The present invention relates generally to a vehicle vision system for a vehicle and, more particularly, to a vehicle vision system that utilizes one or more cameras at a vehicle.
Use of imaging sensors in vehicle imaging systems is common and known. Examples of such known systems are described in U.S. Pat. Nos. 5,949,331; 5,670,935 and/or 5,550,677, which are hereby incorporated herein by reference in their entireties.
The present invention provides a driving assistance system or vision system or imaging system for a vehicle that includes a camera disposed at a vehicle equipped with the vehicular control system and viewing at least forward of the vehicle. The camera captures image data. The system includes a radar sensor disposed at the equipped vehicle and sensing at least forward of the equipped vehicle and an electronic control unit (ECU) that includes electronic circuitry and associated software. The electronic circuitry of the ECU includes at least one processor for processing image data captured by the camera and for processing sensor data captured by the radar sensor. As the equipped vehicle travels along a road, the ECU, via processing of image data captured by the camera and processing of sensor data captured by the radar sensor, determines other vehicles present on the road ahead of the equipped vehicle. The ECU, responsive to determining the presence of a plurality of other vehicles present on the road ahead of the equipped vehicle, fuses the image data captured by the camera and the sensor data captured by the radar sensor. The ECU, based on the fused data, determines a threat level for each vehicle of the plurality of other vehicles and, when the threat level for one or more vehicles of the plurality of other vehicles exceeds a threshold value, generates a braking command. The ECU transmits the braking command to a braking system of the equipped vehicle.
These and other objects, advantages, purposes and features of the present invention will become apparent upon review of the following specification in conjunction with the drawings.
A vehicle vision system and/or driver or driving assist system and/or object detection system and/or alert system operates to capture images exterior of the vehicle and may process the captured image data to display images and to detect objects at or near the vehicle and in the predicted path of the vehicle, such as to assist a driver of the vehicle in maneuvering the vehicle in a rearward direction. The vision system optionally includes an image processor or image processing system that is operable to receive image data from one or more cameras and provide an output to a display device for displaying images representative of the captured image data. Optionally, the vision system may provide display, such as a rearview display or a top down or bird's eye or surround view display or the like.
Referring now to the drawings and the illustrative embodiments depicted therein, a vision system 10 for a vehicle 12 includes at least one exterior viewing imaging sensor or camera, such as a forward viewing imaging sensor or camera, which may be disposed at and behind the windshield 14 of the vehicle and viewing forward through the windshield so as to capture image data representative of the scene occurring forward of the vehicle (
Environmental sensing forms an integral part of Advanced Driver Assistance Systems (ADAS) deployed in passenger vehicles today. Multiple environmental sensors such as forward-looking cameras and radars are typically employed to improve the accuracy and latency of information transfer. A fusion system may combine data from these sensors and provide significant information about the environment in front of vehicle (e.g., object and lane information). Object information is used primarily for longitudinal control of vehicles (e.g., braking and acceleration) in systems for development of safety features such as autonomous emergency braking (AEB) as well as comfort features like adaptive cruise control (ACC), etc. The system enables longitudinal control of a vehicle equipped with a camera and/or radar for an AEB system. The AEB system is intended to improve the safety of the driver and other occupants of the vehicle by preventing/minimizing rear-end collisions with vehicles in front of the equipped vehicle.
The camera (e.g., a forward viewing camera disposed at the front of the vehicle) includes hardware and software for capturing raw image data and sending raw data that includes information regarding multiple objects within the field of view of the camera, such as object positions, relative velocities, etc. and lane information such as lane coefficients, quality, etc. A radar module includes hardware and software that captures radar data and sends raw data that includes information pertaining to multiple objects such as object positions, relative velocities, etc. A fusion module or algorithm may fuse the information from the camera(s) and the radar to create a more accurate representation of the object data to be used by downstream components (e.g., a constant turn rate motion model based on a Kalman filter using an associative layer achieved via a nearest neighbor algorithm). A lane data processing module may be responsible for processing the raw data coming out of fusion module in a form that can be used by AEB system. A vehicle state estimator includes vehicle control modules/algorithms/sensors that provide vehicle state information such as vehicle speed, yaw rate, etc. A driver input processing module may be responsible for processing driver inputs such as button presses, voice commands, and the like, as well as accelerator/brake pedal actuation and steering wheel actuation. A threat assessment module may determine a potential of all objects forward of the vehicle and within the field of view/sensing of the camera and/or radar. The threat assessment module may assess the threat potential for each of the objects (e.g., a threat of the object colliding with the equipped vehicle).
