Member Info for johnchucka

[0053]

For example, when the other vehicle occupant gaze direction recognizing unit 132 recognizes the occupant through the window of the recognized other vehicle m, the other vehicle occupant gaze direction recognition unit 132 determines whether or not the steering wheel is present in front of the seat on which the occupant is seated. When the other vehicle occupant gaze direction recognition unit 132 determines that the steering wheel is present in front of the seat on which the recognized occupant is seated, the other vehicle occupant gaze direction recognition unit 132 recognizes the occupant as the driver of the other vehicle m.

[0054]
Next, the other vehicle occupant gaze direction recognition unit 132 recognizes the recognized driver's face or line-of-sight direction D (step S102).

[0055]
5 and 6 are diagrams schematically showing the face D or the direction D of the line of sight of the driver of the other vehicle m.
In the figure, ST represents a steering wheel, and DP represents a display device to be described later. When the driver of the other vehicle m monitors the surroundings of the vehicle through the side window as in the illustrated example, at least a part of the driver's face can be viewed from outside the vehicle.

[0056]
Next, the other vehicle encounter time determination unit 142 acquires gaze direction information as a recognition result from the other vehicle occupant gaze direction recognition unit 132, and based on the gaze direction information, the face or line of sight of the driver of the other vehicle m It is determined whether or not the direction D is a predetermined direction (step S104). The predetermined direction is, for example, a direction facing the host vehicle M when viewed from the other vehicle m.

[0060]
For example, the device control unit 170 controls the communication device 20 to transmit predetermined information to the other vehicle m that is a communication partner of inter-vehicle communication.
The predetermined information is, for example, information for notifying what action is to be taken as a result of the own vehicle M recognizing the face of the driver of another vehicle m or the direction D of the line of sight. For example, the other vehicle m that has received the predetermined information outputs the predetermined information via a display device DP or a speaker installed in the vehicle interior. In addition, the apparatus control part 170 may abbreviate | omit the process which transmits predetermined | prescribed information, when vehicle-to-vehicle communication is not established between the other vehicles m.

VEHICLE CONTROL DEVICE, VEHICLE CONTROL METHOD, AND PROGRAM
Provided is a vehicle control device comprising: an acquisition part for acquiring information indicating the orientation of the face or gaze of an occupant in another vehicle; an assessment part for assessing whether the orientation indicated by the information acquired by the acquisition part corresponds to an orientation that is directed toward a host vehicle (on which the vehicle control device is mounted) as viewed from the other vehicle; and a drive control part for controlling the steering and/or the acceleration of the host vehicle, said drive control part being designed to carry out prescribed control when it has been assessed by the assessment part that the orientation indicated by the information corresponds to the orientation directed toward the host vehicle as viewed from the other vehicle.
https://worldwide.espacenet.com/publicationDetails/description?CC=WO&NR=2019130483A1&KC=A1&FT=D&ND=3&date=20190704&DB=&locale=en_EP#

[0031]
FIG. 2 is a functional configuration diagram of the first control unit 120 and the second control unit 160. The first control unit 120 includes, for example, a recognition unit 130 and an action plan generation unit 140. The recognition unit 130 includes, for example, another vehicle occupant gaze direction recognition unit 132. Moreover, the action plan production | generation part 140 is provided with the determination part 142 at the time of another vehicle encounter, for example. The combination of the camera 10, the object recognition device 16, and the recognition unit 130 is an example of a “detection unit”.

[0037]
In addition, the other vehicle occupant gaze direction recognition unit 132 of the recognition unit 130 identifies the other vehicle m from the recognized objects, and recognizes an occupant riding on the other vehicle m. Then, the other vehicle occupant gaze direction recognition unit 132 recognizes the recognized direction of the occupant's face or the direction of the line of sight of the other vehicle m. For example, the other vehicle occupant gaze direction recognizing unit 132 recognizes the direction of the occupant's face or the direction of the line of sight based on the position of the occupant's pupils, irises, eyes, and the like, as well as the skin and hair regions.

[0052]
First, the other vehicle occupant gaze direction recognition unit 132 recognizes the recognized driver of the other vehicle m (step S100). The driver is, for example, an occupant seated in a seat closest to the steering wheel among one or more occupants who have boarded the vehicle.

TLS,
The SEE Patent SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE
describes a multi camera system where cameras can be positioned around the Vehicle to pick up the whole street scene and show it's relationship with Driver gaze. This looks to me to have wider applications beyond Guardian. This inward/ outward facing camera fusion and data collection type innovation looks to me to be also described in the various 2019 Toyota/GM/ Continental patents I have posted recently and is also described in recent Honda Patents also.

