WO2003006279A1 - Überwachungssystem für einen fahrzeuginnenraum - Google Patents
Überwachungssystem für einen fahrzeuginnenraum Download PDFInfo
- Publication number
- WO2003006279A1 WO2003006279A1 PCT/DE2002/002514 DE0202514W WO03006279A1 WO 2003006279 A1 WO2003006279 A1 WO 2003006279A1 DE 0202514 W DE0202514 W DE 0202514W WO 03006279 A1 WO03006279 A1 WO 03006279A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- occupancy
- probabilities
- vehicle interior
- classes
- transition probabilities
- Prior art date
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 32
- 230000008859 change Effects 0.000 claims abstract description 11
- 230000007704 transition Effects 0.000 claims description 83
- 238000000034 method Methods 0.000 claims description 26
- 239000011159 matrix material Substances 0.000 claims description 10
- 238000005259 measurement Methods 0.000 claims description 10
- 238000004422 calculation algorithm Methods 0.000 claims description 7
- 238000012935 Averaging Methods 0.000 claims description 6
- 230000006870 function Effects 0.000 claims description 5
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 241000295146 Gallionellaceae Species 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000007635 classification algorithm Methods 0.000 description 2
- 230000006378 damage Effects 0.000 description 2
- 238000009499 grossing Methods 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 235000014676 Phragmites communis Nutrition 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000036962 time dependent Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
- 238000002604 ultrasonography Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
- B60R21/015—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting the presence or position of passengers, passenger seats or child seats, and the related safety parameters therefor, e.g. speed or timing of airbag inflation in relation to occupant position or seat belt use
- B60R21/01512—Passenger detection systems
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/002—Seats provided with an occupancy detection means mounted therein or thereon
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
- B60R21/015—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting the presence or position of passengers, passenger seats or child seats, and the related safety parameters therefor, e.g. speed or timing of airbag inflation in relation to occupant position or seat belt use
- B60R21/01556—Child-seat detection systems
Definitions
- the invention relates to a monitoring system for a vehicle interior with a device for recording data reflecting the occupancy status of a location in the vehicle interior and with a computing unit for obtaining probabilities of belonging to occupancy classes for the location in the vehicle interior with the aid of the
- Occupancy status of the location in the vehicle interior reflecting features from measurement data of the device.
- a method and a device for determining the position of an object in a vehicle are known from WO 00 65538.
- This method is based on the problem that airbag systems in motor vehicles can lead to personal injuries in individual cases. The reason for this is usually that the airbag system has no reliable information about the position of the passenger.
- the inflation process is designed for extreme situations, which means that an adult, buckled-up person must not bump through to the dashboard in the event of an accident. However, if the passenger's head is too close to the dashboard (out-of-position) at the time of inflation, this configuration of the airbag system can lead to serious injuries. Numerous systems are under development to remedy this problem.
- the same measurement methods can also be used to determine the occupancy of other seats in the vehicle, for example the rear seats. Even more generalized, such a measurement method can also be used to determine the occupancy of a luggage rack.
- the measuring system is part of a monitoring system, which is additionally equipped with a device for detecting the occupancy state of a seat, in particular the front passenger seat, or also several seats or areas within the vehicle.
- the triggering decision of the airbag control unit is influenced depending on the occupancy status detected.
- the occupancy status is shown with the help of so-called occupancy classes.
- a discrete occupancy class is assigned to each object within the vehicle that is monitored by the monitoring system.
- the occupancy classes are typically the following classes:
- the known monitoring system has the further problem that due to technical restrictions of the sensor system or the sensor systems, if two or more sensor systems are used in connection with one another, occupancy classes in the feature space overlap. In this case, it is not possible to clearly assign the characteristics to a single occupancy class.
- the object is achieved in a device of the type mentioned at the outset in that the computing unit is connected to a memory in which transition probabilities between the occupancy classes are stored, according to which transitions between occupancy classes occur.
- transition probabilities are determined according to which transitions between the occupancy classes take place.
- the assignment to the occupancy classes is based on membership probabilities. These are possibilistic probabilities, i. H. Class membership is between 0 and 1, but the sum of all membership probabilities does not have to be 1, as with probabilistic probabilities.
- Possibilistic probabilities and classification methods based on them are known, for example in neural networks, fuzzy clustering, vector support machines.
- the essence of the invention lies in the definition of the transition probabilities between two occupancy classes. In this way, the number of measurement cycles can be controlled within which the classification can jump from one occupancy class to another.
