System and method for estimating vehicle parameters

Abstract

Methods and systems are provided for estimating vehicle parameters of a vehicle. A maximum desired vehicle acceleration and a minimum excitation acceleration in the first direction are determined. The minimum excitation acceleration is associated with generating an estimated vehicle parameter. A first control input is generated for transmission to an Advanced Driver Assistance System (ADAS) to apply a temporary excitation acceleration greater than a minimum excitation acceleration and less than a maximum desired vehicle acceleration. An estimated vehicle parameter is generated using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor. In response to applying the temporary excitation acceleration to the vehicle, vehicle data is generated. The estimated vehicle parameters are transmitted to an ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS.

Description

Technical Field

[0001] The technical field relates generally to vehicles and, more particularly, to systems and methods for estimating vehicle parameters. Background Art

[0002] Default vehicle parameters are usually provided for the vehicle. In many cases, changes in vehicle parameters can change the longitudinal and lateral response of the vehicle, thereby affecting the implementation of various advanced driver assistance system (ADAS) features. Examples of such vehicle parameters include vehicle mass, vehicle moment of inertia I Z and the vehicle's understeer gradient K US Examples of ADAS features that may be affected by changes in vehicle parameters include, but are not limited to, adaptive cruise control (ACC) and super cruise (SC) control.

[0003] Therefore, it is desirable to provide improved methods and systems for estimating vehicle parameters based on applying additional excitations to the vehicle, and updating the vehicle parameters with the estimated vehicle parameters to facilitate the operation of ADAS. Other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background. Summary of the invention

[0004] In various embodiments, a vehicle parameter estimation system for a vehicle includes at least one processor and at least one memory communicatively coupled to the at least one processor. The at least one memory includes instructions that, when executed by the at least one processor, cause the at least one processor to: determine a maximum desired vehicle acceleration in a first direction; determine a minimum excitation acceleration in the first direction, the minimum excitation acceleration being associated with generating estimated vehicle parameters; generate a first control input for transmission to an advanced driver assistance system (ADAS) of the vehicle to apply a temporary excitation acceleration to the vehicle in the first direction that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration; generate estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, the vehicle data being generated in response to applying the temporary excitation acceleration to the vehicle; and transmit the estimated vehicle parameters to the ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS.

[0005] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to determine a maximum expected vehicle acceleration based at least on a maximum safe acceleration in the first direction.

[0006] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to determine a maximum desired vehicle acceleration based at least on a maximum occupant comfort acceleration in a first direction.

[0007] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to generate a first control input for transmission to an ADAS of the vehicle to apply a temporary excitation acceleration to the vehicle in a first direction, the first direction being a longitudinal direction.

[0008] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to generate estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, wherein: the vehicle data is generated in response to applying a temporary excitation acceleration to the vehicle in a longitudinal direction, the vehicle parameter estimation observation model is a vehicle mass estimation observation model, and the estimated vehicle parameters generated by the vehicle parameter estimation observation model are estimated vehicle mass.

[0009] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to generate a first control input for transmission to an ADAS of the vehicle to apply a temporary stimulus acceleration to the vehicle in a first direction, the first direction being a lateral direction.

[0010] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to generate estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, wherein: the vehicle data is generated in response to applying a temporary excitation acceleration to the vehicle in a lateral direction; the vehicle parameter estimation observation model is a vehicle moment of inertia estimation observation model; and the estimated vehicle parameter is an estimated moment of inertia of the vehicle.

[0011] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to receive estimated vehicle parameters generated by a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, wherein: the vehicle data is generated in response to applying a temporary excitation acceleration to the vehicle in a lateral direction; the vehicle parameter estimation observation model is an understeer gradient estimation observation model; and the estimated vehicle parameter is an understeer gradient of the vehicle.

[0012] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to select a vehicle route that enables application of a temporary excitation acceleration to the vehicle in a first direction.

[0013] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to select a vehicle route that includes at least one curved portion so that a temporary excitation acceleration can be applied to the vehicle in a first direction, the first direction being a lateral direction.

[0014] In various embodiments, the at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to select a vehicle route that includes at least one straight section so that a temporary excitation acceleration can be applied to the vehicle in a first direction, the first direction being a longitudinal direction.

[0015] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to determine whether the vehicle route includes a downhill slope; and generate a first control input for transmission to an ADAS of the vehicle to apply a temporary excitation acceleration to the vehicle in a first direction based on the determination, the first direction being a longitudinal direction, and the temporary excitation acceleration being a temporary positive acceleration followed by a temporary negative acceleration.