A warning controller may be responsible for alerting the driver or other occupant through audio/visual/haptic means in the presence of a confirmed threat. For example, the system may interface with a Human-Machine interface (HMI) that receives the audio/visual/haptic alerts from the AEB controller and presents the alerts to the driver or other occupants. A vehicle brake module communicates with or includes the braking system (hardware and software) of the vehicle that applies the braking torque command to enable the ADAS feature for longitudinal control of the vehicle.
Referring now to
Optionally, a threat filtering module improves the robustness of the threat assessment module to sensor disturbances. The threat filtering module includes (i) an object hold filter to hold objects of interest for certain time if not detected by the sensors, (ii) an object rejection filter that rejects objects which appear for less than a threshold period of time, and (iii) an oncoming filter that applies logic reasoning to negate oncoming objects based on the overall object data received from sensors (e.g., signposts, bridges, etc.).
A threat evaluation module may be responsible for confirming threats out of all the potential threats (i.e., from the threat assessment module) using predefined metrics based on the deceleration of the equipped vehicle necessary to achieve collision avoidance (i.e., avoid collision with the detected object). A haptic controller module alerts the driver through a series of braking events that may not cause any perceivable vehicle deceleration. A closed-loop AEB longitudinal controller may be responsible for applying the correct level of safety braking to prevent the imminent collision within limits and to achieve consistent stopping distance.
Thus, implementations herein provide an autonomous emergency braking (AEB) system that longitudinally controls the vehicle to avoid collision with other vehicles and to provide maximum braking within limits specified by regulations as the equipped vehicle approaches a potential collision threat. The system includes one or more cameras that capture image data that is processed by the vehicular control system. Optionally, the camera(s) are included within a module (such as a front camera module (FCM)) that includes an image processor and ADAS feature software supporting the functionality describing above. That is, in some examples, a camera ECU locally processes the captured image data to perform automatic emergency braking functions. In other examples, the camera module includes an image processor that processes the image data and a separate ECU or processor that executes the ADAS feature software. In yet other examples, the camera module includes an image processor that processes the image data and the ADAS feature software is executed by an ECU or processor of the vehicle that is remote from the camera module.
For autonomous vehicles suitable for deployment with systems herein, an occupant of the vehicle may, under particular circumstances, be desired or required to take over operation/control of the vehicle and drive the vehicle so as to avoid potential hazard for as long as the autonomous system relinquishes such control or driving. Such occupant of the vehicle thus becomes the driver of the autonomous vehicle. As used herein, the term “driver” refers to such an occupant, even when that occupant is not actually driving the vehicle, but is situated in the vehicle so as to be able to take over control and function as the driver of the vehicle when the vehicle control system hands over control to the occupant or driver or when the vehicle control system is not operating in an autonomous or semi-autonomous mode.
Typically an autonomous vehicle would be equipped with a suite of sensors, including multiple machine vision cameras deployed at the front, sides and rear of the vehicle, multiple radar sensors deployed at the front, sides and rear of the vehicle, and/or multiple lidar sensors deployed at the front, sides and rear of the vehicle. Typically, such an autonomous vehicle will also have wireless two way communication with other vehicles or infrastructure, such as via a car2car (V2V) or car2x communication system.
The camera or sensor may comprise any suitable camera or sensor. Optionally, the camera may comprise a “smart camera” that includes the imaging sensor array and associated circuitry and image processing circuitry and electrical connectors and the like as part of a camera module, such as by utilizing aspects of the vision systems described in U.S. Pat. Nos. 10,099,614 and/or 10,071,687, which are hereby incorporated herein by reference in their entireties.