- the transition from “empty seat” to “adult person” must be possible very quickly since the airbag is typically switched off when the seat is empty, but has to be activated by one person. Therefore, a high transition probability from "empty seat” to "adult person” must be provided. Conversely, it is critical if the airbag is switched off for a person because the classification result temporarily jumps to "empty seat”.
- the transition from "adult person” to "child seat” is also critical, since the adult triggers the airbag in one However, the child seat attached to the seat is not, and a transition must also be permitted in this case
- the transition probability must be small so that a transition can take place after several matching measurement cycles. Because of the small transition probability, a high level of security is built in, which prevents the airbag from failing to function in an adult person.
- the invention also relates to a generic monitoring system for a vehicle interior, which is characterized in that a threshold value is defined and that the features are only assigned to an occupancy class if they are above the threshold value.
- the assignment to an occupancy class is based on the following rules: Belonging to this occupancy class is the highest.
- the affiliation is preferably above a threshold value introduced according to the invention, which can be predetermined for the computing unit when implementing the computing algorithm.
- the boundary area between two occupancy classes in the characteristic space lies exactly where the possible probabilities of belonging to a characteristic set assume the same value.
- the invention can be used with particular advantage if the monitoring system is additionally equipped with a switch or a sensor for detecting the opening state of at least one door of the vehicle.
- the computing unit is then connected to the switch or the sensor via a data line.
- the computing unit receives this information depending on whether one or more doors are open or closed.
- An algorithm is available in the computing unit, according to which the transition probabilities can be set depending on when the door was last opened. In this way, a suitable transition probability between two occupancy classes is also specified if, after the door is closed, the monitoring system is reactivated after a reset and no data from the past are available to obtain suitable transition probabilities.
- transition probabilities are available for the monitoring system even when the monitoring system is activated for the first time or after a reset, these are predefined for the computing unit, so that after detection of the closing of the vehicle door, these predefined transition probabilities are used.
- the monitoring system can also react quickly to a real change in the occupancy state in this situation, for example, when a person gets out and places a child seat on the front passenger seat.
- transition probabilities are stored in the memory as matrix elements.
- the transition probabilities are expressed by numerical values which embody the number of classification cycles, according to which a change in an occupancy state from one occupancy class to another occupancy class is considered to have occurred.
- transition probabilities are stored in the matrix as digits between 0 and 1.
- n occupancy classes an n x n matrix is defined in which the transition probabilities are summarized. It is for each possible initial state, i.e. H. the current classification result, a transition probability to every possible target state, d. H. the new classification result.
- the transition probabilities are based on the frequency of the corresponding state changes to be expected in practice, taking into account the criticality of this transition with regard to influencing the airbag deployment. For example, a transition from the occupancy class "rear-facing child seat” to the class “forward-facing child seat” can be classified as rather uncritical, since the airbag is switched off for both classification results.
- the invention also relates to a method for monitoring a vehicle interior, in which data are measured that reflect the occupancy status of a location in the vehicle interior, and wherein membership probabilities for occupancy classes for a selected location in the vehicle interior using the occupancy status features reflecting a location in the vehicle interior can be obtained from measured data.
- the method is characterized in that transition probabilities between the occupancy classes are determined, according to which transitions between the occupancy classes occur.
- the transition probabilities are determined according to how likely the transition is viewed. This can be determined experimentally, for example.
- the transition probabilities can also be determined according to how reliably the membership probabilities are obtained. If, due to an inaccuracy of the measuring system, characteristics belonging to an occupancy class cannot be determined with such a high degree of certainty for metrological reasons, this can be offset by correspondingly higher transition probabilities to other occupancy classes in which the probabilities of membership are determined with greater certainty can be.
- the occupancy class for which the airbag must be activated must therefore be equipped with a high probability of transition from another occupancy class to it and with a low probability of transition from it.
- the invention provides that the transition probabilities are changed as a function of the time or the state of motion of the vehicle.
- the invention also includes a method in which the values for the membership probabilities are smoothed over time by averaging. The influence of measurement errors can also be mitigated by calculating the statistical mean value of the last classifications obtained, ie by smoothing the values over time.
- the classification results are saved over a specific period of time adapted to the problem.
- ambiguities in the assignment of a characteristic to an occupancy class are then eliminated.
- the weighting of the current membership probabilities in comparison to the weighting of the historical membership probabilities can be individually influenced depending on the corresponding tax parameters for each individual occupancy class.
- the weighting of the current membership probabilities in the individual occupancy classes can be Histories can be controlled using the transition probabilities described above.
