The present invention relates generally to a vehicle sensing system for a vehicle and, more particularly, to a vehicle sensing system that utilizes one or more sensors at a vehicle to provide a field of sensing at or around the vehicle.
Use of imaging sensors or ultrasonic sensors or radar sensors in vehicle sensing systems is common and known. Examples of such known systems are described in U.S. Pat. Nos. 8,013,780 and 5,949,331 and/or U.S. publication No. US-2010-0245066 and/or International Publication No. WO 2011/090484, which are hereby incorporated herein by reference in their entireties.
The present invention provides a driver assistance system or sensing system for a vehicle that utilizes a sensor module or system disposed at the vehicle and comprising at least one radar sensor disposed at the vehicle and having a field of sensing exterior of the vehicle. The at least one radar sensor comprises multiple Tx (transmitters) and Rx (receivers) on an antenna array, so as to provide high definition, fine resolution in azimuth and/or elevation to determine high definition Radar Reflection Responses for objects detected by the system. The system includes a control, where outputs of the at least one radar sensor are communicated to the control, and where the control, responsive to the outputs of the at least one radar sensor, detects the presence of one or more objects exterior the vehicle and within the field of sensing of at least one of the at least one radar sensor.
The sensing system may determine object edges to determine that the detected object is another vehicle and to determine the oblique angle (or skewness) of the other vehicle present in the field of sensing relative to the motion of the source or equipped vehicle (equipped with the sensing system and sensor(s) of the present invention). Successive scanning cycles may be performed to establish vehicle level inputs, the location in range and relative lane position of the detected other vehicle. Comparison to the known lane locations determines the oblique angle (or skewness) of the detected vehicle relative to the lane traveled by the equipped vehicle, such that the system can preemptively anticipate lane change, cut-in or merge intent of the other vehicle.
The system may be operable (via a rearward sensing radar sensor of the vehicle) to attribute classified edges to a trailer being towed by the equipped vehicle. The edge position and trailer angle may be provided to vehicle systems supporting trailer angle detection. The motion of the trailer is analyzed using mathematical methods to determine the severity of trailer sway relative to the towing/equipped vehicle. Control methods may be used (responsive to the determined trailer sway frequency and/or amplitude) to provide active dampening of trailer sway.
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 sensing system, such as a driver assist system, object detection system, parking assist system and/or alert system, operates to capture sensing data exterior of the vehicle and may process the captured data to detect objects or other vehicles at or near the equipped vehicle and in the predicted path of the equipped vehicle, such as to assist a driver of the equipped vehicle in maneuvering the vehicle in a forward or rearward direction or to assist the driver in parking the vehicle in a parking space. The system includes a processor that is operable to receive sensing data from one or more sensors and to provide an output to a control that, responsive to the output, generates an alert or controls an accessory or system of the vehicle, or highlights or overlays an alert on a display screen (that may be displaying video images captured by a single rearward viewing camera or multiple cameras providing forward, side or 360 degree surround views of the area surrounding the vehicle during a reversing or low speed maneuver of the vehicle).
Referring now to the drawings and the illustrative embodiments depicted therein, a vehicle 10 includes an driver assistance system or sensing system 12 that includes at least one radar sensor unit, such as a forward facing radar sensor unit 14 (and the system may optionally include multiple exterior facing sensors, such as cameras or other sensors, such as a rearward facing sensor at the rear of the vehicle, and a sideward/rearward facing sensor at respective sides of the vehicle), which sense regions exterior of the vehicle. The sensing system 12 includes a control or electronic control unit (ECU) or processor that is operable to process data captured by the sensor or sensors and may detect objects or the like. The data transfer or signal communication from the sensor to the ECU may comprise any suitable data or communication link, such as a vehicle network bus or the like of the equipped vehicle.
Some automotive radars use MIMO (Multiple Input Multiple Output) techniques to create an effective virtual antenna aperture, which is significantly larger than the real antenna aperture, and delivers much better angular resolution than conventional radars, such as, for example, conventional scanning radars.
In Advanced Driving Assistance Systems, the resolution of radar and machine vision systems have been limited. Typically, radar information has been limited to range, and velocity information with instability in the precise location of the edges of the vehicle, while vision systems have been able to assess width of objects and approximate range based on size of the object in the image. Anticipating rapid changes in intended path of travel for other vehicles, such as in situations such as cut in (of the other vehicle into the lane being traveled by the equipped vehicle and in front of the equipped vehicle), are difficult to recognize quickly. The radar sensors used typically have been limited to provide only track vector and velocity information, and have been unable to rapidly detect or confirm changes in the intended path of vehicles. Problems such as cut in, merging, lane drift, and avoidance maneuvers occur in the near field, where reaction timing is critical in maximizing the reduction of energy of impact, should an accident or near accident occur between the equipped vehicle and the cutting in or merging vehicle.
