Mitsubishi Electric Corporation

Kentaro Daikoku

Takashi Irie

Yuji Igarashi

Masahiko Ikawa

Masatoshi Fujii

Yuko Ohta

According to the present disclosure, a map matching apparatus includes a map information acquisition unit configured to acquire map information expressed by a plurality of links, a movement information acquisition unit configured to acquire movement information of a moving body on a predetermined route, and a matching unit configured to specify a link string, which is a string of the links corresponding to the route, based on the map information and the movement information, in which the matching unit is configured to generate a physical network, which is a road network, based on the connection relationship and the map information, generate a hierarchical logical network in which the physical network is duplicated in a plurality of layers and configured in a hierarchical manner, and specify the link string indicating a minimized cost in the hierarchical logical network.

Map matching apparatus and map matching method

A vehicle position estimation apparatus according to the present invention includes a painted line recognition result processing unit configured to calculate whether the vehicle has made a lane change and a direction of the lane change when the vehicle has made the lane change, a vehicle lateral position calculating unit configured to calculate a lane where the vehicle is in travel and a vehicle lateral position that is a lateral position of the vehicle in the lane based on whether the vehicle has made the lane change, the direction of the lane change, and a lane connection relation, and an on-map vehicle position calculating unit configured to calculate an on-map position of the vehicle on the road based on a map information, the lane where the vehicle is in travel, the vehicle lateral position, and a forward travel distance.

Vehicle position estimation apparatus

A travel-lane estimation system includes: a GNSS receiver; a vehicle-speed calculator; an angular-velocity measurement mechanism; a subject-vehicle-position positioner calculating a vehicle's reference coordinate and reference orientation from a GNSS coordinate, and calculating time series data of vehicle's positions; a map information storage storing positional information about a division line of each lane; and a lane estimator calculating, as an optimal correction amount, an error pattern having a highest posterior probability among plural error patterns, correcting the time series data using the optimal correction amount, and comparing the corrected time series data with the division line, to estimate a vehicle's travel lane, the posterior probability calculated with the product of prior occurrence probability of the time series data by the plural error patterns and a likelihood calculated, under condition that the error pattern has occurred, based on a relative positional relationship between the corrected time series data and the division line.

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Tokyo, Japan

Kentaro Daikoku