IP Library › Granted Patent US 11,535,247
Granted Patent B2
US 11,535,247 · App. 17/046,776 · Granted Dec 27, 2022

Method and device for a cooperative coordination between future driving maneuvers of one vehicle and the maneuvers of at least one other vehicle

Inventors: Hendrik Fuchs (Hildesheim, DE); Florian Wildschütte (Hildesheim, DE); Thomas Michalke (Weil der Stadt, DE); Ignacio Llatser Marti (Hildesheim, DE); Maxim Dolgov (Renningen, DE); Sebastian Strunck (Niedernhausen, DE); Jonas Schönichen (Weiterstadt, DE); Thomas Grotendorst (Eschborn, DE)
Assignees: Robert Bosch GMBH; Continental Automotive Technologies GMBH
B60W30/0956B60W30/0953G06K9/6267H04W4/46B60W2554/4045B60W2554/4049
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Quick Facts
Patent No.
US 11,535,247
App. No.
17/046,776
Granted
Dec 27, 2022
Kind
B2
Abstract

The present invention relates to a method of cooperatively coordinating future driving maneuvers of a vehicle with fellow maneuvers of at least one fellow vehicle, wherein trajectories for the vehicle are rated with an effort value each, trajectories and fellow trajectories of the fellow vehicle are combined into tuples, the trajectory and the associated effort value of a collision-free tuple are selected as reference trajectory and reference effort value, trajectories with a lower effort value than the reference effort value are classified as demand trajectories, trajectories with higher effort value than the reference effort value are classified as alternative trajectories, and a data packet having a trajectory set consisting of the reference trajectory and the associated reference effort value as well as at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the respective effort values is transmitted to the fellow vehicle.

Claims (24)

1. A method performed by a processor of a vehicle for automated cooperatively coordinating future driving maneuvers of the vehicle with fellow maneuvers of at least one fellow vehicle, the method comprising the following steps:

automatically rating a trajectory set of pre-planned trajectories for the vehicle with one effort value each using at least one rating criterion;

automatically receiving a fellow data packet from the fellow vehicle, wherein the fellow data packet contains a fellow trajectory set with different pre-planned fellow trajectories for the fellow vehicle and a fellow effort value for each fellow trajectory;

automatically combining one trajectory and one fellow trajectory each into tuples and combining the respective effort value with the respective fellow effort value into a tuple effort value of the tuple;

automatically selecting collision-free tuples, wherein tuples are selected where the trajectory and the fellow trajectory are collision-free within a collision horizon;

automatically selecting the collision-free tuple with the lowest tuple effort value and classifying the trajectory and the associated effort value of this tuple as reference trajectory and reference effort value;

controlling the vehicle using the reference trajectory;

automatically selecting trajectories having a lower effort value than the reference effort value and classifying these trajectories and associated effort values as demand trajectories and demand effort values, wherein a demand trajectory is an intended trajectory of the vehicle, with which a desired travel destination may be reached more favorably than with the reference trajectory;

automatically selecting trajectories having a higher effort value than the reference effort value and classifying these trajectories and associated effort values as alternative trajectories and alternative effort values, wherein an alternative trajectory is a trajectory indicating a cooperation offer of the vehicle that the vehicle might be willing to drive if applicable; and

automatically transmitting a data packet to the fellow vehicle, wherein the data packet contains a trajectory set of the reference trajectory and the associated reference effort value and at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the corresponding effort values.

2. The method according to claim 1 , wherein in the step of selecting, the collision horizon is situation dependent.

3. The method according to claim 1 , wherein in the step of receiving, the fellow data packet further contains sensor data of the fellow vehicle, wherein at least one of

in the step of selecting, the collision horizon is set using the sensor data or

in the step of transmitting, the data packet further contains sensor data of the vehicle.

4. The method according to claim 1 , wherein in the step of selecting, the collision-free tuples are selected using the road traffic regulations, wherein tuples whose trajectory has priority over the fellow trajectory are selected as collision-free tuples.

5. The method according to claim 1 , wherein in the step of receiving, at least one further fellow data packet is received from a further fellow vehicle, wherein in the step of combining, a further fellow trajectory is added to the tuple, wherein the tuple effort value is supplemented with a further fellow effort value.

6. The method according to claim 1 , wherein in the step of receiving, the fellow trajectory set further comprises a fellow reference trajectory of the fellow vehicle and a fellow reference effort value of the fellow reference trajectory, wherein in the step of combining, fellow reference tuples are combined from the fellow reference trajectory and one of the trajectories, wherein in the step of selecting, the trajectory of the collision-free fellow reference tuple with the lowest tuple effort value is selected as reference trajectory.

7. The method according to claim 1 , wherein in the step of receiving, a category is received for at least one fellow trajectory, wherein in the step of selecting, the reference trajectory is further selected using the category.

8. The method according to claim 1 , wherein in the step of selecting, the alternative trajectories are selected from tuples that are collision-free within the collision horizon.

9. The method according to claim 1 , wherein in the step of combining, the fellow trajectory is predicted at least up to a prediction horizon of the vehicle if the fellow vehicle uses a shorter fellow prediction horizon.

10. The method according to claim 1 , wherein in the step of combining, the fellow trajectories are transformed to a calculation time of the trajectories.

11. A device, wherein the device is adapted to at least one of execute, implement and control the method according to claim 1 in corresponding units.

12. A computer program product adapted to at least one of execute, implement and control the method according to claim 1 .

13. A machine readable storage medium on which the computer program product according to claim 12 is stored.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 18, 2022
From: CONTINENTAL TEVES AG & CO. OHG
To: CONTINENTAL AUTOMOTIVE TECHNOLOGIES GMBH
Reel/Frame 060845/0339 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 11, 2020
From: FUCHS, HENDRIK; WILDSCHÜTTE, FLORIAN; MICHALKE, THOMAS; LLATSER MARTI, IGNACIO; DOLGOV, MAXIM; STRUNCK, SEBASTIAN; SCHÖNICHEN, JONAS; GROTENDORST, THOMAS
To: ROBERT BOSCH GMBH; CONTINENTAL TEVES AG & CO. OHG
Reel/Frame 054612/0941 →
Priority Claims (1)
DE 102018109883.9 · Apr 24, 2018 · national
Continuity (1)
Related Publication 20210146922A1 · May 20, 2021
Cited By (1)
US 12,664,890