The system includes an image processor operable to process image data captured by the camera or cameras, such as for detecting objects or other vehicles or pedestrians or the like in the field of view of one or more of the cameras. For example, the image processor may comprise an image processing chip selected from the EYEQ family of image processing chips available from Mobileye Vision Technologies Ltd. of Jerusalem, Israel, and may include object detection software (such as the types described in U.S. Pat. Nos. 7,855,755; 7,720,580 and/or 7,038,577, which are hereby incorporated herein by reference in their entireties), and may analyze image data to detect vehicles and/or other objects. Responsive to such image processing, and when an object or other vehicle is detected, the system may generate an alert to the driver of the vehicle and/or may generate an overlay at the displayed image to highlight or enhance display of the detected object or vehicle, in order to enhance the driver's awareness of the detected object or vehicle or hazardous condition during a driving maneuver of the equipped vehicle.
The vehicle may include any type of sensor or sensors, such as imaging sensors or radar sensors or lidar sensors or ultrasonic sensors or the like. The imaging sensor or camera may capture image data for image processing and may comprise any suitable camera or sensing device, such as, for example, a two dimensional array of a plurality of photosensor elements arranged in at least 640 columns and 480 rows (at least a 640×480 imaging array, such as a megapixel imaging array or the like), with a respective lens focusing images onto respective portions of the array. The photosensor array may comprise a plurality of photosensor elements arranged in a photosensor array having rows and columns. Preferably, the imaging array has at least 300,000 photosensor elements or pixels, more preferably at least 500,000 photosensor elements or pixels and more preferably at least 1 million photosensor elements or pixels. The imaging array may capture color image data, such as via spectral filtering at the array, such as via an RGB (red, green and blue) filter or via a red/red complement filter or such as via an RCC (red, clear, clear) filter or the like. The logic and control circuit of the imaging sensor may function in any known manner, and the image processing and algorithmic processing may comprise any suitable means for processing the images and/or image data.
For example, the vision system and/or processing and/or camera and/or circuitry may utilize aspects described in U.S. Pat. Nos. 9,233,641; 9,146,898; 9,174,574; 9,090,234; 9,077,098; 8,818,042; 8,886,401; 9,077,962; 9,068,390; 9,140,789; 9,092,986; 9,205,776; 8,917,169; 8,694,224; 7,005,974; 5,760,962; 5,877,897; 5,796,094; 5,949,331; 6,222,447; 6,302,545; 6,396,397; 6,498,620; 6,523,964; 6,611,202; 6,201,642; 6,690,268; 6,717,610; 6,757,109; 6,802,617; 6,806,452; 6,822,563; 6,891,563; 6,946,978; 7,859,565; 5,550,677; 5,670,935; 6,636,258; 7,145,519; 7,161,616; 7,230,640; 7,248,283; 7,295,229; 7,301,466; 7,592,928; 7,881,496; 7,720,580; 7,038,577; 6,882,287; 5,929,786 and/or 5,786,772, and/or U.S. Publication Nos. US-2014-0340510; US-2014-0313339; US-2014-0347486; US-2014-0320658; US-2014-0336876; US-2014-0307095; US-2014-0327774; US-2014-0327772; US-2014-0320636; US-2014-0293057; US-2014-0309884; US-2014-0226012; US-2014-0293042; US-2014-0218535; US-2014-0218535; US-2014-0247354; US-2014-0247355; US-2014-0247352; US-2014-0232869; US-2014-0211009; US-2014-0160276; US-2014-0168437; US-2014-0168415; US-2014-0160291; US-2014-0152825; US-2014-0139676; US-2014-0138140; US-2014-0104426; US-2014-0098229; US-2014-0085472; US-2014-0067206; US-2014-0049646; US-2014-0052340; US-2014-0025240; US-2014-0028852; US-2014-005907; US-2013-0314503; US-2013-0298866; US-2013-0222593; US-2013-0300869; US-2013-0278769; US-2013-0258077; US-2013-0258077; US-2013-0242099; US-2013-0215271; US-2013-0141578 and/or US-2013-0002873, which are all hereby incorporated herein by reference in their entireties. The system may communicate with other communication systems via any suitable means, such as by utilizing aspects of the systems described in U.S. Pat. Nos. 10,071,687; 9,900,490; 9,126,525 and/or 9,036,026, which are hereby incorporated herein by reference in their entireties.