[0031] The embodiments of the present disclosure described herein relate to determining a camera pose of a forward facing camera in a multi-camera vehicle monitoring system. In these embodiments, the scene to be imaged includes a driver of a vehicle, the interior of the vehicle/****pit, the forward road scene of the vehicle and optionally side and rear views from the vehicle. The vehicle may represent a commercial automobile, truck, earthmoving machine, airplane, jet or helicopter. However, it will be appreciated that the disclosure is applicable to other multi-camera monitoring systems.

[0032] Use of the term camera pose herein represents a three dimensional position and three dimensional orientation of a camera within a scene.

[0033] Referring initially to FIGS. 1 and 2, there is illustrated a vehicle monitoring system 100 including four cameras 101-104 disposed at different locations within a vehicle 106. Camera 101 is positioned on a dashboard of the vehicle and oriented in a forward direction of the vehicle for monitoring the forward road scene. Cameras 102, 103 and 104 are positioned and oriented to monitor a driver 108 of vehicle 106. Camera 102 is positioned on or adjacent an instrument panel of vehicle 106 or on the steering column of vehicle 106. Camera 103 is positioned on the driver side A-pillar of the frame of vehicle 106. Camera 104 is positioned on or adjacent a center console of vehicle 106, preferably adjacent a display screen in vehicles where such a screen is provided. The specific camera locations are exemplary only and it will be appreciated that more or less cameras can be incorporated at other locations within or outside vehicle 106 to monitor the driver, the forward road scene or other views in or around the vehicle. Other exemplary camera locations of cameras include a rearview mirror, rear bumper, front bumper, vehicle roof and bonnet/hood.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2019266751A1&KC=A1&FT=D&ND=3&date=20190829&DB=&locale=en_EP#

That's how I see it going TLS. Inward /outward data collection with aligned sensors.
I also imagine it being valuable in the BdMS applications also? do you think that likely?

Thanks S2020,
I guess that also has possible read across to what Harish refereed to 'As a UI software developer, I contribute to the graphical display interface and button handling aspects of the Driver display. Currently, working on next generation display interfaces for major Asian automotive OEMs'.

What do we expect from Honda given the Honda, GM partner on cruise autonomous vehicle venture headline of Oct 2018.
https://uk.motor1.com/news/268508/honda-gm-cruise-autonomous-venture/ The Honda Patent PREDICTIVE HUMAN-MACHINE INTERFACE USING EYE GAZE TECHNOLOGY, BLIND SPOT INDICATORS AND DRIVER EXPERIENCE @ 033 mentions “Smart Eye Pro 5.0” but recent patents do not make explicit reference. I also note Safestocks Oct 18 commentary 'I’m personally confident that Seeing Machines will soon announce some huge auto wins: Toyota, FCA and Volvo. Other OEMs that I believe will fall to Seeing Machines include: Mazda, Honda, Subaru and Audi'. https://www.safestocks.co.uk/2018/10/02/panmure-puts-28p-price-target-on-seeing-machines-auto-division/

Do we have any further info on how this partnership is progressing and any more details on the Safestocks hunches?

Is this what Semicast is referring to? and is this the Global Bus 100 shared safety architecture mentioned in the Toyota /Conti Patent?

GM shows off 'digital vehicle platform' enabling more in-car tech and OTA updates
Next-gen electrical architecture five times more capable than GM's current electrical system.
It appears to have dropped the sobriquet "Global B," but General Motors' new electrical architecture has bowed in drawings and video. This is the "digital vehicle platform" GM president Mark Reuss spoke to Reuters about in 2015, saying it would move a great deal of a vehicle's computer work to the cloud and enable over-the-air updates. Reuss took the microphone for the debut, too, saying, "Our new digital vehicle platform and its eventual successors will underpin all our future innovations across a wide range of technological advancements, including EVs and expanded automated driving."
https://tinyurl.com/vr7byjm

Missy Cummings@missy_cummings
Replying to
@tedstein
@greentheonly
and 5 others
Super Cruise can't guarantee you are paying attention, nor can any driver monitoring system in existence today. It only detects if you are sitting up & face forward, it is very possible that even when face forward, you are not paying attention. This occurs daily in my classes

Semicast Research@semicast_res
You’re gonna be surprised in 2020 Missy! So too a lot of people.

L7,
FCA not confirmed as you say but most are not by name so that's not new. With my JC logic and SEE's history of pulling key staff over form the companies with whom theyare working closely , I look at Nathaniel Todd's appointment together with Safestocks call as supporting evidence that SEE is more likely than not working with FCA.
https://www.linkedin.com/in/nathaniel-todd-b08a8458/?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAxC4TgB47h-k9HEF0kZj7mPUI_dzZFses8

Lombard Logic

Looks like a sophisticated Coffee Cup type sensor.

