Abstract:
A control system for safety deployment. The control system includes a processor, a first imaging sensor, and a second imaging sensor. The first and second imaging sensor are in electrical communication with the processor. The processor generates a safety system activation decision based on two-dimensional information received from the first imaging sensor and three-dimensional information based on the first and second imaging sensor.

Description:
FIELD OF THE INVENTION 
     This invention relates to a system for sensing a motor vehicle impact and the deployment of a safety device. 
     BACKGROUND AND SUMMARY OF THE INVENTION 
     Enhancements in automotive safety systems over the past several decades have provided dramatic improvements in vehicle occupant protection. Presently available motor vehicles include an array of such systems, including inflatable restraint systems for protection of occupants from frontal impacts, side impacts, and roll-over conditions. Advancements in restraint belts and vehicle interior energy absorbing systems have also contributed to enhancements in safety. Many of these systems must be deployed or actuated in a non-reversible manner upon the detection of a vehicle impact to provide their beneficial effect. Many designs for such sensors are presently used to detect the presence of an impact or roll-over condition as it occurs. 
     In addition, attention has been directed recently to providing deployable systems external to the vehicle. For example, when an impact with a pedestrian or bicyclist is imminent, external airbags can be deployed to reduce the severity of impact between the vehicle and pedestrian. Collisions with bicyclists and pedestrians account for a significant number of motor vehicle fatalities annually. Another function of an external airbag may be to provide greater compatibility between two vehicles when an impact occurs. While an effort has been made to match bumper heights for passenger cars, there remains a disparity between bumper heights, especially between classes of passenger vehicles, and especially involving collisions with heavy trucks. Through deployment of an external airbag system prior to impact, the bag can provide enhancements in the mechanical interaction between the vehicles in a manner which provides greater energy absorption, thereby reducing the severity of injuries to vehicle occupants. 
     For any safety system to operate properly, a robust sensing system is necessary. Unlike crash sensors which trigger deployment while the vehicle is crushing and decelerating, an imaging based sensing system can anticipate an impact before it has occurred. The “Time Before Collision” can be critical and, for example in an external airbag system provides the time to deploy the actuator (e.g. 30-200 ms) to clear the distance in front of the vehicle (e.g. 100-800 mm). Inadvertent deployment of safety systems is not only costly but may temporarily disable the vehicle. Moreover, since the deployment of many safety systems is achieved through a release of energy, deployment at an inappropriate time may result in undesirable effects. This invention is related to a sensing system for sensing an impending collision which addresses these design concerns. 
     Radar detection systems have been studied and employed for motor vehicles for many years. Radar systems for motor vehicles operate much like their aviation counterparts in that a radio frequency signal, typically in the microwave region, is emitted from an antenna on the vehicle and the reflected-back signal is analyzed to reveal information about the reflecting target. Such systems have been considered for use in active braking systems for motor vehicles, as well as obstacle detection systems for vehicle drivers. Radar sensing systems also have applicability in deploying external airbags. Radar sensors provide a number of valuable inputs, including the ability to detect the range to the closest object with a high degree of accuracy (e.g. 5 cm). They can also provide an output enabling measurement of closing velocity to a target with high accuracy. The radar cross section of the target and the characteristics of the return signal may also be used as a means of characterizing the target. 
     Although information obtained from radar systems yield valuable data, reliance upon a radar sensor signal for deploying a safety device may have certain negative consequences. As mentioned previously, deployment of the external airbag is a significant event and should only occur when needed in an impending impact situation. Radar sensor systems are, however, prone to “false-positive” indications. These are typically due to phenomena such as a ground reflection, projection of small objects, and software misinterpretation, which faults are referred to as “fooling” and “ghosting”. For example, a small metal object with a reflector type geometry can return as much energy as a small car and as such can generate a collision signal in the radar even when the object is too small to damage the vehicle in a substantial way. Also, there may be “near miss” situations where a target is traveling fast enough to avoid collision, yet the radar sensor system would provide a triggering signal for the safety system. 
