Scene ascertainment device
A situation and obstacle technology, applied in the field of situation understanding devices, can solve problems such as increased computing load and longer time to calculate the degree of danger
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
no. 1 approach
[0026] Next, embodiments of the present invention will be described in detail with reference to the drawings.
[0027] (first embodiment)
[0028] refer to figure 1 An overall configuration of a driving assistance device 1 a including the situation understanding device of the first embodiment will be described. The driving assistance device 1a determines the behavior of the own vehicle based on the degree of danger (situation) of intersecting with other vehicles or people at a specific point on the planned driving route of the own vehicle (driving assistance (assist driving) method), and executes driving assistance ( Assisted driving) device. The situation understanding device is a device that calculates the degree of risk, that is, understands the situation (understands the situation, comprehends the situation, and confirms the situation sceneascertainment). The specific point refers to a point on the road where vehicles or vehicles cross each other, for example, an inters...
Embodiment approach
[0072] As described above, according to the first embodiment of the present invention, the following effects are obtained.
[0073] The situation understanding device calculates the degree of danger at a specific point based on the presence or absence of an obstacle in the obstacle detection frame 42 having a shape corresponding to the road structure set in advance in the map data. Therefore, an obstacle detected at a position not related to the calculation of the risk level can be excluded from the processing target, so that an excessive increase in the calculation load can be suppressed.
[0074] like Figure 6 As shown, the risk calculation unit 27 calculates the risk of a specific point based on whether or not the gaze frame 48 on which the host vehicle 46 should focus overlaps with the blind spot 50 caused by the obstacle 49 . Therefore, it is possible to calculate the degree of danger at a specific point by assuming that an obstacle exists in the blind spot 50 .
[007...
no. 2 approach
[0081] refer to Figure 10 and Figure 11 The configuration of the driving assistance device 1b including the situation understanding device of the first embodiment will be described. and figure 1 The difference is that the driving assistance device 1b includes a knowledge database 17 instead of the risk database 16 . The knowledge database 17 stores obstacle detection frames 42 identified from the position of the own vehicle at a specific point and data (knowledge tree) indicating the sequence of obstacle detection frames 42 that should be paid attention to. The position of the host vehicle at a specific point includes, for example, an entrance, an inside, and an exit at a specific point. The order of the obstacle detection frame 42 and the obstacle detection frame 42 to be noted is determined for each of the entrance, interior, and exit of the specific point. Of course, in the knowledge tree, the order of the attention frame 48 and the attention frame 48 to be paid atten...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


