Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-7 are rejected under 35 U.S.C. 102(a) (1) as being anticipated by Saito (U.S. Pub. No: 2022/0415172 A1).
Regarding claim 1, Saito discloses an information processing apparatus including a controller comprising at least one processor configured to perform; determining whether a number of standing occupants in a vehicle exceeds a threshold or not (see abstract, congestion rate calculation unit calculates a congestion rate in the cabin based on the “number of recognized passengers”. When the congestion rate is more than a “predetermined congestion threshold”, an in-vehicle display and an in-vehicle speaker are capable of giving an alighting notification that notifies the presence of a passenger who is alighting at the next stop and seat information of the passenger, and does not make an alighting notification when the congestion rate is less than or equal to the congestion threshold in the process of the passenger vehicle heading to the next stop. Also page 3, paragraphs, [0045-0046] this alighting notification is made in the process of the passenger vehicle leaving the current stop and heading to the next stop. By giving an alighting notification before arriving at the next stop, for example, “standing passengers” are prompted to move so as to secure the exit route. In addition, since the alighting notification includes information on the seat where the alighting passenger is seated, other passengers in the vehicle can understand the starting point of the exit route that ends at the exit (i.e., the seat of the alighting passenger). Furthermore, in the operation management system of the present embodiment, during low-congestion times when the congestion rate in the vehicle is lower than a “predetermined congestion threshold”, no alighting notification is made. Since no alighting notification is made during low congestion times when the exit route is secured, unnecessary movement of “standing passengers” can be controlled));
identifying a number of occupants in the vehicle based on the moving image analysis of a cabin of the vehicle when the number of standing occupants is less than the threshold (see above, also pages 1 and 6, paragraphs, [0008] and [0100], the present specification discloses a passenger vehicle and an operation management system that includes an operation management apparatus. The passenger vehicle is capable of traveling along a defined route and stopping at stops along the defined route. The passenger vehicle includes an imaging device that captures an image of the interior of a cabin. The operation management apparatus includes an image recognition unit and a congestion rate calculation unit. The image recognition unit recognizes (identifying), passengers in the “in-cabin image captured” by the imaging device in the process of the passenger vehicle leaving the current stop and heading to the next stop. The congestion rate calculation unit calculates a congestion rate in the cabin based on the recognized passengers. The passenger vehicle further includes a notification unit. When the congestion rate exceeds a predetermined congestion threshold, the notification unit can make an alighting notification that notifies the passengers that there is a passenger who is going to alight at the next stop and the seat information of the passenger. On the other hand, when the congestion rate is less than or equal to the congestion threshold, the notification unit does not make an alighting notification in the process of the passenger vehicle heading to the next stop. The in-cabin image recognition unit 66 recognizes passengers 101A and 101B in the captured image, and assigns the value of the attribute “Passenger” to the recognized passengers. In order to enable such image recognition, for example, SSD algorithms are learned using supervisory data. This supervisory data include a pair of supervisory data sets with standing and seated human images as input data and the class “Passenger” and the position parameters of the bounding box surrounding the passenger as output data);
identifying the number of occupants in the vehicle based on a transition of the number of occupants entering and exiting the vehicle determined by the moving image analysis at an entrance/exit of the vehicle when the number of standing occupants exceeds the threshold, and outputting identified information about the number of occupants in the vehicle (see above, also page 3, paragraphs, [0045-0046] this alighting notification is made in the process of the passenger vehicle leaving the current stop and heading to the next stop. By giving an alighting notification before arriving at the next stop, for example, “standing passengers” are prompted to move so as to secure the exit route. In addition, since the alighting notification includes information on the seat where the alighting passenger is seated, other passengers in the vehicle can understand the starting point of the exit route that ends at the exit. Furthermore, in the operation management system of the present embodiment, during low-congestion times when the congestion rate in the vehicle is lower than a predetermined congestion threshold, no alighting notification is made. Since no alighting notification is made during low congestion times when the exit route is secured, unnecessary movement of standing passengers can be controlled.
Also page 4, paragraphs, [0057-0059] As shown in FIG. 5, the passenger vehicle is used as a passenger bus, and has a pair of doors on the left side that serve as “an entrance and an exit”. As shown in FIG. 6, the cabin has a plurality of passenger seats along its walls. The seats include, for example, the reserved seats 42A to 42F, which can be reserved in advance, and a non-reserved seat, which cannot be reserved. For the support of standing passengers, a plurality of hanging straps are provided on the ceiling. An in-vehicle display, which is a notification unit, is located above the doors. The in-vehicle display, like the exterior display, includes a liquid crystal display or an LED display. As will be described later, the in-vehicle display displays a text message as the mode of giving an alighting notification. This text message will be a message that prompts standing passengers to ensure an exit route, for example, “The passenger in seat XX will be getting off the next stop. Please cooperate to ensure smooth exiting”. This alighting notification message can also be output as voice guidance from an in-vehicle speaker 45, which is a notification unit installed on the ceiling of the cabin 40.
