SYSTEMS AND METHODS FOR CONTROLLING ACTUATORS BASED ON LOAD CHARACTERISTICS AND PASSENGER COMFORT

• US 20200130703A1
• Filed: 10/18/2019
• Published: 04/30/2020
• Est. Priority Date: 10/29/2018
• Status: Active Grant

• Current Assignee: Motional AD, LLC (Aptiv PLC)
• Original Assignee: Aptiv Technologies Limited (BorgWarner Incorporated)
• Inventors: Pendelton, Scott D., Di Cicco, Maurilio
• Granted Patent: US 11,648,951 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02233 Occluders specially adapted therefor tourniquets A61B17/132
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/6893 Cars
• CPC Class Codes: B60N 2/002 Seats provided with an occupancy detection means mounted therein or thereon detection means responsive to presence or absence of children B60N2/266
• CPC Class Codes: B60W 2040/0872 Driver physiology
• CPC Class Codes: B60W 2050/0083 Setting, resetting, calibration
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2720/10 Longitudinal speed
• CPC Class Codes: B60W 2720/106 Longitudinal acceleration
• CPC Class Codes: B60W 2720/125 : Lateral acceleration
• CPC Class Codes: B60W 2754/20 : Lateral distance
• CPC Class Codes: B60W 2754/30 : Longitudinal distance
• CPC Class Codes: B60W 30/182 : Selecting between different operative modes, e.g. comfort and performance modes
• CPC Class Codes: B60W 40/08 : related to drivers or passengers
• CPC Class Codes: B60W 40/09 : Driving style or behaviour
• CPC Class Codes: B60W 50/0098 : Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: B60W 50/085 : Changing the parameters of the control units, e.g. changing limit values, working points by control input
• CPC Class Codes: G05D 1/0088 : characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/227 : Handing over between remote control and on-board control; Handing over between remote control arrangements
• CPC Class Codes: G06Q 30/0236 : Incentive or reward received by requiring registration or ID from user
• CPC Class Codes: G06V 20/59 : inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
• CPC Class Codes: G06V 40/15 : Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
• CPC Class Codes: G06V 40/174 : Facial expression recognition
• CPC Class Codes: G06V 40/18 : Eye characteristics, e.g. of the iris

Abstract

Among other things, we describe techniques for operation of a vehicle based on measured load characteristics and/or passenger comfort. One or more sensors of the vehicle can measure passenger data and/or load data of the vehicle. The passenger data and/or load data of the vehicle can be used by the vehicle to determine how to navigate within the surrounding environment.

Claims

1. A method comprising:

determining, using one or more processors of a vehicle, a vehicle operation profile for the vehicle, the determining of the vehicle operation profile comprising aggregating a plurality of stored passenger profiles, the plurality of stored passenger profiles being demographically similar to a stored passenger profile of at least one passenger located within the vehicle;

measuring, using one or more passenger sensors of the vehicle, passenger data of the at least one passenger;

updating, using the one or more processors, the vehicle operation profile based on the passenger data; and

navigating, using a control module of the vehicle, the vehicle using the updated vehicle operation profile.

2. The method of claim 1, wherein the passenger data comprises biometric data of the at least one passenger.

3. The method of claim 1, wherein the vehicle operation profile is partially determined based on data received from the stored passenger profile of the at least one passenger.

4. The method of claim 1, wherein the stored passenger profile of the at least one passenger comprises biometric data of the at least one passenger recorded on previous vehicle rides.

5. The method of claim 1, wherein the stored passenger profile of the at least one passenger comprises demographic data of the at least one passenger recorded on previous vehicle rides or obtained from the at least one passenger.

6. The method of claim 1, wherein the stored passenger profile of the at least one passenger comprises personal preference data of the at least one passenger recorded on previous vehicle rides or obtained from the at least one passenger.

7. The method of claim 1, wherein the one or more passenger sensors comprise one or more biometric sensors and the passenger data comprises at least one of a skin conductance, a pulse, a heart-rate, or a body temperature.

8. The method of claim 1, wherein the one or more passenger sensors comprise one or more imaging sensors and the passenger data comprises at least one of facial expressions or a magnitude of pupil dilation.

9. The method of claim 1, wherein the one or more passenger sensors comprise one or more pressure sensors and the passenger data comprises a pressure exerted by the at least one passenger on seat arm rests.

10. The method of claim 1, wherein the passenger data is associated with at least one of a time of day, a geographical location, a pattern of traffic, or a weather pattern.

11. The method of claim 1, wherein the one or more passenger sensors comprise at least one of a heart rate monitor, a sphygmomanometer, a pupilometer, an infrared thermometer, or a galvanic skin response sensor.

12. The method of claim 1, wherein the vehicle operation profile comprises at least one of a maximum speed limit, a maximum longitudinal acceleration limit, a maximum amplitude of fluctuation of acceleration, a maximum lateral acceleration, a maximum change in steering angle, a maximum rate of turn, or a maximum limit on a magnitude of jerk of the vehicle.

13. The method of claim 1, wherein the vehicle operation profile comprises at least one of a lateral clearance of the vehicle from an object or a lateral clearance of the vehicle from a pedestrian located in an environment containing the vehicle.

14. The method of claim 1, wherein the vehicle operation profile is determined based on data received, using an input device of the vehicle, from the at least one passenger.

15. The method of claim 1, wherein the passenger data is measured at different operating speeds of the vehicle.

16. The method of claim 1, further comprising adjusting a trajectory of the vehicle based on at least one of the passenger data or data received from a stored passenger profile of the at least one passenger.

17. The method of claim 1, further comprising transmitting, using a display of the vehicle, data representing ride pricing incentives to the at least one passenger to incentivize the at least one passenger to allow biometric data collection within the vehicle.

18. An autonomous vehicle comprising:

one or more computer processors; and

one or more non-transitory storage media storing instructions which, when executed by the one or more computer processors, cause the one or more computer processors to;

determine a vehicle operation profile for the vehicle, the determining of the vehicle operation profile comprising aggregating a plurality of stored passenger profiles, the plurality of stored passenger profiles being demographically similar to a stored passenger profile of at least one passenger located within the vehicle;

measure, using one or more passenger sensors of the vehicle, passenger data of the at least one passenger;

update the vehicle operation profile based on the passenger data; and

navigate, using a control module of the vehicle, the vehicle using the updated vehicle operation profile.

19. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to:

determine a vehicle operation profile for the vehicle, the determining of the vehicle operation profile comprising aggregating a plurality of stored passenger profiles, the plurality of stored passenger profiles being demographically similar to a stored passenger profile of at least one passenger located within the vehicle;

measure, using one or more passenger sensors of the vehicle, passenger data of the at least one passenger;

update the vehicle operation profile based on the passenger data; and

navigate, using a control module of the vehicle, the vehicle using the updated vehicle operation profile.

20. The one or more non-transitory storage media of claim 19, wherein the passenger data comprises biometric data of the at least one passenger.