Method and system for providing driver assistance in a vehicle

Abstract

Methods and systems for providing driving assistance in a vehicle. In one embodiment, a method comprises: determining curvature data associated with a roadway in front of the vehicle by a processor; determining velocity data based on the curvature data, steering data of the vehicle, and set speed data associated with a semi-autonomous control system of the vehicle by the processor; and generating control commands for the semi-autonomous control system by the processor to steer the vehicle to a speed other than a set speed based on the set speed data.

Description

The technical field generally relates to systems and methods for providing cruise control by an autonomous or semi-autonomous driving system based on road preview.Some semi-autonomous driving functions, such as adaptive cruise control, enable control of the speed of the vehicle to follow an intended path or lane based on a set control speed. In some cases, e.g., on curved roads, when a vehicle is performing a cornering maneuver, the semi-autonomous driving function does not adjust the set regulation speed and the driver needs to intervene and assist in operating the vehicle. Optimal cornering requires vehicle deceleration when entering the curve and acceleration at and after the apex of the cornering maneuver.DE 10 2022 102 101 A1 describes a vehicle, wherein a torque is commanded to the vehicle.DE 10 2009 034 931 A1 describes a vehicle speed control method.DE 10 2011 102 435 A1 describes a longitudinal driver assistance system of a motor vehicle.DE 10 2016 107 938 A1 describes a predictive vehicle speed control system.DE 11 2015 005 515 T5 describes a control device for autonomous driving.DE 10 2019 102 944 A1 describes a method for controlling an autonomous vehicle.DE 10 2008 025 174 B4 describes a cruise control system for a vehicle.It may be considered an object to provide improved cruise control strategies, methods, and systems for improved semi-autonomous control of the vehicle without driver assistance during such a turning maneuver.The invention relates to a method according to claim 1 and a system according to claim 10.Vehicles including, methods, and systems for providing driving assistance are presented herein. According to the invention, a method comprises: determining, by a processor, curvature data associated with a roadway in front of the vehicle; determining, by the processor, speed data based on the curvature data, steering data of the vehicle, and set speed data associated with a semi-autonomous control system of the vehicle; and generating, by the processor, control commands for the semi-autonomous control system to control the vehicle to a speed different than a set speed of the set speed data based on the speed data.In various embodiments, determining the curvature data is based on image data received from an image sensor of the vehicle.In various embodiments, determining the curvature data is based on map data and / or location data received from a global positioning system sensor.In various embodiments, determining the curvature data includes determining a radius of a curve on the roadway in front of the vehicle, wherein determining the speed data is based on the radius.In various embodiments, the method includes determining a target lateral acceleration based on the radius of the curve on the roadway in front of the vehicle and the vehicle speed, and wherein the determining of the speed data is based on the target lateral acceleration.In various embodiments, the steering data includes a steering angle and a steering speed.In various embodiments, when the steering angle is greater than a threshold and the set speed data is above a threshold, the method includes where the speed data is based on a target lateral acceleration.In various embodiments, when the steering angle remains greater than the threshold and the adjusted speed data remains above the threshold, the method includes where the speed data is based on an updated target lateral acceleration.In various embodiments, when the steering angle is less than the threshold and the steering speed has changed to the opposite of an initial steering speed and the radius of a curve on the roadway in front of the vehicle increases, the method includes where the speed data is based on an acceleration profile and the set speed data.According to the invention, the determination of the speed data is based on the weather conditions which apply for the roadway in front of the vehicle and / or on a tire pressure and / or a fuel level of the vehicle.According to the invention, a system includes: a controller including non-transitory computer readable media and configured to, by a processor: determine curvature data associated with a roadway in front of the vehicle; determine speed data based on the curvature data, steering data of the vehicle, and set speed data associated with a semi-autonomous control system of the vehicle; and generate control commands for the semi-autonomous control system to control the vehicle to a speed different than a set speed of the set speed data based on the speed data.In various embodiments, the controller is configured to determine the curvature data based on image data received from an image sensor of the vehicle.In