recognition range of the road of the object to be recognized is set based on the detected position of the vehicle, a position of the object stored in the map database, and the computed positioning accuracy. The object is recognized for the set recognition range by processing of the captured image of the camera.

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Miyoshi, Japan

Kiyokazu Okada