[0016] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to determine whether the vehicle route includes an uphill slope; and generate a first control input for transmission to an ADAS of the vehicle to apply a temporary excitation acceleration to the vehicle in a first direction based on the determination, the first direction being a longitudinal direction, and the temporary excitation acceleration being a temporary negative acceleration followed by a temporary positive acceleration.

[0017] In various embodiments, at least one memory includes further instructions that, when executed by at least one processor, cause the at least one processor to generate a second control input for transmission to an ADAS of the vehicle to stop applying temporary excitation acceleration to the vehicle in a first direction when it is determined by the vehicle parameter estimation model that the estimated vehicle parameters have converged.

[0018] In various embodiments, a method for estimating vehicle parameters of a vehicle includes: determining a maximum desired vehicle acceleration in a first direction; determining a minimum excitation acceleration in the first direction, the minimum excitation acceleration being associated with generating estimated vehicle parameters; generating a first control input for transmission to an advanced driver assistance system (ADAS) of the vehicle to apply a temporary excitation acceleration to the vehicle in the first direction that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration; generating estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, the vehicle data being generated in response to applying the temporary excitation acceleration to the vehicle; and transmitting the estimated vehicle parameters to the ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS.

[0019] In various embodiments, the method further includes determining a maximum desired vehicle acceleration based at least on the maximum safe acceleration in the first direction.

[0020] In various embodiments, the method further includes determining a maximum desired vehicle acceleration based at least on a maximum occupant comfort acceleration in the first direction.

[0021] In various embodiments, the method further includes generating a first control input for transmission to an ADAS of the vehicle to apply a temporary excitation acceleration to the vehicle in a first direction, the first direction being a longitudinal direction.

[0022] In various embodiments, the method further includes generating a first control input for transmission to an ADAS of the vehicle to apply a temporary excitation acceleration to the vehicle in a first direction, the first direction being a lateral direction.

[0023] In various embodiments, a vehicle includes a vehicle parameter estimation system. The vehicle parameter estimation system includes at least one processor and at least one memory communicatively coupled to the at least one processor. The at least one memory includes instructions that, when executed by the at least one processor, cause the at least one processor to: determine a maximum desired vehicle acceleration in a first direction; determine a minimum excitation acceleration in the first direction, the minimum excitation acceleration being associated with generating estimated vehicle parameters; generate a first control input for transmission to an advanced driver assistance system (ADAS) of the vehicle to apply a temporary excitation acceleration to the vehicle in the first direction that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration; generate estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, the vehicle data being generated in response to applying the temporary excitation acceleration to the vehicle; and transmit the estimated vehicle parameters to the ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Exemplary embodiments will be described below with reference to the following drawings, wherein like reference numerals denote like elements, wherein:

[0025] Figure 1 is a functional block diagram of a vehicle including a vehicle parameter estimation system according to at least one embodiment;

[0026] Figure 2 is a functional block diagram of a vehicle parameter estimation system according to at least one embodiment;

[0027] Figure 3 is a flowchart representation of an exemplary method of estimating a vehicle parameter of a vehicle according to at least one embodiment;

[0028] Figure 4 is a graphical representation of exemplary boundaries associated with determination of temporary excitation acceleration according to at least one embodiment;

[0029] Figure 5 is a graphical representation of an exemplary boundary that does not allow for temporary excitation acceleration to be applied to a vehicle according to at least one embodiment;

[0030] Figure 6 is an exemplary diagram associated with a vehicle parameter estimation system generating an estimated vehicle mass of a vehicle according to at least one embodiment;

[0031] Figure 7 is an exemplary graphical representation associated with generating, by a vehicle parameter estimation system, an estimated vehicle mass of a vehicle on a downhill grade in accordance with at least one embodiment;

[0032] Figure 8 is an exemplary graphical representation associated with generating, by a vehicle parameter estimation system, an estimated vehicle mass of a vehicle on an uphill grade, according to at least one embodiment;

[0033] Fig. 9 is an exemplary graph associated with generating an estimated moment of inertia and / or an estimated understeer gradient of a vehicle by a vehicle parameter estimation system according to at least one embodiment;

[0034] Fig.10 is a flowchart representation of an exemplary method for selecting a vehicle path by a vehicle parameter estimation system to apply a temporary acceleration stimulus to the vehicle according to at least one embodiment; and

[0035] Fig.11 An exemplary graph and histogram associated with two candidate vehicle routes are shown in accordance with at least one embodiment. DETAILED DESCRIPTION

[0036] The following detailed description is merely exemplary in nature and is not intended to limit application and use. In addition, there is no intention to be bound by any express or implied theory presented in the previous technical field, background technology, invention content or the following detailed description. As used herein, the term module refers to an application-specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated or group) and memory that executes one or more software or firmware programs, a combinational logic circuit and / or other suitable components that provide the described functions.

