A thorough background of the invention is set forth in U.S. patent application Ser. No. 10/931,288, incorporated by reference herein.
Briefly, automotive vehicles are equipped with seat belts and air bags as equipment for ensuring the safety of the passenger. In recent years, an effort has been underway to enhance the performance of the seat belt and/or the air bag by controlling these devices in accordance with the morphology, e.g., weight, of the occupant. For example, the quantity of gas used to deploy the air bag or the speed of deployment could be controlled. Further, the amount of pretension of the seat belt could be adjusted in accordance with the weight and posture of the passenger. To this end, it is necessary to know the weight of the passenger sitting on the seat by some technique. The position of the center of gravity of the passenger sitting on the seat could also be referenced in order to estimate the posture of the passenger.
As an example of a technique to determine the weight or the center of gravity of the passenger of this type, a method of measuring the seat weight including the passenger's weight by disposing the load sensors (load cells) at the front, rear, left and right corners under the seat and summing vertical loads applied to the load cells has been disclosed in the assignee's numerous patents and patent applications on occupant sensing.
Since a seat weight measuring apparatus of this type is intended for use in general automotive vehicles, the cost of the apparatus must be as low as possible. In addition, the wiring and assembly also must be easy. Keeping such considerations in mind, the object of the present invention is to provide a seat weight measuring apparatus having such advantages that the production cost and the assembling cost may be reduced. To provide new and improved vehicular seats in which the weight applied by an occupying item to the seat is measured based on capacitance between conductive and/or metallic members underlying the seat cushion.
A further object of an invention herein is to provide new and improved adjustment apparatus and methods that evaluate the occupancy of the seat and adjust the location and/or orientation relative to the occupant and/or operation of a part of the component or the component in its entirety based on the evaluated occupancy of the seat and on a measurement of the occupant's weight or a measurement of a force exerted by the occupant on the seat.
Definitions
Preferred embodiments of the invention are described below and unless specifically noted, it is the applicants' intention that the words and phrases in the specification and claims be given the ordinary and accustomed meaning to those of ordinary skill in the applicable art(s). If the applicants intend any other meaning, they will specifically state they are applying a special meaning to a word or phrase.
Likewise, applicants' use of the word “function” here is not intended to indicate that the applicants seek to invoke the special provisions of 35 U.S.C. §112, sixth paragraph, to define their invention. To the contrary, if applicants wish to invoke the provisions of 35 U.S.C. §112, sixth paragraph, to define their invention, they will specifically set forth in the claims the phrases “means for” or “step for” and a function, without also reciting in that phrase any structure, material or act in support of the function. Moreover, even if applicants invoke the provisions of 35 U.S.C. §112, sixth paragraph, to define their invention, it is the applicants' intention that their inventions not be limited to the specific structure, material or acts that are described in the preferred embodiments herein. Rather, if applicants claim their inventions by specifically invoking the provisions of 35 U.S.C. § 112, sixth paragraph, it is nonetheless their intention to cover and include any and all structure, materials or acts that perform the claimed function, along with any and all known or later developed equivalent structures, materials or acts for performing the claimed function.
“Pattern recognition” as used herein will generally mean any system which processes a signal that is generated by an object (e.g., representative of a pattern of returned or received impulses, waves or other physical property specific to and/or characteristic of and/or representative of that object) or is modified by interacting with an object, in order to determine to which one of a set of classes that the object belongs. Such a system might determine only that the object is or is not a member of one specified class, or it might attempt to assign the object to one of a larger set of specified classes, or find that it is not a member of any of the classes in the set. The signals processed are generally a series of electrical signals coming from transducers that are sensitive to acoustic (ultrasonic) or electromagnetic radiation (e.g., visible light, infrared radiation, capacitance or electric and/or magnetic fields), although other sources of information are frequently included. Pattern recognition systems generally involve the creation of a set of rules that permit the pattern to be recognized. These rules can be created by fuzzy logic systems, statistical correlations, or through sensor fusion methodologies as well as by trained pattern recognition systems such as neural networks, combination neural networks, cellular neural networks or support vector machines.
A trainable or a trained pattern recognition system as used herein generally means a pattern recognition system that is taught to recognize various patterns constituted within the signals by subjecting the system to a variety of examples. The most successful such system is the neural network used either singly or as a combination of neural networks. Thus, to generate the pattern recognition algorithm, test data is first obtained which constitutes a plurality of sets of returned waves, or wave patterns, or other information radiated or obtained from an object (or from the space in which the object will be situated in the passenger compartment, i.e., the space above the seat) and an indication of the identify of that object. A number of different objects are tested to obtain the unique patterns from each object. As such, the algorithm is generated, and stored in a computer processor, and which can later be applied to provide the identity of an object based on the wave pattern being received during use by a receiver connected to the processor and other information. For the purposes here, the identity of an object sometimes applies to not only the object itself but also to its location and/or orientation in the passenger compartment. For example, a rear facing child seat is a different object than a forward facing child seat and an out-of-position adult can be a different object than a normally seated adult. Not all pattern recognition systems are trained systems and not all trained systems are neural networks. Other pattern recognition systems are based on fuzzy logic, sensor fusion, Kalman filters, correlation as well as linear and non-linear regression. Still other pattern recognition systems are hybrids of more than one system such as neural-fuzzy systems.
