Processing sensor measurements of a vehicle environment with low transverse resolution

• US 10,386,483 B2
• Filed: 08/01/2017
• Issued: 08/20/2019
• Est. Priority Date: 02/02/2015
• Status: Active Grant

• Current Assignee: Bayerische Motoren Werke AG
• Original Assignee: Bayerische Motoren Werke AG
• Inventors: Walessa, Marc
• Primary Examiner(s): Chen, Shelley
• Application Number:
  US15/665,569
• Publication Number:
  US 20170329008A1
• Time in Patent Office: 749 Days
• Field of Search: None
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 15/89 for mapping or imaging
• CPC Class Codes: G01S 15/931 of land vehicles
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 2015/933 for measuring the dimensions of the parking space when driving past
• CPC Class Codes: G01S 7/53 Means for transforming coordinates or for evaluating data, e.g. using computers
• CPC Class Codes: G05D 1/0257 using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

An environment map includes cells, each of which is assigned to portions of the environment of a vehicle and each of which is assigned an obstacle probability that represents the probability that the corresponding portion of the environment is occupied by an obstacle. The vehicle has at least two environment sensors, each of which is designed to provide measurement data on the occupancy of a region of the environment by an obstacle, referred to as an obstacle region, in the respective detection region of the sensor. The measurement data describes obstacle regions which extend over multiple portions of the environment, and the detection regions of the environment sensors at most partly overlap. A method for providing the environment map for the vehicle has the following steps: receiving the measurement data from the at least two environment sensors, the measurement data of a first environment sensor identifying an obstacle region; determining occupancy probabilities for the portions of the environment covered by the identified obstacle region of the measurement data of the first environment sensor on the basis of the measurement data of at least one other environment sensor, wherein an occupancy probability for a portion indicates the probability that the corresponding portion of the environment is occupied by an obstacle; and updating the obstacle probability of the environmental map for at least the portions for which the occupancy probability has been determined.

Claims

1. A method for providing an environment map for a vehicle, wherein

the environment map comprises cells, each of which is assigned to portions of surroundings of the vehicle and each of which is assigned an obstacle probability that represents the probability that the corresponding portion of the surroundings is occupied by an obstacle;

the vehicle comprises at least two surroundings sensors, each of which is configured to provide measurement data on the occupancy of a region of the surroundings by an obstacle (an obstacle region) in the respective capture region;

the measurement data describe obstacle regions which extend over a plurality of portions of the surroundings; and

the capture regions of the surroundings sensors overlap at most in part;

wherein the method comprises the acts of;

receiving the measurement data from the at least two surroundings sensors, wherein the measurement data from a first surroundings sensor have an obstacle region;

determining occupancy probabilities for those portions of the surroundings which are covered by the established obstacle region in the measurement data from the first surroundings sensor, depending on the measurement data from at least a further one of the surroundings sensors, wherein an occupancy probability for a portion specifies the probability that the corresponding portion of the surroundings is occupied by an obstacle; and

updating the obstacle probability of the environment map for at least those portions for which the occupancy probability was determined, wherein the occupancy probability for a covered portion which is situated at a first distance from the capture region of the further sensor depends more strongly on the measurement data from the further sensor than the occupancy probability for a covered portion which is situated at a greater distance than the first distance from the capture region of the further sensor.

2. The method as claimed in claim 1, wherein different occupancy probabilities are determined for at least two different covered portions.

3. The method as claimed in claim 1, wherein

the occupancy probability of the portions that are covered by the obstacle occupancy are determined, up to a constant, in accordance with a linear function or other desired continuous or discontinuous function, and

the function is predetermined by the sensor data from the considered surroundings sensor and from the at least one further surroundings sensor.

4. The method as claimed in claim 1, wherein

the spatial relationship between the capture regions of the first surroundings sensor and of the at least one further surroundings sensor is taken into account when determining the occupancy probabilities.

5. The method as claimed in claim 1, wherein

the measurement data from the further sensor have no obstacle region;

and

the occupancy probability for a covered portion which is situated at a first distance from the capture region of the further sensor is determined to have a lower value than the occupancy probability for a covered portion that is situated at a greater distance than the first distance from the capture region of the further sensor.

6. The method as claimed in claim 1, wherein

the vehicle comprises at least three surroundings sensors, the capture regions of which are next to one another and in each case adjacent to one another, and said capture regions overlap at most in part in each case;

wherein the method further comprises the acts of;

receiving the measurement data from the at least three surroundings sensors, wherein the measurement data from the central surroundings sensor have an obstacle region;

determining the occupancy probability for those portions of the surroundings which are covered by the established obstacle region in the measurement data from the central surroundings sensor, depending on the measurement data from the two adjacent surroundings sensors.

7. The method as claimed in claim 6, wherein

the occupancy probability is determined depending on whether the measurement data from only one adjacent surroundings sensor or from both adjacent surroundings sensors have an obstacle region.

8. The method as claimed in claim 7, wherein

the highest occupancy probability of the covered portions is determined for the occupancy probability of one or more covered portions that do not lie on the edge of the obstacle region if the sensor data from both adjacent surroundings sensors do not have an obstacle region in each case.

9. The method as claimed in claim 1, wherein

the measurement data provide the distance of an obstacle from the respective surroundings sensor, and

the measurement data do not provide any information about the extent of the obstacle in the capture region.

10. The method as claimed in claim 9, wherein the surroundings sensors are ultrasonic sensors.

11. The method as claimed in claim 1, wherein

the obstacle probabilities previously stored in the environment map are complemented by the occupancy probabilities when updating the obstacle probability.

12. The method as claimed in claim 11, wherein

the obstacle probabilities previously stored in the occupancy probabilities when updating the obstacle probability are combined via calculation.

13. An electronic computing device for a vehicle, wherein the electronic computing device is configured to execute the method as claimed in claim 1.