     Imaging sensors have also been used to anticipate vehicle collisions. However, a single imaging sensor provides only two-dimensional position information about approaching objects. Certain aspects can be inferred about the travel of the object outside of the two-dimensional position, for example by determining a change is size of the object over a time period, but again this technique is not reliable enough for determining the deployment of a safety system. Alternatively, multiple vision sensors may be used to generate stereo or a three-dimensional vision system that is mounted to the vehicle. The pair of two-dimensional cameras can be designed to work as a stereo pair. By designing a stereo pair, the set of cameras can generate a three-dimensional image of the scene. Both the two-dimensional and three-dimensional vision sensors determine a range to the sensed object, the object classification, and the trajectory of the object. This information is important for correct fusion of the independently sensed information especially in a multiple target environment. The fusion of the two-dimensional and three-dimensional sensing systems provide a highly reliable non-contact sensing of an impending collision. The invention functions to provide a signal that an impact is imminent. This signal of an impending crash is generated from an object approaching the vehicle from any direction in which the sensor system is installed. In addition to an indication of impending crash, the sensor system may also indicate the potential intensity of the crash. The exact time of impact, and the direction of the impact may also be indicated by this fused sensor system. The intensity of the crash is determined by the relative size of the striking object, and the speed with which the object is approaching the host vehicle. The time and direction of the impact can be determined by repeated measurements of the object&#39;s position. This sequence of position data points can be used to compute an objects trajectory, and by comparing this trajectory with that of the host vehicle, a point of impact can be determined. The closing velocity can also be determined by using the position data and trajectory calculations. 
     By sensing and notifying the safety system of an imminent crash, this sensor enables the safety system to prepare for the impact prior to the impact. The safety system can tighten the seat belts by activating an electric pre-tensioner, which makes the seat belt system more effective at restraining the occupant after contact with the object, and during the deceleration force of the crash. The advanced warning of a frontal crash can be used to inflate a larger airbag at a much slower rate. The slower rate would reduce the potential of injury by the inflating airbag, and the larger size would offer a higher level of potential energy absorption to the occupant, compared to a smaller bag. Other advantages of the forward-looking application of this sensor are the ability to deploy additional structures or modify existing structures to maximize occupant safety. These structures could be expanding bumpers or additional frame rails or pressurized body components that would add a level of safety just prior to impact during a crash. 
     Additional deployment time enables safety devices that are slow in comparison to today&#39;s airbags. The seating position and headrest position can be modified, based on advanced crash information to increase their effectiveness in a variety of crash scenarios. Electric knee bolster extenders can be enabled to help hold the occupant in position during a crash. Advance warning also enables the windows and sunroof to close to further increase crash safety. External structures can be modified with advance notice of an impending crash. Structures such as extendable bumpers and external airbags can be deployed to further reduce the crash forces transmitted to the vehicle&#39;s occupants. 
     The system can be used in a side looking application with additional benefit to occupant safety in side crash scenarios. Knowing that a side impact will occur in advance of contact allows the side airbag to achieve similar benefit that the front airbags achieved with activation prior to impact. Such advanced activation would allow larger side bags and side curtains to deploy at slower, less aggressive rates. In a case where the contact based side airbag activation might trigger late in the crash, there is potential for the occupant to be displaced laterally before the airbag is triggered. Such displacement prior to activation reduces the effectiveness of the side airbag. In the case where a sliding vehicle crashes into a solid pole in an area of the side of the car that has less structure, like the passenger door, an acceleration based deployment system would not deploy the airbag until significant intrusion has taken place. The pre-crash sensor described here in a side looking application would give the safety system the ability to trigger the airbags prior to contact with the pole, and making the airbag more effective in protecting the occupant from the pole intrusion. 
     In a rearward looking application, the system may be used with further benefit to the host vehicle&#39;s occupants. Advance knowledge of a rear-end collision prior to contact gives the host vehicle&#39;s safety system time to move any reclined seats to a more safe upright position. The safety system has time to take up the seatbelt slack with an electric pre-tensioner to make the seatbelt more effective. Modifying the host vehicle structure is also possible with collision warning prior to impact. An expandable rear bumper could be deployed and help to absorb additional crash energy that would otherwise be transferred to the host vehicle occupants. 