various embodiments, the controller is configured to determine the curvature data based on map data and / or location data received from a global positioning system sensor.In various embodiments, the controller is configured to determine the curvature data by determining the radius of a curve on the roadway in front of the vehicle and determine the speed data based on the radius.In various embodiments, the controller is configured to determine a target lateral acceleration based on the radius of the curve on the roadway in front of the vehicle and the vehicle speed, and determine the speed data based on the target lateral acceleration.In various embodiments, the steering data includes a steering angle and a steering speed.In various embodiments, the controller is configured to: when the steering angle is greater than a threshold and the set speed data is greater than a threshold, determine the speed data based on a target lateral acceleration; when the steering angle remains greater than the threshold and the set speed data remains greater than the threshold, determine the speed data based on an updated target lateral acceleration; and when the steering angle is less than the threshold and the steering speed has changed to the opposite of an initial steering speed and a radius of a curve on the roadway in front of the vehicle increases, determine the speed data based on an acceleration profile and the set speed data.According to the invention, the controller is configured to determine the speed data based on at least one of a weather condition associated with the roadway in front of the vehicle, a tire pressure of the vehicle, and a fuel level of the vehicle.For example, a vehicle includes: a sensor system configured to sense the environment of the vehicle; a semi-autonomous control system; and a controller to implement a driver assistance system, the controller configured to: determine, by a processor, curvature data associated with a roadway in front of the vehicle based on sensor data from the sensor system; determine, by the processor, speed data based on the curvature data, steering data of the vehicle, and set speed data associated with the semi-autonomous control system; and generate, by the processor, control commands for the semi-autonomous control system to control the vehicle to a speed other than a set speed of the set speed data based on the speed data.The exemplary embodiments will be described below in conjunction with the following drawings, wherein like reference numerals designate like elements, and wherein: FIG. 1 is a block diagram illustrating an example vehicle with a cruise control system according to various embodiments; FIG. 2 is an illustration of areas associated with a curved roadway, in accordance with various embodiments; and FIG. 3 is a dataflow diagram illustrating features of the vehicle cruise control system in accordance with various embodiments; and FIG. 4 is a process flow diagram illustrating an example method for the cruise control system in accordance with various embodiments.As used herein, the term "module" refers to any hardware, software, firmware, electronic control component, processing logic, and / or processor device, alone or in any combination, including, but not limited to: application specific integrated circuits (ASIC), a field programmable gate array (FPGA), an electronic circuit, a processor (shared, dedicated, or group), and memory that executes one or more software or firmware programs, combinatorial logic circuitry, and / or other suitable components that provide the described functionality.Embodiments of the present description may be described herein in terms of functional and / or logical block components and various processing steps. Such block components may be implemented by any number of hardware, software, and / or firmware components configured to perform the specified functions. For example, an embodiment of the present description may use various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, that may perform a variety of functions under the control of one or more microprocessors or other controllers. Moreover, those skilled in the art will recognize that embodiments of the present description may be used in connection with any number of systems, and that the systems described herein are merely exemplary embodiments of the present description.For brevity, conventional techniques associated with signal processing, data transmission, signaling, control, machine learning models, radar, lidar, image analysis, and other functional aspects of the systems (and the individual operating components of the systems) will not be described in detail herein. Moreover, the connection lines depicted in the various figures are intended to represent example functional relationships and / or physical couplings between the various elements. It should be appreciated that many alternative or additional functional relationships or physical connections may be present in an embodiment of the present description.Referring to FIG. 1, a cruise control system, generally designated 100, is connected to a vehicle 10 in accordance with various embodiments. In general, the cruise control system 100 controls the longitudinal speed of the vehicle based on information obtained from previewing the road ahead. In