Abstract: A distance estimating device has a processor configured to calculate first and second right side distances between a moving object and a right side feature and first and second left side distances between the moving object and a left side feature, determine a reference feature-to-feature distance between the right and left side feature at the current location, and estimate a right side and left side distance combination, where the feature-to-feature distance between a right left side feature obtained for each combination of first right side distance corrected by an estimation error or second right side distance and first left side distance corrected by an estimation error or second left side distance, is closest to a reference distance, determining it to be the distance between the moving object and the right side feature and the distance between the moving object and the left side feature, for the current location.

Abstract: The vehicle position estimation device includes a processor configured to estimate a vertical position of a vehicle based on an output of a vehicle state detection device, detect actual dividing lines at both left and right sides of the vehicle, compare a dividing line on a map at the vertical position of the vehicle and an actual dividing line and estimate a horizontal position of the vehicle, and determine a driving route of the vehicle. The processor is configured to calculate an amount of change of a horizontal position with respect to the driving route based on a map information for each of dividing lines of both left and right sides of the driving route in a predetermined range, and determine a dividing line on the map for comparison based on the amounts of change.

Abstract: A host vehicle position estimation device includes: a detected position recognition unit configured to recognize a detected position of a first target object included in a first recognition range and a detected position of a second target object included in a second recognition range; a host vehicle first position estimation unit configured to estimate a host vehicle first position; a host vehicle second position estimation unit configured to estimate a host vehicle second position; and a deviation determination unit configured to determine that there is a deviation between the detected position of the target object and the information on the position of the target object on the map if a distance between the host vehicle first position and the host vehicle second position is equal to or greater than a deviation threshold value.

Abstract: A distance estimating device has a processor configured to calculate first and second right side distances between a moving object and a right side feature and first and second left side distances between the moving object and a left side feature, determine a reference feature-to-feature distance between the right and left side feature at the current location, and estimate a right side and left side distance combination, where the feature-to-feature distance between a right left side feature obtained for each combination of first right side distance corrected by an estimation error or second right side distance and first left side distance corrected by an estimation error or second left side distance, is closest to a reference distance, determining it to be the distance between the moving object and the right side feature and the distance between the moving object and the left side feature, for the current location.

Abstract: A host vehicle position estimation device includes an object determination unit configured to determine whether or not a planar object is included in a captured image, on which a host vehicle travels, a center point information acquisition unit configured to, when the planar object is included in the captured image, acquire center point information of the planar object including at least one of longitudinal center coordinate and lateral center coordinate of the planar object in the captured image, a longitudinal distance calculation unit configured to calculate a longitudinal distance as a distance between the host vehicle and the planar object in a front-rear direction of the host vehicle, and a host vehicle position estimation unit configured to estimate a host vehicle position using the positional information of the planar object on the map and the longitudinal distance.

Abstract: A vehicle localization device includes: a target database; a target recognition unit configured to recognize, based on a detection result of an in-vehicle sensor, a relative position of the first target relative to a vehicle and a relative position of the second target relative to the vehicle; a lateral position estimation unit configured to estimate a lateral position of the vehicle and a direction of the vehicle based on the relative position of the first target relative to the vehicle and the position information on the first target on the map; and a longitudinal position estimation unit configured to estimate a longitudinal position of the vehicle by reflecting the lateral position of the vehicle and the direction of the vehicle.

Abstract: A host vehicle position estimation device includes an object determination unit configured to determine whether or not a planar object is included in a captured image, on which a host vehicle travels, a center point information acquisition unit configured to, when the planar object is included in the captured image, acquire center point information of the planar object including at least one of longitudinal center coordinate and lateral center coordinate of the planar object in the captured image, a longitudinal distance calculation unit configured to calculate a longitudinal distance as a distance between the host vehicle and the planar object in a front-rear direction of the host vehicle, and a host vehicle position estimation unit configured to estimate a host vehicle position using the positional information of the planar object on the map and the longitudinal distance.

Abstract: A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit. The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of a ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Abstract: A host vehicle position estimation device includes: a detected position recognition unit configured to recognize a detected position of a first target object included in a first recognition range and a detected position of a second target object included in a second recognition range; a host vehicle first position estimation unit configured to estimate a host vehicle first position; a host vehicle second position estimation unit configured to estimate a host vehicle second position; and a deviation determination unit configured to determine that there is a deviation between the detected position of the target object and the information on the position of the target object on the map if a distance between the host vehicle first position and the host vehicle second position is equal to or greater than a deviation threshold value.