Finally, page 6, paragraphs, [0102] and [0113], the congestion rate calculation unit 69 “counts the number of passengers” recognized by the in-cabin image recognition unit 66. In addition, the congestion rate calculation unit 69 refers to the capacity of the passenger vehicle. The capacity Nc is stored, for example, in a storage unit of the passenger vehicle 10. The congestion rate calculation unit 69 calculates the congestion rate A [%] from the ratio of the number of passengers Np to the capacity Nc (A=Np/Nc). The congestion rate A thus calculated is sent to the alighting notification determination unit 64 of the operation management apparatus. When the congestion rate A is less than or equal to the congestion threshold, the process of the alighting notification determination in FIG. 9 is completed. That is, the alighting notification determination unit does not make an alighting determination. On the other hand, when the congestion rate A is more than the congestion threshold K1, the congestion rate calculation unit sends a notification to the alighting notification determination unit that the cabin is congested. In response to this, the alighting notification determination units refers to the operation schedule of the passenger vehicle 10-1 stored in the operation schedule storage unit, in particular the boarding/alighting request information, and executes the alighting determination).
Regarding claim 3, Saito discloses the information processing apparatus according to claim 2, where in determining whether the number of standing passengers exceeds the threshold or not is constituted by determining whether there exist any standing passengers or not (see claim 1, also page 6, paragraphs, [0094-0095], as will be described in detail later, in this determination process, when the alighting determination determines that the alighting request information in which the next stop is set as the scheduled alighting stop is set, and the congestion rate A is more than the predetermined congestion threshold K1, the alighting notification command unit 65 commands the notification unit to make an alighting notification via the operation guidance unit 33 of the passenger vehicle 10. The notification unit includes at least one of the in-vehicle speaker 45 and the in-vehicle display 47B. Upon receiving the notification command, the in-vehicle speaker 45 and the in-vehicle display 47B, which are the notification units, output an operation guidance message (voice message and text message). On the other hand, even if the next stop is set as the scheduled alighting stop, when the congestion rate A is in a low congestion state less than or equal to the predetermined congestion threshold K1, the alighting notification command unit 65 does not command the notification unit (in-vehicle speaker 45 and in-vehicle display 47B) to make an alighting notification. Since no alighting notification is made during low congestion times when the exit route is secured, unnecessary movement of standing passengers can be avoided).
Regarding claim 4, Saito discloses the information processing apparatus according to claim 2, where in a single entrance/exit is provided in the vehicle (see claim 1, also page 4, paragraphs, [0057] and [0059], as shown in FIG. 5, the passenger vehicle is used as a passenger bus, and has a pair of doors (one unit of double door), on the left side that serve as an entrance and an exit. An in-vehicle display 47B, which is a notification unit, is located above the doors 41, 41. The in-vehicle display 47B, like the exterior display 47A, includes a liquid crystal display or an LED display. As will be described later, the in-vehicle display 47B displays a text message as the mode of giving an alighting notification. This text message will be a message that prompts standing passengers to ensure an exit route, for example, “The passenger in seat XX will be getting off the next stop. Please cooperate to ensure smooth exiting”. This alighting notification message can also be output as voice guidance from an in-vehicle speaker 45, which is a notification unit installed on the ceiling of the cabin 40).
Regarding claim 5, Saito discloses the information processing apparatus according to claim 2, wherein the moving image captured by a single camera that simultaneously shoots the cabin and the entrance/exit of the vehicle is used, in the moving image analysis of the cabin and the moving image analysis of the entrance/exit (see claim 1, also page 6, paragraphs,
[0098] and [0100] calculation of Congestion Rate 1. Since the SSD algorithm is a known technology, it is described herein only briefly. In the SSD algorithm, position and class estimation in the captured image is performed. That is, the two types of estimation; i.e., where the object is located in the image and what is the attribute (class) of the object, are done in parallel; i.e., in a single shot using a neural network. The in-cabin image recognition unit 66 recognizes passengers 101A and 101B in the captured image and encloses them in bounding boxes 111A and 111B, and assigns the value of the attribute “Passenger” to the recognized passengers. In order to enable such image recognition, for example, SSD algorithms are learned using supervisory data. This supervisory data include a pair of supervisory data sets with standing and seated human images as input data and the class “Passenger” and the position parameters of the bounding box surrounding the passenger as output data).
Regarding claim 6, Saito discloses the information processing apparatus according to claim 2, wherein the vehicle is a self-driving vehicle with no crews onboard ( see page 5, paragraph, [0077] the autonomous driving control unit 32 performs driving control of the passenger vehicle 10 based on the operation route map data stored in the dynamic map storage unit 34, the self-position information (vehicle position information) transmitted from the self-position estimation unit 31, and the peripheral data transmitted from the scan data analysis unit 30. Once arriving at the stop ST1 to ST3, the passenger vehicle 10 waits at the stop ST1 to ST3 until the departure time set in the operation schedule).
Regarding claim 7, Saito discloses a method by the at least one processor of the information processing apparatus according to claim 2, for improving travel mobility as a service (MaaS) (see claim 1, also page 3, paragraph, [0052] at least one of the ROM 75 and the storage device 77, which are storage devices, stores a program, which is executed by the CPU 72 to configure a bus application 81 illustrated in FIG. 3 in the mobile terminal 70. The bus application 81 is software for “improving the convenience of the transportation service” according to the present embodiment, and includes an operation schedule display unit 82 and a boarding/alighting request input unit 84.
With regard to claim 2, the arguments analogous to those presented above for claims 1, 3, 4, 5, 6 and 7, are respectively applicable to claim 2.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Seyed Azarian whose telephone number is (571) 272-7443. The examiner can normally be reached on Monday through Thursday from 6:00 a.m. to 7:30 p.m.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Matthew Bella, can be reached at (571) 272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SEYED H AZARIAN/Primary Examiner, Art Unit 2667
September 12, 2026
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