Similarly, problems such as offset collisions require precise means for location of the corners of vehicles or obstacles, so that systems can have sufficiently early detection to prevent or minimize the impact of collisions. Oblique angle collision avoidance (NCAP Oblique Angle Collision Avoidance) and small offset barrier tests (IIHS Small Offset Barrier), such as shown in
The sensing system of the present invention comprises High Definition (HD) radar sensor(s) positioned at a vehicle to provide range, velocity, and angular information in horizontal and/or vertical fields of view (FOV). The radar sensor(s) include transmitters that transmit radio waves or signals and receivers that receive the transmitted signals as reflected off of objects in the field of sensing of the sensor(s). Use of sensors with high angular and range resolution distinguishes multiple radar reflection responses from the surfaces of the detected other vehicle. With high definition in azimuth and/or elevation, multiple reflections are received from each surface of the detected vehicle. Reflections are processed with data analysis software (SW) of the radar unit(s) or a central processing location to associate the multiple reflections to a single object. This set of reflections is analyzed using mathematical methods to determine the best fit determination of the vehicle edge. In combination with successive scanning cycles, vehicle level inputs, the location in range, and the relative lane position are established for the vehicle. Comparison to the known lane locations, available from a machine vision system, may be used as an input to determine the oblique angle (or skewness) of the detected vehicle relative to the lane being traveled by the equipped vehicle, preemptively anticipating the lane change intent of the detected vehicle. The sensing system is capable of providing at least one driving assist system function including, for example, (i) automated parking, (ii) blind spot detection, (iii) cross traffic alert, (iv) lane change assist, (v) lane merge assist, (vi) automatic emergency braking, (vii) pedestrian detection, (viii) turn assist, (ix) terrain management, (x) collision mitigation and/or (xi) intersection collision mitigation.
Similarly, for oncoming or intersecting vehicle paths, the oblique angle determination is computed, permitting the determination probability for a potential of collision and a predicted point of contact. Responsive to such determinations, the system may activate collision avoidance measures, including braking of the equipped vehicle, steering of the equipped vehicle and/or acceleration of the equipped vehicle, to mitigate the effects of the potential or likely or imminent collision.
In accordance with the present invention, and such as shown in
During vehicle overtaking (such as shown in
As shown in
Onboard the source vehicle or equipped vehicle 38, the driver intent path or semi-autonomous or fully autonomous expected vehicle path 52 can be determined and/or controlled. Provided the information gathered from environment mapping, an optimized path plan for the equipped vehicle can be established to avoid a potential collision anticipated based on the detected other vehicle's expected path and position. Using these inputs, a collision mitigation strategy involving driver warnings, steering, braking, and/or acceleration of the equipped vehicle may be implemented. Where a collision is imminent and unavoidable, the system may determine an optimized collision scenario to provide maximum protection to drivers and passengers of both of the vehicles.
Additionally, the ability to detect minimal changes in the oblique angle of adjacent vehicle or trailers, offers the potential for features designed to enhance the driving experience.
For scenarios where the equipped vehicle is towing a trailer, the determination of oblique angle and the measure of the periodic swaying motion of the trailer can be determined based on changes to the oblique angle (of the longitudinal axis of the trailer relative to the longitudinal axis of the vehicle). During towing by a source vehicle or equipped vehicle (equipped with a rearward sensing sensor and system of the present invention), swaying of the trailer is observable (via processing sensor data captured by one or more rearward sensing radar sensors) with SW designed to extract the maximum, minimum, frequency and variance of the periodic motion. Controls to manage trailer sway, including active sway management, are envisioned to suppress the negative NVH (Noise, Vibration, and Harshness) and improve vehicle handling and dynamics.
In such trailering conditions, sensors oriented to the rear and sides of the vehicle would have visibility to the front and sides of a trailer, such as a tractor trailer combination, fifth wheel or traditional trailer being towed by the equipped vehicle (
Therefore, the present invention provides a vehicle sensing system having a radar sensor that comprises multiple Tx (transmitters) and Rx (receivers) on an antenna array, so as to provide high definition, fine resolution in azimuth and/or elevation, to determine high definition Radar Reflection Responses for objects detected by the system. The high definition Radar Reflections (range, azimuth, velocity, magnitude, and/or the like) are evaluated by data analysis SW methods to establish surface responses for objects in the device(s) field of view. The set of reflections is analyzed using mathematical methods, determining the best fit determination of the object edges, and classification of stationary, vehicular or pedestrian based on motion factors. The set of reflections that are analyzed and classified as stationary are aggregated into a high definition environmental map.