[0037] Embodiments of the present disclosure may be described herein in terms of functional and / or logical block components and various processing steps. It should be understood that such block components may be implemented by any number of hardware, software, and / or firmware components configured to perform a specified function. For example, embodiments of the present disclosure may employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, etc., which may perform various functions under the control of one or more microprocessors or other control devices. In addition, those skilled in the art will appreciate that embodiments of the present disclosure may be practiced in conjunction with any number of systems, and the systems described herein are merely exemplary embodiments of the present disclosure.

[0038] For the sake of brevity, conventional techniques related to other functional aspects of signal processing, data transmission, signaling, control, and systems (and the various operating components of the systems) may not be described in detail herein. In addition, the connecting lines shown in the various figures included herein are intended to represent exemplary functional relationships and / or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in the embodiments of the present disclosure.

[0039] refer to Figure 1 , shows a functional block diagram of a vehicle 10 including a vehicle parameter estimation system 100 according to at least one embodiment. The vehicle 10 generally includes a chassis 12, a body 14, front wheels 16, and rear wheels 18. In the illustrated embodiment, the vehicle 10 is described as a passenger car, but it should be understood that the vehicle parameter estimation system 100 may be included in any other vehicle, including a truck, a sport utility vehicle (SUV), a recreational vehicle (RV), etc.

[0040] In various embodiments, the body 14 is disposed on the chassis 12 and substantially surrounds the components of the vehicle 10. The body 14 and the chassis 12 may together form a frame. The wheels 16-18 are each rotatably coupled to the chassis 12 near a respective corner of the body 14.

[0041] In various embodiments, the vehicle 10 is an autonomous or semi-autonomous vehicle that is automatically controlled to transport passengers and / or cargo from one place to another. For example, in an exemplary embodiment, the vehicle 10 is a so-called Level 2, Level 3, Level 4, or Level 5 automation system. Level 2 automation describes that the vehicle assists the driver in completing various driving tasks under driver supervision. Level 3 automation describes that the vehicle can take over all driving functions in specific situations. All major functions are automated, including braking, steering, and acceleration. At this level, the driver can completely disengage until the vehicle tells the driver not to do so. Level 4 systems indicate "high automation" and refer to driving mode-specific performance of all aspects of dynamic driving tasks by the automated driving system, even if the human driver does not respond appropriately to intervention requests. Level 5 systems indicate "full automation" and refer to full-time performance of all aspects of dynamic driving tasks by the automated driving system under all road and environmental conditions that can be managed by a human driver.

[0042] 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 controller 34 is configured to implement an advanced driver assistance system (ADAS). The propulsion system 20 is configured to generate power to propel the vehicle. In various embodiments, the propulsion system 20 may include an internal combustion engine, a motor such as a traction motor, a fuel cell propulsion system, and / or any other type of propulsion configuration. The transmission system 22 is configured to transmit power from the propulsion system 20 to the wheels 16-18 according to a selectable speed ratio. According to various embodiments, the transmission system 22 may include a stepped automatic transmission, a continuously variable transmission, or other suitable transmissions. The braking system 26 is configured to provide braking torque to the wheels 16-18. In various embodiments, the braking system 26 may include a friction brake, a wire control brake, a regenerative braking system such as an electric motor, and / or other suitable braking systems.

[0043] The steering system 24 is configured to affect the position of the wheels 16. Although described as including a steering wheel and a steering column for purposes of explanation, in some embodiments contemplated within the scope of the present disclosure, the steering system 24 may not include a steering wheel and / or a steering column. The steering system 24 includes a steering column that is coupled to a shaft 50 associated with the front wheels 16 via, for example, a rack and pinion or other mechanism (not shown). Alternatively, the steering system 24 may include a steer-by-wire system that includes an actuator associated with each of the front wheels 16.

[0044] The sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the external environment and / or the internal environment of the vehicle 10. The sensing devices 40a-40n may include, but are not limited to, radar, lidar, global positioning system, optical camera, thermal camera, ultrasonic sensor, and / or other sensors.