- This can, for example, reinforce the average membership of occupancy classes that belong to the classification group of the current classification result (e.g. group of child seats), while the average membership of occupancy classes that do not belong to the classification group of the current classification result (e.g. group of adult persons) are weakened, making a transition from the classification state "child seat” to the classification state "adult person” less likely.
- an advantageous embodiment provides that a safety device for protecting people and / or objects in the vehicle interior remains switched off while the door is open.
- an airbag remains switched off as long as the door is open. This prevents the airbag from being triggered incorrectly when the vehicle is stationary.
- this fact is also taken into account in that the results of classifications of an occupancy state to occupancy classes of the seat are used for averaging for each occupancy class, the number of results flowing into the averaging increasing over time becomes. This results in an increasing smoothing of the values for the occupancy status.
- the transition probability is only adjusted for a special, selected occupancy class, for example for the occupancy class "person sitting normally”. As long as the classification "person sitting normally” is not made over a certain period of time with high probability , it is assumed that the object detected by the sensor is a child seat and accordingly assigned the occupancy class "child seat”.
- transition probabilities are adjusted so that the stabilized classification state can no longer be disturbed by temporary fluctuations in the membership probabilities.
- the invention is explained in more detail in an exemplary embodiment with reference to the drawing.
- the single figure shows membership values (o) of occupancy classes for an adult P, a child seat K and an empty seat L as a function of time t and classification results ( * ), which are the current using a plurality of measured membership values (I) Values using the classification algorithm.
- the classification algorithm takes into account the current three-dimensional image obtained from a CMOS or a CCD camera and also uses the previous three-dimensional images for decision-making.
- the functionality of the algorithm is shown on the basis of a real seat occupancy sequence over the course of time t. First the seat is occupied by a person P, then the seat is left by person P (empty seat L). Then a child seat K is placed on the seat. Finally, the child seat is removed again; the seat is empty again (state L). At the end the takes again
- the resulting classification result is then determined as the class that has the highest effective value. Because of the high current values for P, the resulting classification result is available after the second classification cycle after the camera and the monitoring system have been switched on, for example when the ignition lock of the vehicle is actuated.
- the effective value for L increases sharply, so that after two classification cycles, the empty seat is output again as the result of the classification.
- the effective value for L almost drops to 0, while the effective value for K increases, so that the resulting classification result is switched to K very quickly.
- strongly fluctuating current values for K are determined, which, however, are smoothed to effective values by means of the algorithm, which only have a small fluctuation range.
- transition phases between the different occupancy classes are controlled by adjustable transition probabilities, which can be represented in a matrix:
- the numbers represent the transition probabilities that should exist between the different occupancy states and that are predefined for the computing unit.
- the m occupancy classes L, K, P in a column represent the initial occupancy classes L, K, P the occupancy classes to which the change takes place.
- the numbers represent the reciprocal of the number of classification cycles that are required to change from one classification state to another classification state. Large matrix values thus represent high transition probabilities, while small matrix values represent small transition probabilities. Since adult persons P can be classified very reliably and a sudden transition from P to a child seat K is very unlikely, the low transition probability 0.1 is used in the matrix for the transition from P to K. A change of state from P to K usually takes place in such a way that the adult P leaves the seat and the latter is then empty. Only then is the child seat K placed on the seat.
- the following matrix is also specified for only three occupancy classes for the transition probabilities:
- transition probabilities are either determined once by a matrix, as shown above, but they can also be changeable over time in another embodiment of the invention.
- transition probabilities between the occupancy classes for example the closing or opening of a door. Due to the inclusion of the fall state (open or closed) in the classification, the transition probabilities between two occupancy classes can be adapted to the events.
- a door switch for example a reed contact
- a mechanical switch or a sensor in particular by means of a two- or three-dimensional occupant monitoring system, the open state of a door or a plurality of doors is detected.
- the classification system connected to the computing unit is in the reset state.
- the airbag is switched off during this time This prevents the classification system from being influenced by the head or upper body of people who bend into the vehicle interior, for example to place or attach a child seat to the front passenger seat, and to produce erroneous classification results that can then be based on an earlier one Classifications with an assignment to an occupancy class have a negative impact on the following classification process.
- the surface of the person corresponds to a rear-facing child seat, so that a 3D camera classifies the person as a child seat and the airbag is deactivated, because the monitoring system already reclassifies this unique measurement result.
- the "person” classification should be maintained if the person bends forward after a long journey and the current classification result fails as a "child seat". Since a transition between two occupancy classes becomes less realistic with increasing time after the door is closed, the transition probabilities are also reduced accordingly. For example, these fall proportionally to the passage of time, or they are inversely proportional to the time.