The object edges establish the oblique angle (or skewness) of another vehicle observed in the sensor's field of view relative to the motion of the source or equipped vehicle. Successive scanning cycles are performed to establish vehicle level inputs, the location in range and relative lane position. Comparison to the known lane locations, available from a machine vision system used as an input, determines the oblique angle (or skewness) of the detected vehicle relative to the lane traveled by the equipped vehicle, preemptively anticipating lane change, cut-in or merge intent.
The sensing system may include a machine vision system (comprising at least one exterior viewing camera disposed at the vehicle and an image processor for processing image data captured by the at least one camera), where information is shared between the stereo radar and the machine vision system.
The system may include two or more individual radars, having individual or multiple Tx (transmitters) and Rx (receivers) on an antenna array, spaced at a known separation (x, y, z) and aligned within a known attitude (pitch, roll, yaw), where information is shared between individual radars operating in stereo, to determine high definition Radar Reflection Responses for objects detected by the system. The high definition Radar Reflections (range, azimuth, velocity, magnitude, and/or the like.) are evaluated by data analysis SW methods to establish surface responses for objects in the device(s) field of view. The set of reflections is analyzed using mathematical methods determining the best fit determination of the object edges, and classification of stationary, vehicular or pedestrian based on motion factors. The set of reflections analyzed and classified as stationary are aggregated into a high definition environmental map. The object edges establish the oblique angle (or skewness) of the vehicle observed in the field of view relative to the motion of the equipped vehicle. Successive scanning cycles, vehicle level inputs, the location in range, relative lane position are established for the vehicle. Comparison to the known lane locations, such as may be available from a machine vision system of the vehicle used as an input, determines the oblique angle (or skewness) of the detected other vehicle relative to the lane, preemptively anticipating lane change, cut-in or merge intent of the other vehicle at or near or in front of the equipped vehicle.
The system may include a machine vision system, where information is shared between the stereo radar and the machine vision system. The system may utilize environment mapping and/or vehicle oblique angles and path information to implement closed loop motion control (steering, braking, etc.) to avoid collisions or mitigate their impact.
The system may be operable to attribute classified edges to a trailer being towed by the equipped vehicle. The edge position and trailer angle are provided to vehicle systems supporting trailer angle detection. The motion of the trailer is analyzed using mathematical methods, to determine the severity of trailer sway relative to the towing/equipped vehicle. Control methods may be used (responsive to the determined trailer sway frequency and/or amplitude) to provide active dampening of trailer sway.
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; 6,825,455; 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 No. WO 2011/090484 and/or U.S. Publication Nos. US-2017-0222311 and/or US-2010-0245066, and/or U.S. patent applications Ser. No. 15/685,123, filed Aug. 24, 2017, and published on Mar. 1, 2018 as U.S. Publication No. US-2018-0059236, Ser. No. 15/675,919, filed Aug. 14, 2017, now U.S. Pat. No. Ser. No. 15/647,339, filed Jul. 12, 2017, now U.S. Pat. No. 10,239,446, Ser. No. 15/619,627, filed Jun. 12, 2017, now U.S. Pat. No. 10,768,298, Ser. No. 15/584,265, filed May 2, 2017, now U.S. Pat. No. 10,534,081, Ser. No. 15/467,247, filed Mar. 23, 2017, now U.S. Pat. No. 10,571,562, Ser. No. 15/446,220, filed Mar. 1, 2017, and published on Sep. 7, 2017 as U.S. Publication No. US-2017-0254873, and/or Ser. No. 15/675,919, filed Aug. 14, 2017, now U.S. Pat. No. 10,641,867, and/or International PCT Application No. PCT/162017/054120, filed Jul. 7, 2017, and published on Jan. 11, 2018 as International Publication No. WO 2018007995, and/or U.S. provisional application Ser. No. 62/383,791, filed Sep. 6, 2016, which are hereby incorporated herein by reference in their entireties.