[0045] The vehicle dynamics sensors provide vehicle dynamics data, including longitudinal velocity, yaw rate, lateral acceleration, longitudinal acceleration, etc. The vehicle dynamics sensors may include wheel sensors that measure information associated with one or more wheels of the vehicle 10. In one embodiment, the wheel sensors include wheel speed sensors coupled to each of the wheels 16-18 of the vehicle 10. Additionally, the vehicle dynamics sensors may include one or more accelerometers (provided as part of an inertial measurement unit (IMU)) that measure information associated with the acceleration of the vehicle 10. In various embodiments, the accelerometers measure one or more acceleration values ​​of the vehicle 10, including lateral and longitudinal acceleration and yaw rate.

[0046] The actuator system 30 includes one or more actuator devices 42a-42n that control one or more vehicle features, such as, but not limited to, the propulsion system 20, the transmission system 22, the steering system 24, and the braking system 26. In various embodiments, the vehicle features may further include interior and / or exterior vehicle features, such as, but not limited to, doors, trunks, and cabin features such as air, music, lighting, etc. (not numbered).

[0047] The communication system 36 is configured to wirelessly transmit information to and from other entities 48, such as, but not limited to, other vehicles ("V2V" communication), infrastructure ("V2I" communication), remote systems and / or personal devices. In an exemplary embodiment, the communication system 36 is a wireless communication system that is configured to communicate via a wireless local area network (WLAN) using the IEEE 802.11 standard or by using cellular data communications. However, additional or alternative communication methods, such as dedicated short-range communication (DSRC) channels, are also considered within the scope of the present disclosure. A DSRC channel refers to a one-way or two-way short-range to medium-range wireless communication channel designed specifically for automotive applications and a corresponding set of protocols and standards.

[0048] The data storage device 32 stores data used in the ADAS of the vehicle 10. In various embodiments, the data storage device 32 stores a defined map of the navigable environment. In various embodiments, the defined map may be predefined by a remote system and obtained from the remote system. For example, the defined map may be assembled by the remote system and transmitted to the vehicle 10 (wirelessly and / or in a wired manner) and stored in the data storage device 32. It should be understood that 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.

[0049] The controller 34 includes at least one processor 44 and a computer readable storage device or medium 46. The processor 44 can be any custom or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor of several processors associated with 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 device or medium 46 can include volatile and non-volatile storage in, for example, read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is a permanent or non-volatile memory that can be used to store various operating variables when the processor 44 is powered off. The computer readable storage device or medium 46 can be implemented using any of a variety of known memory devices, such as a programmable read-only memory (PROM), an electrical PROM (EPROM), an electrically erasable PROM (EEPROM), flash memory, or any other electrical, magnetic, optical, or combination memory device capable of storing data, some of which represent executable instructions used by the controller 34 in controlling the vehicle 10.

[0050] The instructions may include one or more separate programs, each of which includes an ordered list of executable instructions for implementing logical functions. When executed by the processor 44, the instructions receive and process signals from the sensor system 28, execute logic, calculations, methods and / or algorithms for automatically controlling components of the vehicle 10, and generate control signals for the actuator system 30 to automatically control components of the vehicle 10 based on the logic, calculations, methods and / or algorithms. Although Figure 1 Only one controller 34 is shown, but embodiments of the vehicle 10 may include any number of controllers 34 that communicate via any suitable communication medium or combination of communication mediums and cooperate to process sensor signals, execute logic, calculations, methods and / or algorithms, and generate control signals to automatically control features of the vehicle 10. In various embodiments, the controller(s) 34 are configured to implement ADAS.

[0051] refer to Figure 2 , shows a functional block diagram of a vehicle parameter estimation system 100 according to at least one embodiment. In various embodiments, the vehicle parameter estimation system 100 is a controller 34. The vehicle parameter estimation system 100 includes at least one processor 200 and at least one memory 202. The (multiple) processors 200 are communicatively coupled to the at least one memory 202. The (multiple) processors 200 are programmable devices that include one or more instructions stored in or associated with the at least one memory 202. The at least one memory 202 includes instructions that the (multiple) processors 200 are configured to execute. The at least one memory 202 includes a vehicle route selection module 204, a maximum desired acceleration module 206, a minimum excitation acceleration module 208, a temporary excitation acceleration module 210, and a vehicle parameter estimation module 212.

[0052] The vehicle parameter estimation system 100 is configured to be communicatively coupled to the ADAS 214 and the sensor system 28 of the vehicle 10. The vehicle parameter estimation system 100 may include additional components that facilitate operation of the vehicle parameter estimation system 100. The operation of the vehicle parameter estimation system 100 will be described in more detail below.