I assume it's tankers on public roads.
https://www.permianroadsafety.org/wp-content/uploads/2019/04/Retzer_Oil_and_Gas_Driver_Fatigue_0917.pdf

Paul talked in the Pro=ac video about the Caterpillar fields of use and particularly Oil and Gas and Forestry being reversed to SEE. He said the Oil and Gas sector was 'highly prospective'.
Does anyone have any thoughts on how the oil and gas companies previously monitored by Cat would be treated under such arrangements? would Cat retain them or would they now be all transferred to SEE ?

Semicast Research@semicast_res
Prediction: NHTSA has a mandate on the books within next 12 months looking a lot like “Europe on the Move” : AEB, LKAS, IR vision DMS. Put that into all new on-highway vehicles with 4 or more wheels. Then let market decide if robotaxi/MaaS is the future.

METHODS AND SYSTEMS FOR PROCESSING DRIVER ATTENTION DATA GM
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2019318180A1&KC=A1&FT=D&ND=3&date=20191017&DB=&locale=en_EP#

HYUNDAI MOTOR CO LTD [KR]; KIA MOTORS CORP
VEHICLE AND CONTROL METHOD THEREOF
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2019256084A1&KC=A1&FT=D&ND=3&date=20190822&DB=&locale=en_EP#

HYUNDAI MOTOR CO LTD [KR]; KIA MOTORS CORP [KR] (Cont)
[0007] The present disclosure provides a vehicle capable of informing a driver of the risk of collision at an optimal time by controlling a collision warning time in consideration of the driver's gaze, field of view and visibility of the forward object, and a method of controlling the vehicle. Accordingly, the satisfaction of the driver, the reliability of the system, and the accident prevention effect can be enhanced.

[0008] Additional aspects of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.

[0009] In accordance with an aspect of the present disclosure, a vehicle includes a distance sensor configured to collect data of an object; a camera configured to collect image data; a driver recognition sensor configured to collect driver's facial data; and a controller configured to analyze driver's gaze and field of view using the driver's facial data, analyze visibility of the object using the image data, and calculate a collision warning time based on a result of analyzing the driver's gaze and field of view and the visibility of the object; and an alarm device configured to inform the driver of the risk of collision at the collision warning time under the control of the controller.

[0010] The controller may be configured to calculate a driver's attention distribution function by analyzing the driver's gaze and the field of view, calculate a visibility index by analyzing the visibility of the object, and calculate a recognition index using the driver's attention distribution function and the visibility index.

1
METHODS AND SYSTEMS FOR PROCESSING DRIVER ATTENTION DATA GM 2019-10-17
[0005] Methods and systems are provided for processing attention data. In one embodiment, a method includes: receiving, by a processor, object data associated with at least one object of an exterior environment of the vehicle; receiving upcoming behavior data determined from a planned route of the vehicle; receiving gaze data sensed from an occupant of the vehicle; processing, by the processor, the object data, the upcoming behavior data, and the gaze data to determine an attention score associated with an attention of an occupant of the vehicle; and selectively generating, by the processor, signals to at least one of notify the occupant and control the vehicle based on the attention score.

[0006] In various embodiments, the processing includes computing an object location from the object data, computing a gaze location from the gaze data, computing an upcoming behavior location from the upcoming behavior data, and computing the attention score based on the gaze location, the object location, and the upcoming behavior location.

[0007] In various embodiments, computing the attention score includes computing a matching level between the object location and the gaze location. In various embodiments, computing the attention score further includes applying a weighting factor to the matching level. In various embodiments, computing the matching level is based on a duration of matching. In various embodiments, computing the matching level is based on a breadth of matching. In various embodiments, the weighting factor is dynamically determined based on environmental conditions.

[0008] In various embodiments, the weighting factor is dynamically determined based on a driving scenario. In various embodiments, computing the attention score includes computing a matching level between the upcoming behavior location and the gaze location. In various embodiments, computing the attention score further includes applying a weighting factor to the matching level.

HYUNDAI MOTOR CO LTD [KR]; KIA MOTORS CORP [KR] 2019-08-22
A vehicle, which adjusts a collision warning time based on driver's field of view and visibility of the object, is provided. The vehicle includes: a distance sensor that collects data of an object, a camera that collects image data, a driver recognition sensor that collects driver's facial data, and a controller that analyzes driver's gaze and field of view using the driver's facial data, analyzes visibility of the object using the image data, and calculates a collision warning time based on a result of analyzing the driver's gaze and field of view and the visibility of the object, and an alarm device that informs the driver of the risk of collision at the collision warning time under the control of the controller.

:)

Baxter, I prefer to forage rather than 'trawl'. Foraging involves more specialist knowledge of the local species and habitats so you don't waste time looking in all the wrong places.

Apologies S7 if Harish has inconveniently interrupted your Toyota Doitashima****e narrative.