Abstract: In a location estimation device, a change detection unit detects a point of change in the width of a roadside structure as a width change point. A width correction unit calculates a width deviation between a first relative location of the roadside structure on a map data segment and a second relative location of the roadside structure obtained based on shape information of the roadside structure in the width direction of a vehicle. The width correction unit corrects, as a function of the width deviation and a positional accuracy of the vehicle in the travelling direction, an estimated location of the vehicle in the width direction when it is determined that there is the point of change in the width of the roadside structure in the travelling direction of the vehicle.

Abstract: A vehicle localization device includes: a target database; a target recognition unit configured to recognize, based on a detection result of an in-vehicle sensor, a relative position of the first target relative to a vehicle and a relative position of the second target relative to the vehicle; a lateral position estimation unit configured to estimate a lateral position of the vehicle and a direction of the vehicle based on the relative position of the first target relative to the vehicle and the position information on the first target on the map; and a longitudinal position estimation unit configured to estimate a longitudinal position of the vehicle by reflecting the lateral position of the vehicle and the direction of the vehicle.

Abstract: An in-vehicle system as a road curvature detection device calculates a curvature of a road in front of a vehicle based on an acquired front scene image. The in-vehicle system receives gradient information from the data map. The gradient information corresponds to a current road section on the road on which the vehicle drives. The in-vehicle system detects a gradient accuracy of the received gradient information. When the current road section has a gradient, i.e. the road is an uphill or downhill road, the in-vehicle system selects an appropriate special detection methods based on the gradient accuracy of the received gradient information, and calculates a road curvature by using the selected special detection method. Each of the special detection methods calculates a road curvature while effectively suppressing influence of a road gradient indicated by the received gradient information.

Abstract: A method and apparatus for driving assisting provided with an ECU which includes an extraction unit extracting a shape and a distribution of a landmark on a plurality of routes leading to a destination on a map, an accuracy calculation unit calculating an estimated accuracy of a vehicle position at each sampling point positioned at predetermined intervals on each route, on the basis of the shape and distribution of each landmark, an operating ratio calculation unit calculating an operating ratio of a driving assistance control on each of the routes, on the basis of the calculated accuracy at each sampling point, and a route selection unit which enables a driver of the vehicle to select a route among the plurality of routes, after the calculated operating ratio is presented to the driver.

Abstract: A vehicle location recognition device has a correction unit for correcting a position of an own vehicle detected by a vehicle position estimation unit. The correction unit corrects the position of the own vehicle so as to reduce a difference in position between a position of a road object detected by a sensor and a position of a map road object contained in map road object information stored in a memory unit. When there are plural combinations of road objects detected by the sensor and map road objects acquired from the map road object information, the correction unit uses a weight value to adjust a likelihood of each of the combinations, and corrects the position of the own vehicle based on the weighted likelihood. The weight value is increased according to increasing of a magnitude of the likelihood.

Abstract: In a location estimation device, a change detection unit detects a point of change in the width of a roadside structure as a width change point. A width correction unit calculates a width deviation between a first relative location of the roadside structure on a map data segment and a second relative location of the roadside structure obtained based on shape information of the roadside structure in the width direction of a vehicle. The width correction unit corrects, as a function of the width deviation and a positional accuracy of the vehicle in the travelling direction, an estimated location of the vehicle in the width direction when it is determined that there is the point of change in the width of the roadside structure in the travelling direction of the vehicle.

Abstract: A vehicle localization system is provided which localizes a system-equipped vehicle. The vehicle localization system determines a position of the system-equipped vehicle on a map using a map matching technique. The vehicle localization system also calculates a variation in arrangement of feature points (e.g., edge points) of a roadside object around the system-equipped vehicle in a captured image and corrects the calculated position of the system-equipped vehicle on the map using the variation in arrangement of the feature points. This ensures a required accuracy in localizing the system-equipped vehicle.

Abstract: A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit. The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Abstract: An in-vehicle system as a road curvature detection device calculates a curvature of a road in front of a vehicle based on an acquired front scene image. The in-vehicle system receives gradient information from the data map. The gradient information corresponds to a current road section on the road on which the vehicle drives. The in-vehicle system detects a gradient accuracy of the received gradient information. When the current road section has a gradient, i.e. the road is an uphill or downhill road, the in-vehicle system selects an appropriate special detection methods based on the gradient accuracy of the received gradient information, and calculates a road curvature by using the selected special detection method. Each of the special detection methods calculates a road curvature while effectively suppressing influence of a road gradient indicated by the received gradient information.