[0053] refer to Figure 3 , a flowchart representation of an exemplary method 300 for estimating vehicle parameters of a vehicle 10 according to at least one embodiment is shown. The method 300 will be described with reference to an exemplary implementation of the vehicle parameter estimation system 100. It will be appreciated from the present disclosure that the order of operations within the method 300 is not limited to the following. Figure 3 The embodiments are not performed in the order shown, but may be performed in one or more alternate orders where applicable and in accordance with the present disclosure.

[0054] Vehicle parameters that the ADAS 214 of the vehicle 10 may rely on to facilitate operation of the vehicle 10 include vehicle mass, vehicle moment of inertia I Z and the understeer gradient K of the vehicle 10 US . The vehicle 10 may be initially provided with default vehicle parameters. The vehicle parameters of the vehicle 10 may change over time and / or under different operating conditions. The vehicle parameter estimation system 100 is configured to generate estimated vehicle parameters based on applying a temporary excitation acceleration to the vehicle 10, and transmit the generated estimated vehicle parameters to the ADAS 214, so that the ADAS 214 can use the estimated vehicle parameters to update the vehicle parameters used by the ADAS 214 when implementing one or more ADAS features. Examples of estimated vehicle parameters include, but are not limited to, estimated vehicle mass, estimated moment of inertia I of the vehicle 10, and estimated speed of the vehicle 10. Z and the estimated understeer gradient K of the vehicle 10 US .

[0055] At 302, the vehicle path selection module 204 is configured to select a vehicle path for the vehicle 10 based on the estimated vehicle parameters to be generated by the vehicle parameter estimation system 100. In at least one embodiment, the vehicle path selection module 204 is configured to select a vehicle path that generates a desired stimulus for estimating the vehicle parameter(s). If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the vehicle path selection module 204 is configured to select a vehicle path that includes a straight portion on the vehicle path. If the vehicle parameter estimation system 100 is generating an estimated moment of inertia I Z and / or understeer gradient K US , the vehicle route selection module 204 is configured to select a vehicle route that includes a curved portion on the vehicle route. In various embodiments, the vehicle route selection module 204 is configured to provide the selected vehicle route to the driver of the vehicle 10 via a vehicle output device, such as via a vehicle display, as a suggested vehicle route. In various embodiments, the vehicle route selection module 204 is configured to provide the selected vehicle route to the ADAS 214 of the vehicle 10. Fig.10 and Fig.11 Describe vehicle route selection in more detail.

[0056] At 304, the maximum expected acceleration module 206 is configured to determine the maximum expected acceleration of the vehicle 10 in a particular direction based on the estimated (multiple) vehicle parameters generated by the vehicle parameter estimation system 100. The maximum expected acceleration has different values ​​for different directions. In various embodiments, the maximum expected acceleration in different directions is a predetermined value. In various embodiments, the maximum expected acceleration is based on one or more vehicle states. In various embodiments, the maximum expected acceleration module 206 is configured to adapt the maximum expected acceleration based on one or more vehicle states. Examples of vehicle states include, but are not limited to, the current vehicle speed and the current vehicle load in the longitudinal direction. The longitudinal direction is the direction of travel of the vehicle 10.

[0057] In various embodiments, the maximum desired acceleration is based on the maximum safe acceleration of the vehicle 10 in a particular direction. In various embodiments, the maximum desired acceleration is based on the maximum occupant comfort acceleration of the vehicle 10 in a particular direction. In various embodiments, the maximum desired acceleration is based on the maximum safe acceleration and the maximum occupant comfort acceleration of the vehicle 10 in a particular direction. In various embodiments, the maximum desired acceleration defines the maximum temporary excitation acceleration that can be applied to the vehicle 10 in a particular direction while ensuring vehicle safety and vehicle occupant comfort.

[0058] If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the maximum expected acceleration module 206 is configured to determine the maximum expected acceleration of the vehicle 10 in the longitudinal direction. Z and / or understeer gradient K US , the maximum expected acceleration module 206 is configured to determine the maximum expected acceleration of the vehicle 10 in the lateral direction. The lateral direction is perpendicular to the direction of travel of the vehicle 10.

[0059] At 306, the minimum excitation acceleration module 208 is configured to determine a minimum excitation acceleration of the vehicle 10 in a particular direction based on the estimated vehicle parameters generated by the vehicle parameter estimation system 100. The minimum excitation acceleration of the vehicle 10 has different values ​​for different directions. In various embodiments, the minimum excitation acceleration of the vehicle 10 in different directions is a predetermined value. In various embodiments, the minimum excitation acceleration is based on one or more vehicle states. In various embodiments, the minimum excitation acceleration module 208 is configured to adapt the minimum excitation acceleration based on one or more vehicle states. Examples of vehicle states include, but are not limited to, a current vehicle speed in a longitudinal direction and a current vehicle load. The longitudinal direction is the direction of travel of the vehicle 10. The minimum excitation acceleration is the minimum amount of excitation acceleration required to generate the estimated vehicle parameters of the vehicle 10.