     Additional benefits and advantages of the present invention will become apparent to those skilled in the art to which the present invention relates from the subsequent description of the preferred embodiment and the appended claims, taken in conjunction with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is schematic view of a system for sensing a collision and controlling deployment of a safety system in accordance with one embodiment of the present invention; and 
         FIG. 2  is a schematic view of another embodiment of a system for sensing a collision. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Referring now to  FIG. 1 , a system embodying the principles of the present invention is illustrated therein and designated at  10 . The system  10  includes a first imager  12 , a second imager  14 , and a processor  16 . 
     The first imager  12  and the second imager  14  are configured in a spaced relationship to view an object  11 . The first imager  12  has a lens system  13  that is configured to view an object from a first direction. The second imager  14  includes a second lens system  15  configured to view the object  11  from a second direction. Since the first imager  12  and second imager  14  produce images of the object from different directions, the object may have a different apparent location between the first imager  12  and second imager  14 . 
     The two-dimensional images from the first and second imager  12 ,  14 , are provided to a two-dimensional information processing algorithm  20  in processor  16 . The two-dimensional information from each imager  12 ,  14  may be used independently. For example, the first imager  12  may utilize the two-dimensional information in the image to determine a two-dimensional spacial relationship of the object to the imager  12 , use successive images to determine the distance or trajectory of the object  11 , and/or use gray scale information to classify the object. Similarly, the second imager  14  may also utilize the two-dimensional information in the image to determine a two-dimensional spacial relationship of the object  11  to the imager  14 , use successive images to determine the distance or trajectory of the object  11 , and/or use gray scale information to classify the object  11 . 
     In addition, the two-dimensional images from the imagers  12 ,  14  may be provided to a three-dimensional information processing algorithm  22  in the processor  16  where the two-dimensional image from imager  12  and the two-dimensional image from imager  14  are used in a three-dimensional processing algorithm, such as a stereo processing algorithm. A stereo processing algorithm utilizes the same principles that provide depth perception for humans. An object is identified and the image from the first imager  12  and then separately identified in an image from the second imager  14 . Knowing the relationship of the first imager  12  to the second imager  14  a triangulation method may be used to relate the position of the object  11  in the first imager  12  to the position of the object  11  in the second imager  14 . Accordingly, a first analysis result  21  may be provided based on the two-dimensional information processing  20  and a separate analysis result  23  may be provided based on the three-dimensional information processing  22 . Each analysis result  21 ,  23  may be an independent determination as to whether the object  11  will collide with the vehicle. A decision making block  24  may receive the analysis results  21 ,  23  and may combine the results for example, through a thresholding or weighting process to generate a deployment decision  26  that is communicated to the safety system  18  such as an airbag, seatbelt tensioners, expandable reinforcement devices, or other safety systems. 
     Referring now to  FIG. 2 , another embodiment of a crash sensing system  40  is provided. As previously described above, the first imager  12  and second imager  14  are provided in a spaced relationship to view an object. The imagers  12  and  14  are each in communication with both a two-dimensional information processing algorithm  20  and a three-dimensional information processing algorithm  22 . The first imager  12  provides two-dimensional image information to a scene classification and understanding algorithm  42 . The scene classification and understanding algorithm  42  may, for example, determine the type of object such as a car, motorcycle, or truck based on the size and shape of the object in the two-dimensional image. The information from the scene classification and understanding algorithm  42  is provided to a ranging and trajectory algorithm  44 . The ranging and trajectory algorithm  44  may determine the range and trajectory of objects identified in the scene classification and understanding algorithm  42 . The range and trajectory of the objects may be determined based on the size, shape, and position of the object and, further, may be determined based on the size, shape, and position change over multiple images. The range and trajectory information from the ranging and trajectory algorithm  44  is provided to a collision decision algorithm  46 . The collision decision algorithm  46  determines whether the objects will collide with the vehicle based on the ranging and trajectory information. In addition, the collision decision algorithm  46  may also consider other vehicle information in determining the likelihood of a collision with the host vehicle. 
