Vehicle system and vehicle controller for controlling vehicle

• US 10,139,831 B2
• Filed: 03/17/2017
• Issued: 11/27/2018
• Est. Priority Date: 03/17/2017
• Status: Active Grant

• Current Assignee: DENSO Corporation, Denso International America Incorporated (DENSO Corporation)
• Original Assignee: DENSO Corporation, Denso International America Incorporated (DENSO Corporation)
• Inventors: Yan, Yu
• Primary Examiner(s): Zanelli, Michael J
• Application Number:
  US15/461,812
• Publication Number:
  US 20180267557A1
• Time in Patent Office: 620 Days
• CPC Class Codes: A61B 3/112 for measuring diameter of pupils
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• 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 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/4266 sweat secretion
• CPC Class Codes: A61B 5/6802 Sensor mounted on worn items
• CPC Class Codes: B60W 2050/0088 Adaptive recalibration
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 50/0098 Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: B62D 15/0255 Automatic changing of lane, e.g. for passing another vehicle

Abstract

A processor is coupled to a vehicle, the processor being configured to store a lane change parameter. A feature sensor detects a feature of a passenger in the vehicle. The processor is programmed to control the vehicle to execute an assisted lane change based on the lane change parameter, the lane change parameter defining a characteristic of the assisted lane change, communicate with the feature sensor to detect the feature of the passenger during the assisted lane change, determine whether the passenger was comfortable during the assisted lane change based on the detected feature of the passenger, and modify the lane change parameter upon determining that the passenger was uncomfortable.

Claims

1. A vehicle system, comprising:

a processor coupled to a vehicle, the processor configured to store a lane change parameter; and

a feature sensor that detects a feature of a passenger in the vehicle, wherein

the processor is programmed to

control the vehicle to execute an assisted lane change based on the lane change parameter, the lane change parameter defining a characteristic of the assisted lane change,

communicate with the feature sensor to detect the feature of the passenger during the assisted lane change,

determine whether the passenger was comfortable during the assisted lane change based on the detected feature of the passenger, and

modify the lane change parameter upon determining that the passenger was uncomfortable, wherein

the processor uses a machine learning model to determine whether the passenger was comfortable during the assisted lane change,

the vehicle system further comprises a human-machine interface mounted in the vehicle, and

the processor is programmed to

receive a comfort rating for the assisted lane change from the passenger through the human-machine interface, and

train the machine learning model based on the detected feature and the received comfort rating.

2. The vehicle system of claim 1, further comprising:

a mobile device that stores a mobile parameter corresponding to the passenger, wherein

the processor is programmed to

download the mobile parameter from the mobile device upon detecting that the mobile device is in the vehicle, and

store the downloaded mobile parameter as the lane change parameter.

3. The vehicle system of claim 2, wherein

the processor is programmed to, when modifying the lane change parameter, modify the mobile parameter stored in the mobile device in a corresponding manner.

4. The vehicle system of claim 2, wherein

the mobile device includes the feature sensor.

5. The vehicle system of claim 1, wherein

the machine learning model is one of a neural network and a decision tree model.

6. The vehicle system of claim 1, wherein

the feature sensor includes one or more of:

a camera mounted in the vehicle, the camera detecting at least one of an expression of the passenger and a pupil diameter of the passenger as the feature of the passenger,

a wearable sensor worn the passenger, the wearable sensor detecting at least one of a pulse, a body temperature, and a perspiration rate of the passenger as the feature of the passenger, and

a pressure sensor mounted on a steering wheel of the vehicle, the pressure sensor detecting a pressure applied by the passenger as the feature of the passenger.

7. The vehicle system of claim 1, wherein

the lane change parameter includes at least one of a maximum speed, a maximum acceleration, a maximum yaw angle, and a minimum inter-vehicle distance.

8. The vehicle system of claim 7, wherein

the processor is programmed to, when modifying the lane change parameter, perform at least one of:

decreasing the maximum speed,

decreasing the maximum acceleration,

decreasing the maximum yaw angle, and

increasing the minimum inter-vehicle distance.

9. A vehicle controller, comprising:

a central processing unit (CPU) coupled to a vehicle and in communication with a feature sensor that detects a feature of a passenger in the vehicle; and

a memory coupled to the CPU, the memory configured to store a lane change parameter, wherein

the CPU is programmed to

communicate with the feature sensor to detect the feature of the passenger during an assisted lane change, the lane change parameter defining a characteristic of the assisted lane change,

determine whether the passenger was comfortable during the assisted lane change based on the detected feature of the passenger, and

modify the lane change parameter upon determining that the passenger was uncomfortable, wherein

the CPU uses a machine learning model stored in the memory to determine whether the passenger was comfortable during the assisted lane change,

a human-machine interface is mounted in the vehicle, and

the CPU is programmed to

receive a comfort rating for the assisted lane change from the passenger through the human-machine interface, and

train the machine learning model based on the detected feature and the received comfort rating.

10. The vehicle controller of claim 9, wherein

the CPU is in communication with a mobile device that stores a mobile parameter corresponding to the passenger, and

the CPU is programmed to

download the mobile parameter from the mobile device upon detecting that the mobile device is in the vehicle, and

store the downloaded mobile parameter in the memory as the lane change parameter.

11. The vehicle controller of claim 10, wherein

the CPU is programmed to, when modifying the lane change parameter, modify the mobile parameter stored in the mobile device in a corresponding manner.

12. The vehicle controller of claim 10, wherein

the mobile device includes the feature sensor.

13. The vehicle controller of claim 9, wherein

the machine learning model is one of a neural network and a decision tree model.

14. The vehicle controller of claim 9, wherein

the CPU is in communication with, as the feature sensor, one or more of:

a camera mounted in the vehicle, the camera detecting at least one of an expression of the passenger and a pupil diameter of the passenger as the feature of the passenger,

a wearable sensor worn the passenger, the wearable sensor detecting at least one of a pulse, a body temperature, and a perspiration rate of the passenger as the feature of the passenger, and

a pressure sensor mounted on a steering wheel of the vehicle, the pressure sensor detecting a pressure as the feature of the passenger.

15. The vehicle controller of claim 9, wherein

the lane change parameter includes at least one of a maximum speed, a maximum acceleration, a maximum yaw angle, and a minimum inter-vehicle distance.

16. The vehicle controller of claim 15, wherein

the CPU is programmed to, when modifying the lane change parameter, perform at least one of:

decreasing the maximum speed,

decreasing the maximum acceleration,

decreasing the maximum yaw angle, and

increasing the minimum inter-vehicle distance.