[0060] If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the minimum excitation acceleration module 208 is configured to determine a minimum excitation acceleration of the vehicle 10 in the longitudinal direction. Z and / or understeer gradient K US , the minimum excitation acceleration module 208 is configured to determine a minimum excitation acceleration of the vehicle 10 in the lateral direction.

[0061] At 308, the temporary excitation acceleration module 210 is configured to select a temporary excitation acceleration in a particular direction that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration. If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the temporary excitation acceleration module 210 is configured to select a temporary excitation acceleration in a longitudinal direction of the vehicle 10. The temporary excitation acceleration module 210 is configured to select a temporary excitation acceleration in a longitudinal direction that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration. If the vehicle parameter estimation system 100 is generating an estimated moment of inertia I Z and / or understeer gradient K US, the temporary incentive acceleration module 210 is configured to select a temporary incentive acceleration in the lateral direction of the vehicle 10. The temporary incentive acceleration module 210 is configured to select a temporary incentive acceleration in the lateral direction that is greater than the minimum incentive acceleration and less than the maximum desired vehicle acceleration.

[0062] At 310, the temporary excitation acceleration module 210 is configured to generate a control input for transmission to the ADAS 214 of the vehicle 10 to apply the temporary excitation acceleration in the specified direction. If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the temporary excitation acceleration module 210 is configured to generate a control input for transmission to the ADAS 214 of the vehicle 10 to apply the temporary excitation acceleration in the longitudinal direction. If the vehicle parameter estimation system 100 is generating an estimated moment of inertia I Z and / or understeer gradient K US , the temporary excitation acceleration module 210 is configured to generate a control input for transmission to the ADAS 214 of the vehicle 10 to apply a temporary excitation acceleration in the lateral direction.

[0063] One or more vehicle sensors in the sensor system 28 generate vehicle data in response to applying a temporary excitation acceleration to the vehicle 10. At 312, the vehicle parameter estimation module 212 uses the vehicle parameter estimation observation model to generate estimated vehicle parameters. The vehicle parameter estimation module 212 is configured to receive vehicle data generated by the sensor system 28 in response to applying a temporary excitation acceleration to the vehicle 10. The vehicle parameter estimation module 212 includes one or more vehicle parameter estimation observation models. Each vehicle parameter estimation observation model is constructed for a specific vehicle parameter estimation. The vehicle parameter estimation observation model for a specific vehicle parameter estimation is configured to generate a vehicle parameter estimate based on the received vehicle data associated with the vehicle parameter estimation. In various embodiments, the vehicle parameter estimation module 212 includes a vehicle mass estimation observation model, a vehicle moment of inertia estimation observation model, and an understeer gradient estimation observation model.

[0064] When the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the vehicle mass estimation observation model is configured to receive vehicle data generated by the sensor system 28 in response to applying a temporary excitation acceleration to the vehicle 10 in the longitudinal direction, and generate an estimated vehicle mass. The vehicle mass estimation observation model is configured to determine when the estimated vehicle mass generated by the vehicle mass estimation observation model converges to an estimated value of the estimated vehicle mass, and generate the converged estimated value as the estimated vehicle mass. Applying a temporary excitation acceleration to the vehicle 10 in the longitudinal direction can enable the vehicle mass estimation observation model to increase the accuracy of the estimated vehicle mass and / or increase the speed at which the estimated vehicle mass converges to the estimated value.

[0065] When the vehicle parameter estimation system 100 is generating an estimated moment of inertia I of the vehicle 10 Z When the vehicle moment of inertia estimation observation model is configured to receive vehicle data generated by the sensor system 28 in response to applying a temporary excitation acceleration to the vehicle 10 in the lateral direction, and generate an estimated vehicle moment of inertia I Z The vehicle moment of inertia estimation observation model is configured to determine the estimated moment of inertia I generated by the vehicle moment of inertia estimation observation model. Z When converges to the estimated moment of inertia I Z and generate a converged estimate as the estimated moment of inertia I Z Applying a temporary excitation acceleration to the vehicle 10 in the lateral direction may enable the vehicle moment of inertia estimation observation model to increase the estimated moment of inertia I Z to improve the accuracy and / or increase the estimated moment of inertia I Z How quickly it converges to its estimate.