various embodiments, the preview of the road is based on map information, sensor image preview information, steering angle information, and vehicle speed.As shown in FIG. 1, the vehicle 10 generally includes a chassis 12, a body 14, front wheels 16, and rear wheels 18. the body 14 is disposed on the chassis 12 and substantially encloses the components of the vehicle 10. The wheels 16- 18 are each rotatably connected to the chassis 12 near a corner of the body 14.In various embodiments, the vehicle 10 is an autonomous or semi-autonomous vehicle and the cruise control system 100 is integrated with the autonomous or semi-autonomous vehicle 10. The vehicle 10 is, for example, a vehicle that is automatically controlled in some manner (e.g., by a cruise control) to transport passengers or goods from one location to another. The vehicle 10 is shown as a passenger car in the illustrated embodiment, but it should be appreciated that any other vehicle including motor bicycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), watercraft, aircraft, etc., may also be used.As shown, the vehicle 10 generally includes a propulsion system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. The transmission system 22 is configured to transmit power of the propulsion system 20 to the vehicle wheels 16- 18 according to selectable speed ratios. According to various embodiments, the transmission system 22 may include a continuously variable transmission, a continuously variable transmission, or another suitable transmission. The brake system 26 is configured to apply a braking torque to the vehicle wheels 16- 18. The brake system 26 may include friction brakes, brake-by-wire systems, a regenerative brake system such as an electric machine, and / or other suitable brake systems, in various embodiments. The steering system 24 affects the position of the vehicle wheels 16- 18 and, in some cases, includes a steering wheel.The sensor system 28 includes one or more sensing devices 40 a- 40 nthat sense observable conditions of the exterior environment and / or the interior environment of the vehicle 10. The sensing devices 40 a- 40 nmay include, but are not limited to, radars, lidars, global positioning systems, optical cameras, thermal cameras, ultrasonic sensors, and / or other sensors. The sensor system 28 further includes one or more sensing devices 40 a- 40 nthat sense observable conditions of the vehicle 10, such as speed sensors, pressure sensors, temperature sensors, etc.The actuator system 30 includes one or more actuator devices 42 a- 42 nthat control one or more vehicle functions, such as, but not limited to, the propulsion system 20, the transmission system 22, the steering system 24, and the brake system 26. In various embodiments, the vehicle features may also include interior and / or exterior features of the vehicle, such as doors, a trunk, and cabin features such as air, music, lighting, etc. (not numbered).The communication system 36 is configured to wirelessly communicate information to and from other entities 48, such as other vehicles ("V2V" communication), infrastructure ("V2I" communication), remote systems, and / or personal devices (described in more detail with respect to FIG. 2 ). In an exemplary embodiment, communication system 36 is a wireless communication system configured to communicate over a wireless local area network (WLAN) using IEEE 802.11 standards or using cellular data communication. However, additional or alternative communication methods, such as a dedicated short-range communication (DSRC) channel, are also contemplated within the scope of the present description. DSRC channels refer to one or two-sided short to medium range wireless communication channels that have been specially developed for use in automobiles, as well as a number of protocols and standards.The data storage device 32 stores data for use in automatically controlling the vehicle 10. In various embodiments, the defined maps may be predefined by and obtained from a remote system. For example, the defined maps may be compiled by the remote system and transmitted to the vehicle 10 (wirelessly and / or wired) and stored in the data storage device 32. As can be appreciated, the data storage device 32 may be part of the controller 34, separate from the controller 34, or part of the controller 34 and part of a separate system.The controller 34 includes at least one processor 44 and a computer readable storage device or medium 46. the processor 44 may be any custom or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among multiple processors connected to the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, any combination thereof, or generally any device for executing instructions. The computer readable storage devices or media 46 may include volatile and non-volatile memory, such as read only memory (ROM), random access memory (RAM), and keep alive memory (KAM). KAM is a persistent or non-volatile memory that can be used to store various operating variables while the processor 44 is off. The computer readable storage device(s) 46 may / may be implemented using any number of known storage devices, such as programmable read only memory (PROM), electrically EPROM (electrically PROM), EEPROM (electrically erasable PROM), flash memory, or other