- the adjustment takes place over time, for. B. by increasing the number of last classifications over which the averaging takes place with each further classification.
- the adjustment is only limited to the case of "person sitting normally”. As long as the classification "person sitting normally” has not occurred with high probability over a certain period of time, it is assumed that the object is in the seat is a child seat. This means that an adjustment is made dependent on the fact that in the past there must have been a high probability of belonging to the occupancy class in the past in order for the surveillance system to return to this occupancy class.
- the adjustment can also be done via the stability of the classification result: If the classification result and the corresponding membership probabilities have settled to a stable classification state, the transition probabilities are adjusted so that the stabilized classification state is no longer caused by temporary fluctuations in the membership status - Probability values can be disturbed.
- the invention provides a monitoring system for a
- Vehicle interior created when switching in the occupancy of a seat, for example with a person P, a child seat K, with an empty seat L or with occupancy in another occupancy class in a computing unit are realized by transition probabilities that are given to the monitoring system from outside and which reflect the speed at which a change in occupancy is taken into account by the monitoring system. This then depends on whether an associated airbag or other safety device is activated or switched off for the respective seat.
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US10/483,327 US7124007B2 (en) | 2001-07-10 | 2002-07-09 | System for monitoring the interior of a vehicle |
KR1020047000426A KR100862109B1 (ko) | 2001-07-10 | 2002-07-09 | 차량 내부를 모니터링하기 위한 시스템 |
DE50205044T DE50205044D1 (de) | 2001-07-10 | 2002-07-09 | Überwachungssystem für einen fahrzeuginnenraum |
EP02753003A EP1404548B1 (de) | 2001-07-10 | 2002-07-09 | Überwachungssystem für einen fahrzeuginnenraum |
JP2003512065A JP2004533965A (ja) | 2001-07-10 | 2002-07-09 | 車内に対する監視システム |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE10133512.1 | 2001-07-10 | ||
DE10133512 | 2001-07-10 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2003006279A1 true WO2003006279A1 (de) | 2003-01-23 |
Family
ID=7691293
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/DE2002/002514 WO2003006279A1 (de) | 2001-07-10 | 2002-07-09 | Überwachungssystem für einen fahrzeuginnenraum |
Country Status (6)
Country | Link |
---|---|
US (1) | US7124007B2 (de) |
EP (1) | EP1404548B1 (de) |
JP (1) | JP2004533965A (de) |
KR (1) | KR100862109B1 (de) |
DE (1) | DE50205044D1 (de) |
WO (1) | WO2003006279A1 (de) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102004005491A1 (de) * | 2004-02-04 | 2005-08-25 | Adam Opel Ag | Sensierungssystem zur Erkennung eines Sidecrashs |
US10001791B2 (en) | 2012-07-27 | 2018-06-19 | Assa Abloy Ab | Setback controls based on out-of-room presence information obtained from mobile devices |
US10050948B2 (en) | 2012-07-27 | 2018-08-14 | Assa Abloy Ab | Presence-based credential updating |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7734061B2 (en) * | 1995-06-07 | 2010-06-08 | Automotive Technologies International, Inc. | Optical occupant sensing techniques |
JPWO2003034738A1 (ja) * | 2001-10-10 | 2005-02-10 | 松下電器産業株式会社 | 画像処理装置 |
DE10163910A1 (de) * | 2001-12-22 | 2003-07-03 | Bosch Gmbh Robert | Vorrichtung zur Insassenklassifizierung und Verfahren zur Insassenklassifizierung |
WO2004075105A2 (en) * | 2003-02-20 | 2004-09-02 | Intelligent Mechatronic Systems Inc. | Adaptive visual occupant detection and classification system |
KR102355421B1 (ko) | 2015-12-15 | 2022-01-26 | 현대자동차주식회사 | 차량의 알림 출력 시스템 및 그 방법 |
US10493957B2 (en) * | 2016-08-18 | 2019-12-03 | Toyota Motor Engineering & Manufacturing North America, Inc. | Operational mode change based on vehicle occupancy for an autonomous vehicle |
DE102017201965A1 (de) * | 2017-02-08 | 2018-08-09 | Robert Bosch Gmbh | Verfahren zur Erkennung einer Sitzbelegung |
