Information processing system, information processing method, and readable medium

• US 10,625,673 B2
• Filed: 12/13/2017
• Issued: 04/21/2020
• Est. Priority Date: 12/16/2016
• Status: Active Grant

• Current Assignee: Panasonic Automotive Systems Company of America (Panasonic Holdings Corporation)
• Original Assignee: Panasonic Intellectual Property Management Co., Ltd. (Panasonic Holdings Corporation)
• Inventors: Shibata, Tadashi, Mori, Toshiya, Tsuji, Masanaga, Nakano, Nobuyuki
• Primary Examiner(s): Kan, Yuri
• Application Number:
  US15/840,129
• Publication Number:
  US 20180194280A1
• Time in Patent Office: 860 Days
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• 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 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: B60K 28/02 responsive to conditions relating to the driver
• CPC Class Codes: B60K 35/00 Instruments specially adapted for vehicles; Arrangement of instruments in or on vehicles
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: B60R 16/0237 circuits concerning the atmospheric environment meteorology G01W
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2040/0872 Driver physiology
• CPC Class Codes: B60W 2050/0029 Mathematical model of the driver
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2540/045 Occupant permissions
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/223 Posture, e.g. hand, foot, or seat position, turned or inclined
• CPC Class Codes: B60W 2540/225 Direction of gaze
• CPC Class Codes: B60W 2556/10 : Historical data
• CPC Class Codes: B60W 40/08 : related to drivers or passengers
• CPC Class Codes: B60W 50/14 : Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G01C 21/3415 : Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3484 : Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3658 : Lane guidance
• CPC Class Codes: G01C 21/3676 : Overview of the route on the road map
• CPC Class Codes: G01C 21/3697 : Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence
• CPC Class Codes: G06V 20/597 : Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/20 : Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

An information processing system is provided with a modeling unit. The modeling unit models, based on a degree of similarity among individual travel histories of a plurality of drivers, individual travel histories of at least one or more drivers from among the individual travel histories of the plurality of drivers to construct a driver model indicating a relationship between conditions of the at least one or more drivers and travel environments of at least one or more vehicles.

Claims

1. An information processing system comprising at least one processor,

wherein the at least one processor models, based on a degree of similarity among individual travel histories of a plurality of drivers, individual travel histories of at least one or more drivers from among the individual travel histories of the plurality of drivers to construct a driver model indicating a relationship between driver conditions of the at least one or more drivers and travel environments of at least one or more vehicles.

2. The information processing system according to claim 1, further comprising an environment acquisition circuit that acquires a travel environment of a vehicle driven by a driver, whose driving behavior is to be estimated,

wherein the at least one processor further estimates a driver condition associated with the travel environment acquired by the environment acquisition circuit, from among the driver conditions of the at least one or more drivers, in the driver model as a condition of the driver.

3. The information processing system according to claim 2, further comprising a notification circuit that provides notification to the driver,

wherein the at least one processor further determines whether or not the estimated condition of the driver is dangerous, and when determining that the estimated condition of the driver is dangerous, the at least one processor executes a danger avoidance process for causing the notification circuit to provide information for avoiding danger to the driver.

4. The information processing system according to claim 3, wherein the at least one processor estimates a direction of a gaze of the driver as the condition of the driver, and when an estimated gaze is not directed to an advancing direction of the vehicle driven by the driver, the at least one processor determines that the estimated gaze is dangerous, and executes the danger avoidance process to cause the notification circuit to issue a warning to the driver.

5. The information processing system according to claim 3, wherein the at least one processor estimates an intensity level of drowsiness of the driver as the condition of the driver, and when an estimated intensity level of drowsiness is higher than a threshold, the at least one processor determines that the estimated intensity level of drowsiness is dangerous, and executes the danger avoidance process to cause the notification circuit to play predetermined music.

6. The information processing system according to claim 3, wherein

the notification circuit provides a display of a travel route of the vehicle driven by the driver, and

the at least one processor estimates a heart rate of the driver as the condition of the driver, and when an estimated heart rate is higher than a threshold, the at least one processor determines that the estimated heart rate is dangerous, and executes the danger avoidance process to cause the notification circuit to change the travel route of the vehicle to a travel route for avoiding danger.

7. The information processing system according to claim 3, wherein the at least one processor estimates a posture of the driver as the condition of the driver, and when the estimated posture is a predetermined posture, the at least one processor determines that the estimated posture is dangerous, and executes the danger avoidance process to cause the notification circuit to issue a warning to the driver.

8. The information processing system according to claim 1, wherein,

in constructing the driver model,

the at least one processor

constructs the driver model indicating a relationship among the driver conditions of the at least one or more drivers, the travel environments of the at least one or more vehicles, and behaviors of the at least one or more vehicles, and

estimates a behavior of a vehicle associated with the travel environment of the vehicle driven by a driver, whose driving behavior is to be estimated and the condition of the driver in the driver model as a behavior of the vehicle driven by the driver.

11. The information processing system according to claim 4, wherein the at least one processor estimates an intensity level of drowsiness of the driver as the condition of the driver, and when an estimated intensity level of drowsiness is higher than a threshold, the at least one processor determines that the estimated intensity level of drowsiness is dangerous, and executes the danger avoidance process to cause the notification circuit to play predetermined music.

9. An information processing method, comprising modeling, based on a degree of similarity among individual travel histories of a plurality of drivers, individual travel histories of at least one or more drivers from among the individual travel histories of the plurality of drivers to construct a driver model indicating a relationship between driver conditions of the at least one or more drivers and travel environments of at least one or more vehicles.

10. A non-transitory readable medium having instructions, the instructions including instructions that cause a processor to perform modeling, based on a degree of similarity among individual travel histories of a plurality of drivers, individual travel histories of at least one or more drivers from among the individual travel histories of the plurality of drivers to construct a driver model indicating a relationship between driver conditions of the at least one or more drivers and travel environments of at least one or more vehicles.