Optionally, the camera may comprise a forward viewing camera, such as disposed at a windshield electronics module (WEM) or the like. The forward viewing camera may utilize aspects of the systems described in U.S. Pat. Nos. 9,896,039; 9,871,971; 9,596,387; 9,487,159; 8,256,821; 7,480,149; 6,824,281 and/or 6,690,268, and/or U.S. Publication Nos. US-2015-0327398; US-2015-0015713; US-2014-0160284; US-2014-0226012 and/or US-2009-0295181, which are all hereby incorporated herein by reference in their entireties.
The system may utilize sensors, such as radar or lidar sensors or the like. The sensing system may utilize aspects of the systems described in U.S. Pat. Nos. 9,753,121; 9,689,967; 9,599,702; 9,575,160; 9,146,898; 9,036,026; 8,027,029; 8,013,780; 7,053,357; 7,408,627; 7,405,812; 7,379,163; 7,379,100; 7,375,803; 7,352,454; 7,340,077; 7,321,111; 7,310,431; 7,283,213; 7,212,663; 7,203,356; 7,176,438; 7,157,685; 6,919,549; 6,906,793; 6,876,775; 6,710,770; 6,690,354; 6,678,039; 6,674,895 and/or 6,587,186, and/or International Publication Nos. WO 2018/007995 and/or WO 2011/090484, and/or U.S. Publication Nos. US-2018-0231635; US-2018-0045812; US-2018-0015875; US-2017-0356994; US-2017-0315231; US-2017-0276788; US-2017-0254873; US-2017-0222311 and/or US-2010-0245066, which are hereby incorporated herein by reference in their entireties.
The radar sensors of the sensing system each comprise a plurality of transmitters that transmit radio signals via a plurality of antennas, a plurality of receivers that receive radio signals via the plurality of antennas, with the received radio signals being transmitted radio signals that are reflected from an object present in the field of sensing of the respective radar sensor. The system includes an ECU or control that includes a data processor for processing sensor data captured by the radar sensors. The ECU or sensing system may be part of a driving assist system of the vehicle, with the driving assist system controls at least one function or feature of the vehicle (such as to provide autonomous driving control of the vehicle) responsive to processing of the data captured by the radar sensors.
The system may also communicate with other systems, such as via a vehicle-to-vehicle communication system or a vehicle-to-infrastructure communication system or the like. Such car2car or vehicle to vehicle (V2V) and vehicle-to-infrastructure (car2X or V2X or V2I or a 4G or 5G broadband cellular network) technology provides for communication between vehicles and/or infrastructure based on information provided by one or more vehicles and/or information provided by a remote server or the like. Such vehicle communication systems may utilize aspects of the systems described in U.S. Pat. Nos. 6,690,268; 6,693,517 and/or 7,580,795, and/or U.S. Publication Nos. US-2014-0375476; US-2014-0218529; US-2013-0222592; US-2012-0218412; US-2012-0062743; US-2015-0251599; US-2015-0158499; US-2015-0124096; US-2015-0352953; US-2016-0036917 and/or US-2016-0210853, which are hereby incorporated herein by reference in their entireties.
Changes and modifications in the specifically described embodiments can be carried out without departing from the principles of the invention, which is intended to be limited only by the scope of the appended claims, as interpreted according to the principles of patent law including the doctrine of equivalents.