WO2020165908A2 (en) * | 2019-02-17 | 2020-08-20 | Guardian Optical Technologies Ltd | System, device, and methods for detecting and obtaining information on objects in a vehicle |
Citations (5)
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US5482314A (en) * | 1994-04-12 | 1996-01-09 | Aerojet General Corporation | Automotive occupant sensor system and method of operation by sensor fusion |
WO1998049031A1 (en) * | 1997-04-25 | 1998-11-05 | Automotive Systems Laboratory, Inc. | Vehicle occupant discrimination system and method |
US5906393A (en) * | 1997-09-16 | 1999-05-25 | Trw Inc. | Occupant restraint system and control method with variable sense, sample, and determination rates |
WO2000065538A1 (de) | 1999-04-23 | 2000-11-02 | Siemens Aktiengesellschaft | Verfahren und vorrichtung zur ermittlung der position eines objektes innerhalb einer szene |
WO2001014910A2 (en) * | 1999-05-27 | 2001-03-01 | Automotive Technologies International, Inc. | Method for developing a system for identifying the presence and orientation of an object in a vehicle |
Family Cites Families (6)
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US4612876A (en) * | 1984-12-27 | 1986-09-23 | Unique Gifts, Inc. | Aquarium |
DE4339113C2 (de) * | 1993-11-16 | 1996-09-05 | Daimler Benz Ag | Sitzbelegungserkennungseinrichtung in einem Kraftfahrzeug |
US5851026A (en) * | 1994-10-17 | 1998-12-22 | I.E.E. International Electronics & Engineering | Method and installation for detecting certain parameters concerning an auxiliary child seat with a view to controlling the operation of the airbags of a vehicle |
US6027138A (en) | 1996-09-19 | 2000-02-22 | Fuji Electric Co., Ltd. | Control method for inflating air bag for an automobile |
US5999893A (en) * | 1997-05-02 | 1999-12-07 | The United States Of America As Represented By The Secretary Of The Navy | Classification system and method using combined information testing |
JP3286219B2 (ja) | 1997-09-11 | 2002-05-27 | トヨタ自動車株式会社 | 座席の使用状況判定装置 |
-
2002
- 2002-07-09 DE DE50205044T patent/DE50205044D1/de not_active Expired - Lifetime
- 2002-07-09 KR KR1020047000426A patent/KR100862109B1/ko not_active IP Right Cessation
- 2002-07-09 JP JP2003512065A patent/JP2004533965A/ja active Pending
- 2002-07-09 EP EP02753003A patent/EP1404548B1/de not_active Expired - Fee Related
- 2002-07-09 WO PCT/DE2002/002514 patent/WO2003006279A1/de active IP Right Grant
- 2002-07-09 US US10/483,327 patent/US7124007B2/en not_active Expired - Fee Related
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5482314A (en) * | 1994-04-12 | 1996-01-09 | Aerojet General Corporation | Automotive occupant sensor system and method of operation by sensor fusion |
WO1998049031A1 (en) * | 1997-04-25 | 1998-11-05 | Automotive Systems Laboratory, Inc. | Vehicle occupant discrimination system and method |
US5906393A (en) * | 1997-09-16 | 1999-05-25 | Trw Inc. | Occupant restraint system and control method with variable sense, sample, and determination rates |
WO2000065538A1 (de) | 1999-04-23 | 2000-11-02 | Siemens Aktiengesellschaft | Verfahren und vorrichtung zur ermittlung der position eines objektes innerhalb einer szene |
WO2001014910A2 (en) * | 1999-05-27 | 2001-03-01 | Automotive Technologies International, Inc. | Method for developing a system for identifying the presence and orientation of an object in a vehicle |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102004005491A1 (de) * | 2004-02-04 | 2005-08-25 | Adam Opel Ag | Sensierungssystem zur Erkennung eines Sidecrashs |
US10001791B2 (en) | 2012-07-27 | 2018-06-19 | Assa Abloy Ab | Setback controls based on out-of-room presence information obtained from mobile devices |
US10050948B2 (en) | 2012-07-27 | 2018-08-14 | Assa Abloy Ab | Presence-based credential updating |
US10606290B2 (en) | 2012-07-27 | 2020-03-31 | Assa Abloy Ab | Controlling an operating condition of a thermostat |
Also Published As
Publication number | Publication date |
---|---|
US7124007B2 (en) | 2006-10-17 |
EP1404548A1 (de) | 2004-04-07 |
EP1404548B1 (de) | 2005-11-23 |
KR100862109B1 (ko) | 2008-10-09 |
JP2004533965A (ja) | 2004-11-11 |
DE50205044D1 (de) | 2005-12-29 |
US20040176891A1 (en) | 2004-09-09 |
KR20040022446A (ko) | 2004-03-12 |
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