Object detection method and object detection apparatus
An object detection method includes: acquiring three-dimensional data on an area around a host vehicle by use of a distance measurement sensor; based on map data on an area around a current position of the host vehicle, setting a planned travel area where the host vehicle is going to travel in the future; estimating crossing object existence areas where there currently exist objects which are likely to cross the host vehicle in the future in the set planned travel area; and detecting the object by use of the three dimensional data on insides of the estimated crossing object existence areas.
1. An object detection method for an object detection apparatus including a distance measurement sensor for acquiring three-dimensional data on an area around a host vehicle, and configured to detect an object by use of the three-dimensional data acquired by the distance measurement sensor, comprising:
based on map data on an area around a current position of the host vehicle, extracting a vehicle traffic lane which the host vehicle is estimated to travel on a planned travel route from the current position of the host vehicle to a destination as a planned travel area,
based on road structure information included in the map data, estimating road categories whose traveling directions point to the planned travel area as crossing object existence areas where there currently exist objects which are likely to cross the host vehicle in the future in the planned travel area,
detecting the road categories around the current position of the host vehicle from the road structure information, extracting the crossing object existence areas by extracting the road categories which cross the planned travel area from the detected road categories, and
detecting the object by use of the three-dimensional data on insides of the crossing object existence areas.
2. The object detection method according to claim 1 , wherein the planned travel area is set based on travel plan information of the host vehicle.
3. The object detection method according to claim 1 , wherein traveling directions of the objects which are likely to cross the host vehicle in the future are estimated from the planned travel area and the road structure information included in the map data,
the crossing object existence areas are estimated based on the traveling directions.
4. The object detection method according to claim 1 , wherein in a case where the host vehicle is going to change lanes, the crossing object existence areas are estimated in a part of a lane into which the host vehicle is going to move and in a part of a lane adjacent to the lane into which the host vehicle is going to move, the parts extending frontward and rearward from the host vehicle.
5. The object detection method according to claim 1 , wherein in a case where the host vehicle is going to travel straight on a multi-lane road, the crossing object existence areas are estimated in parts of lanes adjacent to the planned travel area, the parts each located frontward of the host vehicle.
6. The object detection method according to claim 1 , wherein a size of the crossing object existence areas is set depending on a speed of the host vehicle, or a relative speed between the host vehicle and objects existing around the host vehicle.
7. The object detection method according to claim 1 , wherein the planned travel area is set based on a lane category of a vehicle traffic lane where the host vehicle is traveling, the lane category recorded in the road structure information included in the map data.
8. The object detection method according to claim 1 , wherein the crossing object existence areas are estimated based on a state of a traffic signal around the host vehicle.
9. The object detection method according to claim 1 , wherein the crossing object existence areas are estimated based on a road regulation governing the area around the host vehicle.
10. An object detection apparatus including a distance measurement sensor for acquiring three-dimensional data on an area around a host vehicle, and configured to detect an object by use of the three-dimensional data acquired by the distance measurement sensor,
comprising a controller for
based on map data on an area around a current position of the host vehicle, extracting a vehicle traffic lane which the host vehicle is estimated to travel on a planned travel route from the current position of the host vehicle to a destination as a planned travel area,
based on road structure information included in the map data, estimating road categories whose traveling directions point to the planned travel area as crossing object existence areas where there currently exist objects which are likely to cross the host vehicle in the future in the planned travel area,
detecting the road categories around the current position of the host vehicle from the road structure information, extracting the crossing object existence areas by extracting the road categories which cross the planned travel area from the detected road categories, and
detecting the object by use of the three-dimensional data on insides of the crossing object existence areas.