The system may utilize aspects of the trailering or trailer angle detection systems described in U.S. Pat. Nos. 9,085,261 and/or 6,690,268, and/or U.S. Publication Nos. US-2017-0217372; US-2017-0050672; US-2015-0217693; US-2014-0160276; US-2014-0085472 and/or US-2015-0002670, and/or U.S. patent application Ser. No. 15/446,220, filed Mar. 1, 2017, and published on Sep. 7, 2017 as U.S. Publication No. US-2017-0254873, and/or U.S. provisional application Ser. No. 62/466,449, filed Mar. 3, 2017, 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 is a continuation of U.S. patent application Ser. No. 16/949,813, filed Nov. 16, 2020, now U.S. Pat. No. 11,597,378, which is a continuation of U.S. patent application Ser. No. 15/695,378, filed Sep. 5, 2017, now U.S. Pat. No. 10,836,376, which claims the filing benefits of U.S. provisional application Ser. No. 62/383,790, filed Sep. 6, 2016, which is hereby incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5949331 | Schofield et al. | Sep 1999 | A |
6587186 | Bamji et al. | Jul 2003 | B2 |
6674895 | Rafii et al. | Jan 2004 | B2 |
6678039 | Charbon | Jan 2004 | B2 |
6690268 | Schofield et al. | Feb 2004 | B2 |
6690354 | Sze | Feb 2004 | B2 |
6710770 | Tomasi et al. | Mar 2004 | B2 |
6825455 | Schwarte | Nov 2004 | B1 |
6876775 | Torunoglu | Apr 2005 | B2 |
6906793 | Bamji et al. | Jun 2005 | B2 |
6919549 | Bamji et al. | Jul 2005 | B2 |
7053357 | Schwarte | May 2006 | B2 |
7157685 | Bamji et al. | Jan 2007 | B2 |
7176438 | Bamji et al. | Feb 2007 | B2 |
7203356 | Gokturk et al. | Apr 2007 | B2 |
7212663 | Tomasi | May 2007 | B2 |
7283213 | O'Connor et al. | Oct 2007 | B2 |
7310431 | Gokturk et al. | Dec 2007 | B2 |
7321111 | Bamji et al. | Jan 2008 | B2 |
7340077 | Gokturk et al. | Mar 2008 | B2 |
7352454 | Bamji et al. | Apr 2008 | B2 |
7375803 | Bamji | May 2008 | B1 |
7379100 | Gokturk et al. | May 2008 | B2 |
7379163 | Rafii et al. | May 2008 | B2 |
7405812 | Bamji | Jul 2008 | B1 |
7408627 | Bamji et al. | Aug 2008 | B2 |
8013780 | Lynam | Sep 2011 | B2 |
8027029 | Lu et al. | Sep 2011 | B2 |
9036026 | Dellantoni et al. | May 2015 | B2 |
9085261 | Lu et al. | Jul 2015 | B2 |
9146898 | Ihlenburg et al. | Sep 2015 | B2 |
9575160 | Davis et al. | Feb 2017 | B1 |
9599702 | Bordes et al. | Mar 2017 | B1 |
9689967 | Stark et al. | Jun 2017 | B1 |
9739881 | Pavek et al. | Aug 2017 | B1 |
9753121 | Davis et al. | Sep 2017 | B1 |
10836376 | Wodrich et al. | Nov 2020 | B2 |
11597378 | Wodrich et al. | Mar 2023 | B2 |
20100245066 | Sarioglu et al. | Sep 2010 | A1 |
20140085472 | Lu et al. | Mar 2014 | A1 |
20140160276 | Pliefke et al. | Jun 2014 | A1 |
20150002670 | Bajpai | Jan 2015 | A1 |
20150217693 | Pliefke et al. | Aug 2015 | A1 |
20170050672 | Gieseke et al. | Feb 2017 | A1 |
20170080940 | Ito | Mar 2017 | A1 |
20170217372 | Lu et al. | Aug 2017 | A1 |
20170222311 | Hess et al. | Aug 2017 | A1 |
20170254873 | Koravadi | Sep 2017 | A1 |
20170276788 | Wodrich | Sep 2017 | A1 |
20170315231 | Wodrich | Nov 2017 | A1 |
20170356994 | Wodrich et al. | Dec 2017 | A1 |
20180015875 | May et al. | Jan 2018 | A1 |
20180045812 | Hess | Feb 2018 | A1 |
20180059236 | Wodrich et al. | Mar 2018 | A1 |
20180067194 | Wodrich et al. | Mar 2018 | A1 |
20180068447 | Prasad | Mar 2018 | A1 |
20180253608 | Diessner et al. | Sep 2018 | A1 |
20190225266 | Enomoto et al. | Jul 2019 | A1 |
Number | Date | Country |
---|---|---|
2018007995 | Jan 2018 | WO |
Number | Date | Country | |
---|---|---|---|
20230202460 A1 | Jun 2023 | US |
Number | Date | Country | |
---|---|---|---|
62383790 | Sep 2016 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 16949813 | Nov 2020 | US |
Child | 18178701 | US | |
Parent | 15695378 | Sep 2017 | US |
Child | 16949813 | US |