Sideslip compensated control method for autonomous vehicles

Patent metadata

Field	Value
Publication number	US-10019008-B2
Application number	US-201615279141-A
Country	US
Kind code	B2
Filing date	Sep 28, 2016
Priority date	Sep 28, 2016
Publication date	Jul 10, 2018
Grant date	Jul 10, 2018

Abstract

A set of driving scenarios are determined for different types of vehicles. Each driving scenario corresponds to a specific movement of a particular type of autonomous vehicles. For each of the driving scenarios of each type of autonomous vehicles, a set of driving statistics is obtained, including driving parameters used to control and drive the vehicle, a driving condition at the point in time, and a sideslip caused by the driving parameters and the driving condition under the driving scenario. A driving scenario/sideslip mapping table or database is constructed. The scenario/sideslip mapping table includes a number of mapping entries. Each mapping entry maps a particular driving scenario to a sideslip that is calculated based on the driving statistics. The scenario/sideslip mapping table is utilized subsequently to predict the sideslip under the similar driving environment, such that the driving planning and control can be compensated.

First claim

What is claimed is:

1. A computer-implemented method for operating an autonomous vehicle, the method comprising:
defining a plurality of driving scenarios for a plurality of types of autonomous vehicles, each driving scenario corresponding to a specific movement of a particular type of autonomous vehicles;
for each of the driving scenarios of each type of autonomous vehicles, obtaining driving statistics of each autonomous vehicle, including
recording one or more driving parameters used to control and drive each autonomous vehicle of the type,
capturing a driving condition corresponding the driving scenario, and
calculating an average sideslip caused by the driving parameters and the driving condition based on sideslips of a number of autonomous vehicles of the type under identical driving conditions; and

storing a driving scenario to a sideslip (scenario/sideslip) mapping table having a plurality of mapping entries to map the driving scenario to the calculated average sideslip, wherein the scenario/sideslip mapping table is utilized to compensate a sideslip under a similar driving scenario, the method further including
determining a driving scenario based on a driving condition of an autonomous vehicle;
identifying an entry matching the driving scenario from the scenario/sideslip mapping table;
obtaining an average sideslip from the matching entry; and
adjusting a steering angle of the autonomous vehicle using the obtained average sideslip.

2. The method of claim 1 , further comprising:
in response to determining a next movement of the autonomous vehicle, determining a first driving scenario corresponding to the next movement;
searching in the scenario/sideslip mapping table based on the first driving scenario to locate a mapping entry corresponding to a second driving scenario matching the first driving scenario; and
determining the next movement for the autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry.

3. The method of claim 2 , wherein determining the next movement for the autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry comprises:
calculating a first steering angle based on a speed required by a route associated with the next movement using a predetermined algorithm;
modifying the first steering angle in view of the first sideslip obtained from the located mapping entry, generating a second steering angle; and
controlling the autonomous vehicle based on the second steering angle.

4. The method of claim 1 , wherein the driving condition comprises at least one of a type of road or a weather condition.

5. The method of claim 1 , wherein a driving parameter identifies an action an autonomous vehicle is taking, a speed during the action, or a steering angle during the action.

6. The method of claim 5 , wherein the driving parameter further identifies a type of an autonomous vehicle involved.

7. The method of claim 5 , wherein the action is one of a left turn, a right turn, or a U-turn.

8. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations of operating an autonomous vehicle, the operations comprising:
defining a plurality of driving scenarios for a plurality of types of autonomous vehicles, each driving scenario corresponding to a specific movement of a particular type of autonomous vehicles;
for each of the driving scenarios of each type of autonomous vehicles, obtaining driving statistics of each autonomous vehicle, including
recording one or more driving parameters used to control and drive each autonomous vehicle of the type,
capturing a driving condition corresponding the driving scenario, and
calculating an average, sideslip caused by the driving parameters and the driving condition based on sideslips of a number of autonomous vehicles of the type under identical driving conditions; and

storing a driving scenario to a sideslip (scenario/sideslip) mapping table having a plurality of mapping entries to map the driving scenario to the calculated average sideslip, wherein the scenario/sideslip mapping table is utilized to compensate a sideslip under a similar driving scenario, the operations further including
determining a driving scenario based on a driving condition of an autonomous vehicle;
identifying an entry matching the driving scenario from the scenario/sideslip mapping table;
obtaining an average sideslip from the matching entry; and
adjusting a steering angle of the autonomous vehicle using the obtained average sideslip.

9. The machine-readable medium of claim 8 , wherein the operations further comprise:
in response to determining a next movement of the autonomous vehicle, determining a first driving scenario corresponding to the next movement;
searching in the scenario/sideslip mapping table based on the first driving scenario to locate a mapping entry corresponding to a second driving scenario matching the first driving scenario; and
determining the next movement for the autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry.

10. The machine-readable medium of claim 9 , wherein determining the next movement for the autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry comprises:
calculating a first steering angle based on a speed required by a route associated with the next movement using a predetermined algorithm;
modifying the first steering angle in view of the first sideslip obtained from the located mapping entry, generating a second steering angle; and
controlling the autonomous vehicle based on the second steering angle.

11. The machine-readable medium of claim 8 , wherein the driving condition comprises at least one of a type of road or a weather condition.

12. The machine-readable medium of claim 8 , wherein a driving parameter identifies an action an autonomous vehicle is taking, a speed during the action, or a steering angle during the action.

13. The machine-readable medium of claim 12 , wherein the driving parameter further identifies a type of an autonomous vehicle involved.

14. The machine-readable medium of claim 12 , wherein the action is one of a left turn, a right turn, or a U-turn.

15. A data processing system, comprising:
a processor; and
a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations of operating an autonomous vehicle, the operations including
defining a plurality of driving scenarios for a plurality of types of autonomous vehicles, each driving scenario corresponding to a specific movement of a particular type of autonomous vehicles,
for each of the driving scenarios of each type of autonomous vehicles, obtaining driving statistics of each autonomous vehicle, including
recording one or more driving parameters used to control and drive each autonomous vehicle of the type,
capturing a driving condition corresponding the driving scenario, and
calculating an average sideslip caused by the driving parameters and the driving condition based on sideslips of a number of autonomous vehicles of the type under identical driving conditions, and

storing a driving scenario to a sideslip (scenario/sideslip) mapping table having a plurality of mapping entries to map the driving scenario to the calculated average sideslip, wherein the scenario/sideslip mapping table is utilized to compensate a sideslip under a similar driving sce

Assignees

• Baidu Usa Llc

Inventors

• Kong Qi
• Zhu Fan
• Yang Guang
• Wang Jingao

Classifications

• B60W2555/20

  Ambient conditions, e.g. wind or rain · CPC title

• B60W50/0097

  Predicting future conditions · CPC title

• B60W30/045

  Improving turning performance · CPC title

• B60W2552/05

  Type of road, e.g. motorways, local streets, paved or unpaved roads · CPC title

• B60W2520/10

  Longitudinal speed · CPC title