[0066] When the vehicle parameter estimation system 100 is generating the estimated understeer gradient K US , the understeer gradient estimation observation model is configured to receive vehicle data generated by the sensor system 28 in response to applying a temporary excitation acceleration to the vehicle 10 in the lateral direction, and generate an estimated understeer gradient K US The understeering gradient estimation observation model is configured to determine an estimated understeering gradient K generated by the understeering gradient estimation observation model. US When converges to the estimated understeer gradient K US and generate a converged estimate as the estimated understeer gradient K US Applying a temporary excitation acceleration to the vehicle 10 in the lateral direction may enable the understeer gradient estimation observation model to increase the estimated understeer gradient K US and / or increase the accuracy of the estimated understeer gradient K US How quickly it converges to its estimate.

[0067] At 314, the vehicle parameter estimation module 212 generates a control input for transmission to the ADAS 214 of the vehicle 10 to stop applying the temporary excitation acceleration. The vehicle parameter estimation module 212 generates a control input for transmission to the ADAS 214 of the vehicle 10 to stop applying the temporary excitation acceleration when the estimated vehicle parameters converge to the estimated values. At 316, the vehicle parameter estimation module 212 transmits the estimated vehicle parameters to the ADAS 214 of the vehicle 10. The ADAS 214 updates the estimated vehicle parameters with the received estimated vehicle parameters. The ADAS 214 implements the ADAS features based on the received estimated vehicle parameters.

[0068] refer to Figure 4 , shows a graphical representation of an exemplary boundary associated with determination of a temporary excitation acceleration 400 according to at least one embodiment. The x-axis represents the lateral direction a x The vehicle acceleration on the y-axis represents the longitudinal direction a y 402 represents the maximum desired acceleration based on the maximum safe acceleration and the maximum passenger comfort acceleration of the vehicle 10. Oval 404 represents the minimum excitation acceleration of the vehicle 10. The minimum excitation acceleration is the minimum excitation acceleration measure required by the parameter estimation observation model to generate the relevant estimated vehicle parameters of the vehicle 10. The maximum desired acceleration and the minimum excitation acceleration are based on one or more current vehicle states. An example of a current vehicle state is the current vehicle speed.

[0069] Region 406 represents temporary excitation accelerations that are greater than the minimum excitation acceleration and less than the maximum desired acceleration. The temporary excitation acceleration is selected from region 406. Applying the temporary excitation acceleration selected from region 406 can maximize the convergence of vehicle parameters estimated by the associated vehicle parameter estimation observation model while maintaining vehicle safety and vehicle passenger comfort.

[0070] When the vehicle parameter estimation system 100 is estimating the vehicle mass, a temporary excitation acceleration is applied in the longitudinal direction. Z and / or understeer gradient K US When , a temporary excitation acceleration is applied in the lateral direction.

[0071] refer to Figure 5 , shows a graphical representation of an exemplary boundary that does not allow temporary excitation acceleration to be applied to the vehicle 10 according to at least one embodiment. The x-axis represents the lateral direction a x The vehicle acceleration on the y-axis represents the longitudinal direction a y . Oval 502 represents the maximum desired acceleration based on the maximum safe acceleration and the maximum passenger comfort acceleration of the vehicle 10. Oval 504 represents the minimum excitation acceleration of the vehicle 10. The minimum excitation acceleration is the minimum excitation acceleration measure required for the parameter estimation observation model to generate the associated estimated vehicle parameters of the vehicle 10. The maximum desired acceleration and the minimum excitation acceleration are based on one or more current vehicle states. An example of a current vehicle state is the current vehicle speed. Figure 5 The current speed of vehicle 10 is less than Figure 4The current speed of the vehicle 10 in FIG. 5 . The minimum excitation acceleration (represented by ellipse 504) required for convergence of generating estimated vehicle parameters by the associated vehicle parameter estimation observation model is greater than the maximum desired acceleration (represented by ellipse 502) at the current vehicle speed. Since the minimum excitation acceleration cannot be achieved while maintaining vehicle safety and vehicle occupant comfort, temporary excitation acceleration in the longitudinal direction or the lateral direction cannot be applied to the vehicle 10 to generate convergence of estimated vehicle parameters by the associated vehicle parameter estimation observation model.