The use of pattern recognition, or more particularly how it is used, is important to many embodiments of the instant invention. In the above-cited prior art, except that assigned to the current assignee, pattern recognition which is based on training, as exemplified through the use of neural networks, is not mentioned for use in monitoring the interior passenger compartment or exterior environments of the vehicle in all of the aspects of the invention disclosed herein. Thus, the methods used to adapt such systems to a vehicle are also not mentioned.
A pattern recognition algorithm will thus generally mean an algorithm applying or obtained using any type of pattern recognition system, e.g., a neural network, sensor fusion, fuzzy logic, etc.
To “identify” as used herein will generally mean to determine that the object belongs to a particular set or class. The class may be one containing, for example, all rear facing child seats, one containing all human occupants, or all human occupants not sitting in a rear facing child seat, or all humans in a certain height or weight range depending on the purpose of the system. In the case where a particular person is to be recognized, the set or class will contain only a single element, i.e., the person to be recognized.
To “ascertain the identity of” as used herein with reference to an object will generally mean to determine the type or nature of the object (obtain information as to what the object is), i.e., that the object is an adult, an occupied rear facing child seat, an occupied front facing child seat, an unoccupied rear facing child seat, an unoccupied front facing child seat, a child, a dog, a bag of groceries, a car, a truck, a tree, a pedestrian, a deer etc.
An “object” in a vehicle or an “occupying item” of a seat may be a living occupant such as a human or a dog, another living organism such as a plant, or an inanimate object such as a box or bag of groceries or an empty child seat.
A “rear seat” of a vehicle as used herein will generally mean any seat behind the front seat on which a driver sits. Thus, in minivans or other large vehicles where there are more than two rows of seats, each row of seats behind the driver is considered a rear seat and thus there may be more than one “rear seat” in such vehicles. The space behind the front seat includes any number of such rear seats as well as any trunk spaces or other rear areas such as are present in station wagons.
An “optical image” will generally mean any type of image obtained using electromagnetic radiation including X-ray, ultraviolet, visual, infrared, terahertz and radar radiation.
In the description herein on anticipatory sensing, the term “approaching” when used in connection with the mention of an object or vehicle approaching another will usually mean the relative motion of the object toward the vehicle having the anticipatory sensor system. Thus, in a side impact with a tree, the tree will be considered as approaching the side of the vehicle and impacting the vehicle. In other words, the coordinate system used in general will be a coordinate system residing in the target vehicle. The “target” vehicle is the vehicle that is being impacted. This convention permits a general description to cover all of the cases such as where (i) a moving vehicle impacts into the side of a stationary vehicle, (ii) where both vehicles are moving when they impact, or (iii) where a vehicle is moving sideways into a stationary vehicle, tree or wall.
“Vehicle” as used herein includes any container that is movable either under its own power or using power from another vehicle. It includes, but is not limited to, automobiles, trucks, railroad cars, ships, airplanes, trailers, shipping containers, barges, etc. The term “container” will frequently be used interchangeably with vehicle however a container will generally mean that part of a vehicle that separate from and in some cases may exist separately and away from the source of motive power. Thus, a shipping container may exist in a shipping yard and a trailer may be parked in a parking lot without the tractor. The passenger compartment or a trunk of an automobile, on the other hand, are compartments of a container that generally only exists attaches to the vehicle chassis that also has an associated engine for moving the vehicle. Note, a container can have one or a plurality of compartments.
“Out-of-position” as used for an occupant will generally mean that the occupant, either the driver or a passenger, is sufficiently close to an occupant protection apparatus (airbag) prior to deployment that he or she is likely to be more seriously injured by the deployment event itself than by the accident. It may also mean that the occupant is not positioned appropriately in order to attain the beneficial, restraining effects of the deployment of the airbag. As for the occupant being too close to the airbag, this typically occurs when the occupant's head or chest is closer than some distance, such as about 5 inches, from the deployment door of the airbag module. The actual distance where airbag deployment should be suppressed depends on the design of the airbag module and is typically farther for the passenger airbag than for the driver airbag.
“Dynamic out-of-position” refers to the situation where a vehicle occupant, either driver or passenger, is in position at a point in time prior to an accident but becomes out-of-position, (that is, too close to the airbag module so that he or she could be injured or killed by the deployment of the airbag) prior to the deployment of the airbag due to pre-crash braking or other action which causes the vehicle to decelerate prior to a crash.