electrical, magnetic, optical, or combined storage devices capable of storing data, some of which represent executable instructions, used by the controller 34 in controlling the vehicle 10.The instructions may include one or more separate programs, each of which includes an ordered listing of executable instructions for implementing logical functions. When executed by the processor 44, the instructions receive and process signals from the sensor system 28, perform logic, computations, methods, and / or algorithms for automatically controlling the components of the vehicle 10, and generate control signals for the actuator system 30 to automatically control the components of the vehicle 10 based on the logic, computations, methods, and / or algorithms. Although only one controller 34 is shown in FIG. 1, embodiments of the vehicle 10 may include any number of controllers 34 that communicate and cooperate via any suitable communication medium or combination of communication media to process the sensor signals, perform logic, calculations, methods, and / or algorithms, and generate control signals to automatically control features of the vehicle 10.In various embodiments, as discussed in detail below, one or more commands of the controller 34 are included in the cruise control system 100 and, when executed by the processor 44, process sensor data and / or other data to determine road preview data, estimate a target lateral acceleration of the vehicle based on the road preview data, and automatically control the vehicle as it traverses a curve on the roadway to adjust a cruise control setting or control the brake system to cause the vehicle 10 to decelerate and / or accelerate based on the target lateral acceleration and the steering data of the steering system 24.For example, as shown in FIG. 2, when an upcoming roadway 200 on which the vehicle 10 is travelling includes a curve 202 that requires the vehicle 10 to perform a cornering maneuver, the speed of the vehicle 10 in a first region 210 is controlled based on a predicted lateral acceleration associated with the curve 202. The speed of the vehicle 10 is further regulated in a second region 220 based on an updated predicted lateral acceleration associated with the curve 202. The speed of the vehicle 10 is then further controlled in a third area 230 based on an acceleration profile and a set speed of the semi-autonomous or autonomous driving function. As discussed in the example embodiments herein, the regions are defined based on the steering data and an estimated radius of the curve 202.In various embodiments, the cruise control system 100 of FIG. 1 may be integrated with or interface with a semi-autonomous driving system implementing the semi-autonomous or autonomous driving function. For example, as shown in more detail in FIG. 2 and with continued reference to FIG. 1, a dataflow diagram illustrates elements of the cruise control system 100 in accordance with various embodiments. As will be appreciated, various embodiments of the cruise control system 100 according to the present description may include any number of modules embedded in the controller 34 that may be combined and / or further partitioned to implement the systems and methods described herein in a similar manner. Additionally, inputs to the cruise control system 100 may be received from the sensor system 28, determined / modeled by other control modules (not shown) connected to the vehicle 10, and / or by other sub-modules (not shown) within the controller 34 of FIG. 1. In various embodiments, the cruise control system 100 includes a curvature determination module 350, a lateral acceleration determination module 352, a cruise control module 356, and a velocity profile data store 358.In various embodiments, the speed profile data store 358 stores speed profiles defining speeds and rates used for longitudinal control of the vehicle 10 to accelerate or decelerate the vehicle 10. In various embodiments, any number of velocity profiles may be defined. For example, a velocity profile 400 may be defined as a multi-dimensional look-up table based on the radius of curvature and / or associated lateral acceleration, steering data, and / or velocity adjustment values. As can be appreciated, speed profiles may be defined for any number of environmental conditions and / or vehicle conditions that may affect the lateral acceleration of the vehicle 10 along the curve, such as weather conditions, tire pressure, fuel level, etc.In various embodiments, the speed profiles provide as output a speed value for use by the semi-autonomous or autonomous system in controlling the speed of the vehicle 10.Referring back to FIG. 2, in various embodiments, the curvature determination module 350 receives as input sensor data 360 and GPS location and / or map data 362. The sensor data 360 may include, for example, image data from the camera sensor or other sensing device configured to generate an image of the environment of the vehicle 10. The curvature determination module 350 processes the sensor data 360 and the GPS location and / or map data 362 to determine a radius of curvature of the roadway ahead, and generates radius data 354 based thereon.In various embodiments, the curvature determination module 350 determines the curvature based on the type and location of the