     Similarly, the imager  14  provides the two-dimensional image to a scene classification and understanding algorithm  48 . The scene classification and understanding algorithm  48  identifies and/or segments objects in the same manner as scene classification and understanding algorithm  42 . The objects from the scene classification and understanding algorithm  48  are provided to a ranging and trajectory algorithm  50  that operates in a similar manner to ranging and trajectory algorithm  44 . The results of the ranging and trajectory algorithm  50  are provided to a collision decision algorithm  52  that generates a collision decision in a similar manner to collision decision algorithm  46 , but based on the image information from the second imager  14 . The collision analysis  47  from the collision decision algorithm  46  is independent from the collision analysis  53  provided by the collision decision algorithm  52 . Both collision analyses  47 ,  53  are provided to a deployment decision algorithm  59 . 
     In addition, the two-dimensional information from imager  12  and imager  14  are both provided to a three-dimensional information extraction algorithm  54  and the three-dimensional information processing algorithm  52 . In the three-dimensional information extraction algorithm  54 , features in the scene of the first image from imager  12  and the second image from imager  14  are compared and related based on the feature information within each image, as well as the spacial and orientation relationship between the first imager  12  and second imager  14 . Accordingly, the three-dimensional feature information is provided to an object classification algorithm  56  that determines the type of object, for example, a bike, pedestrian, or car that is identified by the algorithm  22 . The object classification information from the object classification algorithm  56  is provided to a collision decision algorithm  58 . The collision decision algorithm  58  utilizes the location and object classification information, as well as other information about the vehicle speed and trajectory to determine if a collision will occur. A collision analysis  57  is provided from the collision decision algorithm  58  to a deployment decision algorithm  59 . The deployment decision algorithm  59  combines collision analysis  57 ,  53 , and  47  to determine if one or more safety systems should be deployed. Each of the collision analyses  57 ,  53 , and  47  may be independent decisions if a collision will occur. The deployment decision algorithm  59  combines the analyses  57 ,  53 , and  47 , for example by a weighting or thresholding method to generate a deployment decision  61  that is provided to one or more safety systems  18 . 
     In addition, the information from the crash detection system  40  may be provided to a driver assistance and vehicle control system  66 . Accordingly, the three-dimensional feature information from algorithm  54  and the ranging and trajectory information from algorithms  44  and  50  may be provided to an object trajectory algorithm  60  that combines the information from algorithms  54 ,  44 , and  50  into object or trajectory information  68  with improved reliability over the analysis from the individual algorithms  54 ,  44 , and  50 . Similarly, the object classification information from the object classification algorithm  56  and object classification information from the scene classification and understanding algorithms  42  and  48  are provided to an object classification algorithm  62  where the information from the algorithms  56 ,  42 , and  48  are combined to generate object classification information  70  with improved reliability over each of the independent algorithms  56 ,  42 , and  48 . In addition, an object distance algorithm  64  receives object distance information from the three-dimensional information extraction algorithm  54 , the ranging and trajectory algorithm  44 , and the ranging and trajectory algorithm  50 . The object distance algorithm  64  combines the ranging information from the algorithms  54 ,  44 , and  50  to generate object distance information  72  with improved reliability over the individual algorithms  54 ,  44 , and  50 . Algorithms  60 ,  62 , and  64  may use various techniques to combine the information from the other algorithms and may include for example, weighting, averaging, or simply data verification methodologies to provide an improved result to the driver assistance and vehicle control system  66  which may then be used to actively manipulate the vehicle to avoid or reduce the impacts of a collision. 
     As a person skilled in the art will readily appreciate, the above description is meant as an illustration of implementation of the principles this invention. This description is not intended to limit the scope or application of this invention in that the invention is susceptible to modification, variation and change, without departing from the spirit of this invention, as defined in the following claims.