“Transducer” or “transceiver” as used herein will generally mean the combination of a transmitter and a receiver. In come cases, the same device will serve both as the transmitter and receiver while in others two separate devices adjacent to each other will be used. In some cases, a transmitter is not used and in such cases transducer will mean only a receiver. Transducers include, for example, capacitive, inductive, ultrasonic, electromagnetic (antenna, CCD, CMOS arrays), electric field, weight measuring or sensing devices. In some cases, a transducer will be a single pixel either acting alone, in a linear or an array of some other appropriate shape. In some cases, a transducer may comprise two parts such as the plates of a capacitor or the antennas of an electric field sensor. Sometimes, one antenna or plate will communicate with several other antennas or plates and thus for the purposes herein, a transducer will be broadly defined to refer, in most cases, to any one of the plates of a capacitor or antennas of a field sensor and in some other cases, a pair of such plates or antennas will comprise a transducer as determined by the context in which the term is used.
“Adaptation” as used here will generally represent the method by which a particular occupant or object sensing system is designed and arranged for a particular vehicle model. It includes such things as the process by which the number, kind and location of various transducers are determined. For pattern recognition systems, it includes the process by which the pattern recognition system is designed and then taught or made to recognize the desired patterns. In this connection, it will usually include (1) the method of training when training is used, (2) the makeup of the databases used, testing and validating the particular system, or, in the case of a neural network, the particular network architecture chosen, (3) the process by which environmental influences are incorporated into the system, and (4) any process for determining the pre-processing of the data or the post processing of the results of the pattern recognition system. The above list is illustrative and not exhaustive. Basically, adaptation includes all of the steps that are undertaken to adapt transducers and other sources of information to a particular vehicle to create the system that accurately identifies and/or determines the location of an occupant or other object in a vehicle.
For the purposes herein, a “neural network” is defined to include all such learning systems including cellular neural networks, support vector machines and other kernel-based learning systems and methods, cellular automata and all other pattern recognition methods and systems that learn. A “combination neural network” as used herein will generally apply to any combination of two or more neural networks as most broadly defined that are either connected together or that analyze all or a portion of the input data. “Neural network” can also be defined as a system wherein the data to be processed is separated into discrete values which are then operated on and combined in at least a two-stage process and where the operation performed on the data at each stage is in general different for each of the discrete values and where the operation performed is at least determined through a training process. The operation performed is typically a multiplication by a particular coefficient or weight and by different operation, therefore is meant in this example, that a different weight is used for each discrete value.
A “morphological characteristic” will generally mean any measurable property of a human such as height, weight, leg or arm length, head diameter, skin color or pattern, blood vessel pattern, voice pattern, finger prints, iris patterns, etc.
A “wave sensor” or “wave transducer” is generally any device which senses either ultrasonic or electromagnetic waves. An electromagnetic wave sensor, for example, includes devices that sense any portion of the electromagnetic spectrum from ultraviolet down to a few hertz. The most commonly used kinds of electromagnetic wave sensors include CCD and CMOS arrays for sensing visible and/or infrared waves, millimeter wave and microwave radar, and capacitive or electric and/or magnetic field monitoring sensors that rely on the dielectric constant of the object occupying a space but also rely on the time variation of the field, expressed by waves as defined below, to determine a change in state.
The “windshield header” as used herein generally includes the space above the front windshield including the first few inches of the roof.
A “sensor” as used herein can be a single receiver or the combination of two transducers (a transmitter and a receiver) or one transducer which can both transmit and receive.
The “headliner” is the trim which provides the interior surface to the roof of the vehicle and the A-pillar is the roof-supporting member which is on either side of the windshield and on which the front doors are hinged.
An “occupant protection apparatus” is any device, apparatus, system or component which is actuatable or deployable or includes a component which is actuatable or deployable for the purpose of attempting to reduce injury to the occupant in the event of a crash, rollover or other potential injurious event involving a vehicle
As used herein, an “occupant restraint device” generally includes any type of device which is deployable in the event of a crash involving the vehicle for the purpose of protecting an occupant from the effects of the crash and/or minimizing the potential injury to the occupant. Occupant restraint devices thus include frontal airbags, side airbags, seatbelt tensioners, knee bolsters, side curtain airbags, externally deployable airbags and the like.
As used herein, a “part” of the vehicle generally includes any component, sensor, system or subsystem of the vehicle such as the steering system, braking system, throttle system, navigation system, airbag system, seatbelt retractor, air bag inflation valve, air bag inflation controller and airbag vent valve, as well as those listed below in the definitions of “component” and “sensor”.
As used herein, a “sensor system” generally includes any of the sensors listed below in the definition of “sensor” as well as any type of component or assembly of components which detect, sense or measure something.
The term “gage” or “gauge” is used herein interchangeably with the terms “sensor” and “sensing device”.
References
References potentially relevant to the subject matter of the claimed invention and/or relevant to the disclosure herein are listed in U.S. patent application Ser. No. 10/931,288 incorporated by reference herein.