roadway markings identified in front of the vehicle 10 and / or based on a position of the vehicle 10 relative to a map of the roadway. As can be seen, in various embodiments, other methods for determining the radius of curvature can also be used.In various embodiments, the lateral acceleration determination module 352 receives as input the radius data 364, the speed data 366 of the vehicle, and the sensor data 368 of the vehicle. The vehicle sensor data 368 may include data from vehicle sensors (e.g., rain sensor, ambient temperature sensor, tire pressure sensor, fuel sensor, etc.) that indicate ambient conditions or other conditions associated with the roadway ahead or the vehicle 10. The lateral acceleration determination module 352 determines a lateral acceleration of the vehicle 10 for the predicted radius of the upcoming curve and in consideration of the associated conditions, and generates target lateral acceleration data 370 based thereon.For example, the lateral acceleration determination module 352 determines the target lateral acceleration based on the relationship: where r represents the prospective radius of curvature of the oncoming roadway as seen from the radius data 364, and V2 represents the longitudinal speed (or speed) of the vehicle 10 as provided by the vehicle speed data 366. In various embodiments, the determined lateral acceleration may be compensated for by applying a compensation value determined based on the sensor data 368 of the vehicle. For example, if the vehicle sensor data 368 indicates rain is being sensed, the downward lateral acceleration is corrected to account for a lower coefficient of friction of the roadway. In another example, if the sensor data 368 indicates that the tire pressure is below a recommended value, the lateral acceleration is increased, e.g., due to vehicle roll movements. In yet another example, if sensor data 368 indicates that the fuel level is high, lateral acceleration increases, e.g., due to sloshing occurring with additional fuel.The cruise control module 356 receives as input the target lateral acceleration data 370, the set speed data 372 for control, and the steering data 374. In various embodiments, the adjusted speed data 372 for control includes an adjusted speed determined by the semi-autonomous or autonomous control system (i.e., the cruise control function). In various embodiments, the steering data 374 includes a steering angle and a steering speed of the steering system 24. Based on the inputs, the cruise control module 356 generates a speed control command 376 that is used by the semi-autonomous control system to adjust the adjusted speed of the semi-autonomous feature control to control the speed of the vehicle 10.For example, if the steering angle is greater than a threshold (e.g., three degrees or another value) and the semi-autonomous control is enabled at a set speed greater than a threshold (region 210 of FIG. 2 ), the speed control module 356 generates commands used by the semi-autonomous control system to adjust the set speed of the control such that the target lateral acceleration can be achieved by, for example, obtaining the speed data 378 from the speed profile data store 358 based on the radius data 364, the target lateral acceleration data 370, and / or the steering data 374.In another example, while the steering angle remains greater than the threshold and the semi-autonomous control remains greater than a threshold at a set speed of the control (region 220 in FIG. 2 ), the speed control module 356 generates commands used by the semi-autonomous control system to adjust the set speed of the control such that an updated target lateral acceleration can be achieved, for example, by obtaining the speed data 378 from the speed profile data store 358 based on the radius data 364, the target lateral acceleration data 370, and / or the steering data 374.In another example, the cruise control module 356 generates a cruise control command 376 that is used by the semi-autonomous control system to adjust the adjusted speed of the control by a defined increment or acceleration profile once the steering angle is below the threshold and the steering speed has changed to the opposite of the initial steering speed and the radius increases (region 230 in FIG. 2 ).Referring now to FIG. 4 and with continued reference to FIGS. 1-3, a flowchart illustrates a method 500 that may be performed by the cruise control system 100 of FIGS. 1-4 in accordance with the present description. As will be appreciated in view of the description, the order of operation within the method 500 is not limited to the sequential execution illustrated in FIG. 4, but may be performed in one or more varying orders as applicable and consistent with the present description. In various embodiments, the method 500 may be scheduled to run based on one or more predetermined events and / or may run continuously during operation of the vehicle 10.In one example, method 500 may begin at 505. At 510, it is determined whether the cruise control is active, e.g., by activating an autonomous or semi-autonomous function such as cruise control. If the cruise control is not active at 510, method 500 may continue to monitor when the cruise control is active at 510, or may end at 630.If it is determined at 510 that the cruise