The present application claims the filing benefits of U.S. provisional application Ser. No. 62/706,438, filed Aug. 17, 2020, which is hereby incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5550677 | Schofield et al. | Aug 1996 | A |
5670935 | Schofield | Sep 1997 | A |
5949331 | Schofield | Sep 1999 | A |
6690268 | Schofield et al. | Feb 2004 | B2 |
6824281 | Schofield et al. | Nov 2004 | B2 |
7038577 | Pawlicki et al. | May 2006 | B2 |
7205904 | Schofield | Apr 2007 | B2 |
7480149 | DeWard et al. | Jan 2009 | B2 |
7720580 | Higgins-Luthman | May 2010 | B2 |
7855755 | Weller et al. | Dec 2010 | B2 |
8256821 | Lawlor et al. | Sep 2012 | B2 |
9180908 | Van Dan Elzen et al. | Nov 2015 | B2 |
9487159 | Achenbach | Nov 2016 | B2 |
9596387 | Achenbach et al. | Mar 2017 | B2 |
9871971 | Wang et al. | Jan 2018 | B2 |
9896039 | Achenbach et al. | Feb 2018 | B2 |
9988047 | Johnson et al. | Jun 2018 | B2 |
10032369 | Koravadi | Jul 2018 | B2 |
10055651 | Chundrlik, Jr. et al. | Aug 2018 | B2 |
10071687 | Ihlenburg et al. | Sep 2018 | B2 |
10099614 | Diessner | Oct 2018 | B2 |
10214157 | Achenbach | Feb 2019 | B2 |
10222224 | Johnson | Mar 2019 | B2 |
10268904 | Gupta | Apr 2019 | B2 |
10315651 | Fiaschetti et al. | Jun 2019 | B2 |
10406981 | Chundrlik, Jr. | Sep 2019 | B2 |
10449899 | Gupta et al. | Oct 2019 | B2 |
10457209 | Byrne | Oct 2019 | B2 |
10787125 | Achenbach | Sep 2020 | B2 |
10812992 | Tran | Oct 2020 | B1 |
11017665 | Roy | May 2021 | B1 |
11763410 | Roy | Sep 2023 | B1 |
20050179527 | Schofield | Aug 2005 | A1 |
20080192984 | Higuchi | Aug 2008 | A1 |
20090295181 | Lawlor et al. | Dec 2009 | A1 |
20130297387 | Michael | Nov 2013 | A1 |
20140160284 | Achenbach et al. | Jun 2014 | A1 |
20140226012 | Achenbach | Aug 2014 | A1 |
20150015713 | Wang et al. | Jan 2015 | A1 |
20150327398 | Achenbach et al. | Nov 2015 | A1 |
20160159394 | Ryu | Jun 2016 | A1 |
20180173239 | Yoon | Jun 2018 | A1 |
20200327343 | Lund | Oct 2020 | A1 |
20210061276 | Zhang | Mar 2021 | A1 |
20210221390 | Slobodyanyuk | Jul 2021 | A1 |
20210385865 | Mueck | Dec 2021 | A1 |
20210392454 | Choi | Dec 2021 | A1 |
20220024485 | Theverapperuma | Jan 2022 | A1 |
20220048509 | Prasad Challa | Feb 2022 | A1 |
20220048566 | Prasad Challa et al. | Feb 2022 | A1 |
20220097625 | Russell | Mar 2022 | A1 |
20220255223 | Tran | Aug 2022 | A1 |
Entry |
---|
Snider J.M., “Automatic Steering Methods for Autonomous Automobile Path Tracking”, Feb. 2009, CMU thesis. |
Werling et al., Invariant Trajectory Tracking With a Full-Size Autonomous Road Vehicle, IEEE, vol. 26, No. 4, Aug. 2010. |
Werling et al., Optimal trajectories for time-critical street scenarios using discretized terminal manifolds, The International Journal of Robotics Research, Mar. 2012. |
Number | Date | Country | |
---|---|---|---|
20220048504 A1 | Feb 2022 | US |
Number | Date | Country | |
---|---|---|---|
62706438 | Aug 2020 | US |