Traveling environment recognition device
First Claim
1. A traveling environment recognition device recognizes a traveling environment of one'"'"'s own vehicle, the device comprising:
- own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and
occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of a plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises;
object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects a forward object of the own vehicle, which is one of the obstacles, the occupancy probability of the forward object for each cell of the occupancy grid map;
other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map;
traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and
occupancy probability blending means for blending for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle,wherein the radar device is configured to detect a three-dimensional object as the forward object,the object occupancy probability calculating means is configured to,when the radar device detects a single three-dimensional object, calculate the occupancy probability of the three-dimensional object according to a first sensor model that defines the occupancy probability of the three-dimensional object as a function of a direct distance from a detection wave emitting point of the radar device along a straight line through the detection wave emitting point and an observed point of the three-dimensional object,and when the radar device detects two three-dimensional objects at their respective observed points along a straight line through the two observed points and the detection wave emitting point of the radar device, the object occupancy probability calculating means calculates the occupancy probability of the two three-dimensional objects according to a second sensor model that defines the occupancy probability of two the three-dimensional objects as a function of a direct distance from the detection wave emitting point of the radar device along the straight line such that the occupancy probability at the observed point closer to the own vehicle is set smaller than the occupancy probability at the observed point further away from the own vehicle.
1 Assignment
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Accused Products
Abstract
A traveling environment recognition device capable of accurately recognizing a traveling environment of a vehicle. An occupancy grid map that stores an occupancy probability of each obstacle to traveling of the own vehicle for each cell of the occupancy grid map is generated, and the occupancy probability for each cell is updated according to Bayesian inference. More specifically, for each cell of the occupancy grid map, the occupancy probability calculated from information from a radar device, the occupancy probability calculated from information from a communication device, and the occupancy probability calculated from information from a storage device that stores map data are blended to provide an occupancy probability of the obstacles to traveling of the own vehicle, which leads to more accurate traveling environment recognition.
40 Citations
14 Claims
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1. A traveling environment recognition device recognizes a traveling environment of one'"'"'s own vehicle, the device comprising:
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own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of a plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises; object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects a forward object of the own vehicle, which is one of the obstacles, the occupancy probability of the forward object for each cell of the occupancy grid map; other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map; traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and occupancy probability blending means for blending for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, wherein the radar device is configured to detect a three-dimensional object as the forward object, the object occupancy probability calculating means is configured to, when the radar device detects a single three-dimensional object, calculate the occupancy probability of the three-dimensional object according to a first sensor model that defines the occupancy probability of the three-dimensional object as a function of a direct distance from a detection wave emitting point of the radar device along a straight line through the detection wave emitting point and an observed point of the three-dimensional object, and when the radar device detects two three-dimensional objects at their respective observed points along a straight line through the two observed points and the detection wave emitting point of the radar device, the object occupancy probability calculating means calculates the occupancy probability of the two three-dimensional objects according to a second sensor model that defines the occupancy probability of two the three-dimensional objects as a function of a direct distance from the detection wave emitting point of the radar device along the straight line such that the occupancy probability at the observed point closer to the own vehicle is set smaller than the occupancy probability at the observed point further away from the own vehicle.
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2. A traveling environment recognition device that recognizes a traveling environment of one'"'"'s own vehicle, the device comprising:
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own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of a plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises; object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects a plurality of forward objects of the own vehicle, which is one of the obstacles, the occupancy probability of the forward object for each cell of the occupancy grid map; other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map; traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and occupancy probability blending means for blending, for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, wherein the radar device is configured to detect a three-dimensional object and a traffic lane line as the forward objects, the object occupancy probability calculating means calculates the occupancy probability of the three-dimensional object according to a first sensor model that defines the occupancy probability of the three-dimensional object as a function of a direct distance from a detection wave emitting point of the radar device along a straight line through the detection wave emitting point and an observed point of the three-dimensional object, and the object occupancy probability calculating means calculates the occupancy probability of the traffic lane line according to a second sensor model such that the occupancy probability of the traffic lane line is set smaller than the occupancy probability of the three-dimensional object.
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3. A traveling environment recognition device that recognizes a traveling environment of one'"'"'s own vehicle, the device comprising:
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own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of the plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises; object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects a forward object of the own vehicle, which is one of the obstacles, the occupancy probability of the forward object for each cell of the occupancy grid map; other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map; traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and occupancy probability blending means for blending, for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupant probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, wherein the communication device receives information about a position and a traveling direction of the another vehicle as the positional information, and the other vehicle occupancy probability calculating means calculates the occupancy probability of the another vehicle according to a sensor model that defines a correspondence relation between a position with reference to a contour of the another vehicle and the occupancy probability of the another vehicle.
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4. A traveling environment recognition device that recognizes a traveling environment of one'"'"'s own vehicle, the device comprising:
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own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of a plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises; object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects at least one forward object of the own vehicle, which is one of the obstacles the occupancy probability of the forward object for each cell of the occupancy grid map; other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map; traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and occupancy probability blending means for blending, for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, the device further comprising; low-resolution occupancy grid map generating means for grouping a predetermined number of mutually adjacent cells of the grid into a larger cell of a low-resolution grid over the grid, and generating a low-resolution occupancy grid map that stores a low-resolution occupancy probability of each one of the obstacles to the position and traveling direction of the own vehicle for each cell of the low-resolution grid, and updating the low-resolution occupancy probability according to the Bayesian inference, wherein the low-resolution occupancy grid map generating means comprises; low-resolution object occupancy probability calculating means for calculating, on the basis of the information from the radar device, the low-resolution occupancy probability of the forward object for each cell of the low-resolution occupancy grid map; low-resolution other vehicle occupancy probability calculating means for calculating, on the basis of the information from the communication device, the low-resolution occupancy probability of the another vehicle for each cell of the low-resolution occupancy grid map; low-resolution traffic lane line occupancy probability calculating means for calculating, on the basis of the information from the storage device that stores the map data, the low-resolution occupancy probability of the traffic lane line for each cell of the low-resolution occupancy grid map; and low-resolution occupancy probability blending means for blending, for each cell of the low-resolution occupancy grid map, the low-resolution occupancy probability calculated by the low-resolution object occupancy probability calculating means, the low-resolution occupancy probability calculated by the low-resolution other vehicle occupancy probability calculating means, and the low-resolution occupancy probability calculated by the low-resolution traffic lane line occupancy probability calculating means to provide a low-resolution blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, the device still further comprising; low-resolution grid cell selecting means for selecting, from the equal larger cells of the low-resolution occupancy grid map, a cell that has the low-resolution blended occupancy probability of the obstacles calculated by the low-resolution occupancy probability blending means that is larger than a predetermined threshold, wherein the object occupancy probability calculating means calculates, on the basis of the information from the radar device, the occupancy probability of the forward object for each cell of each larger cell of the low-resolution occupancy grid map that is selected by the low-resolution grid cell selecting means, the other vehicle occupancy probability calculating means calculates, on the basis of the information from the communication device, the occupancy probability of the another vehicle for each cell of each larger cell of the low-resolution occupancy grid map that is selected by the low-resolution grid cell selecting means; the traffic lane line occupancy probability calculating means calculates, on the basis of the information from the storage device that stores map data, the occupancy probability of the traffic lane line for each cell of each larger cell of the low-resolution occupancy grid map that is selected by the low-resolution grid cell selecting means; and the occupancy probability blending means blends, for each cell of each larger cell of the low-resolution occupancy grid map that is selected by the low-resolution grid cell selecting means, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide the blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle. - View Dependent Claims (5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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Specification