control is active, the curvature of the incoming roadway is monitored at 520. For example, a target lateral acceleration associated with the imminent curve radius and other vehicle conditions is determined at 530, as described above. If the radius is above a threshold at 540 (e.g., if the road ahead is quite straight), the method 500 may be ended at 630.If the radius is below a threshold at 540, the steering angle and set speed of the controller are optionally monitored at 550 and 560. For example, if the steering angle is greater than a threshold at 550 and the set speed of control is greater than a threshold at 560, commands are generated to control the longitudinal speed of the vehicle 10 to achieve the calculated target lateral acceleration at or below the target lateral acceleration at 570. Otherwise, if the steering angle is less than the threshold at 550 or the set speed of the controller is less than the threshold at 560, method 500 continues with monitoring the steering angle and the set speed of the controller at 550 and 560.At 580, the target lateral acceleration is determined based on the upcoming radius and the steering data. Once the steering angle falls below the threshold at 590 and the steering speed is changed in the opposite direction at 600, the radius is monitored at 610.If it is determined at 610 that the radius is not increasing, method 500 continues with updating the target lateral acceleration and control of vehicle 10 based thereon at 580. If it is determined at 610 that the radius is increasing, commands are generated to control the speed of the vehicle 10 to increase to the set speed of control by a defined increment or acceleration profile at 620. Thereafter, the method 500 may be ended at 630.

Claims

A method (500) of providing driving assistance in a vehicle (10), comprising: determining, by a processor (44), curvature data associated with a roadway (200) ahead of the vehicle (10); determining, by the processor (44), speed data (378) based on the curvature data, steering data (374) of the vehicle (10), and set speed data (372) associated with a semi-autonomous control system of the vehicle (10); generating, by the processor (44), control commands (376) for the semi-autonomous control system to control the vehicle (10) to a speed other than a set speed of the set speed data (372) based on the speed data (378); and wherein the determining of the speed data (378) is further based on weather conditions applicable to the roadway (200) in front of the vehicle (10) and / or on a tire pressure and / or a fuel level of the vehicle (10).The method (500) of claim 1, wherein the determining of the curvature data is based on image data received from an image sensor of the vehicle (10).The method (500) of claim 1, wherein the determining of the curvature data is based on map data (362) and / or location data received from a global positioning system sensor.The method (500) of claim 1, wherein determining the curvature data comprises determining a radius of a curve (202) on the roadway (200) ahead of the vehicle (10), wherein determining the speed data (378) is based on the radius.The method (500) of claim 4, further comprising determining a target lateral acceleration based on the radius of the curve (202) on the roadway (200) ahead of the vehicle (10) and the vehicle speed, and wherein determining the speed data (378) is based on the target lateral acceleration.The method (500) of claim 1, wherein the steering data (374) comprises a steering angle and a steering speed.The method (500) of claim 6, further comprising the speed data (378) being based on a target lateral acceleration when the steering angle is greater than a threshold and the adjusted speed data (372) is above a threshold.The method (500) of claim 7, further comprising, if the steering angle remains greater than the threshold and the set speed data (372) remains above the threshold, the speed data (378) being based on an updated target lateral acceleration.The method (500) of claim 8, further comprising the speed data (378) being based on an acceleration profile and the adjusted speed data (372) when the steering angle is less than the threshold and the steering speed has changed to the opposite of an initial steering speed and a radius of a curve (202) on the roadway (200) ahead of the vehicle (10) increases.A system in a vehicle (10) for providing driving assistance, comprising: a controller (34) including non-transitory computer readable media (46) and configured to, by a processor (44): determine curvature data for a roadway (200) ahead of the vehicle (10); determine speed data (378) based on the curvature data, steering data (374) of the vehicle (10), and set speed data (372) associated with a semi-autonomous control system of the vehicle (10); generate control commands (376) for the semi-autonomous control system to control the vehicle (10) to a speed other than a set speed of the set speed data (372) based on the speed data (378); and wherein the controller (34) is further configured to determine the speed data (378) based on at least one of a weather condition associated with the roadway (200) in front of the vehicle (10), a tire pressure of the vehicle (10), and a fuel level of the vehicle (10).

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