[0072] refer to Figure 6 , shows an exemplary graph associated with generating an estimated vehicle mass of a vehicle 10 by a vehicle parameter estimation system 100, according to at least one embodiment. The ADAS 214 of the vehicle 10 was previously provided with a default vehicle mass m0. The vehicle 10 has been connected to a trailer 600, such that the actual vehicle mass m* defined by the combination of the mass of the vehicle 10 and the mass of the trailer 600 has changed. Graph 602 represents the speed of the vehicle 10 as a function of time. Graph 604 represents the generation of the estimated vehicle mass as a function of time.

[0073] The acceleration of the vehicle 10 increases from an initial speed v0 to a second speed v*. Relationship 606 shows the increase in the speed of the vehicle 10 due to the application of the first acceleration to the vehicle 10. Relationship 608 shows that the estimated vehicle mass converges to a first estimated vehicle mass value 610 generated by the vehicle mass estimation observation model based on the application of the first acceleration.

[0074] According to at least one embodiment, relationship 612 shows that the speed of vehicle 10 increases from an initial speed v0 to a second speed v* based on applying a temporary excitation acceleration to vehicle 10. The temporary excitation acceleration generated by vehicle parameter estimation system 100 is greater than the minimum excitation acceleration and less than the maximum desired acceleration. The temporary excitation acceleration is greater than the first acceleration. Relationship 614 shows that the estimated vehicle mass converges to a second estimated vehicle mass value 616, which is generated by the vehicle mass estimation observation model based on the temporary excitation acceleration.

[0075] The second estimated vehicle mass value 616 generated by the vehicle mass estimation observation model due to the application of the temporary excitation acceleration is closer to the actual vehicle mass m* than the first estimated vehicle mass value 610 generated by the vehicle mass estimation observation model due to the application of the first acceleration. The rate at which the vehicle mass converges to the second estimated vehicle mass value 616 is faster than the rate at which the vehicle mass converges to the first estimated vehicle mass value 610. Use of the vehicle parameter estimation system 100 can result in faster and more accurate generation of an estimated vehicle mass of the vehicle 10 by the vehicle mass estimation observation model.

[0076] refer to Figure 7 , shows an exemplary graph associated with the vehicle parameter estimation system 100 generating an estimated vehicle mass of the vehicle 10 on a downhill grade 700, according to at least one embodiment. The ADAS 214 of the vehicle 10 was previously provided with a default vehicle mass. The vehicle 10 has been loaded with a payload, so the actual vehicle mass defined by the combination of the mass of the vehicle 10 and the payload has changed. The graph 702 represents the speed of the vehicle 10 as a function of time.

[0077] According to at least one embodiment, when the vehicle parameter estimation system 100 determines that the vehicle is on a downhill slope 700, the vehicle parameter estimation system 100 generates a control input for transmission to the ADAS 214 of the vehicle 10 to apply a temporary excitation acceleration to the vehicle 10 in the longitudinal direction. The temporary excitation acceleration includes a temporary positive acceleration applied to the vehicle 10 having an initial velocity v0 until the vehicle 10 reaches a temporary velocity v tmp , followed by a temporary negative acceleration until the vehicle 10 returns to the initial velocity v0. Applying the temporary negative excitation acceleration to the vehicle 10 causes the additional longitudinal excitation required by the vehicle mass estimation observation model to generate the estimated vehicle mass.

[0078] refer to Figure 8 , shows an exemplary graph associated with generating an estimated vehicle mass of a vehicle 10 on an uphill grade 800 by a vehicle parameter estimation system 100, according to at least one embodiment. The ADAS 214 of the vehicle 10 was previously provided with a default vehicle mass. The vehicle 10 has been loaded with a payload, and thus the actual vehicle mass defined by the combination of the mass of the vehicle 10 and the payload has changed. Graph 802 represents the speed of the vehicle 10 as a function of time.

[0079] According to at least one embodiment, when the vehicle parameter estimation system 100 determines that the vehicle is on an uphill slope 800, the vehicle parameter estimation system 100 generates a control input for transmission to the ADAS 214 of the vehicle 10 to apply a temporary excitation acceleration to the vehicle 10 in the longitudinal direction. The temporary excitation acceleration includes a temporary negative acceleration applied to the vehicle 10 having an initial velocity v0 until the vehicle 10 descends to the temporary velocity v tmp , followed by a temporary positive acceleration until the vehicle 10 returns to the initial velocity v0. The application of the temporary positive excitation acceleration to the vehicle 10 causes the additional longitudinal excitation required by the vehicle mass estimation observation model to generate the estimated vehicle mass.

[0080] refer to Fig. 9 , showing an estimated moment of inertia I of the vehicle 10 generated by the vehicle parameter estimation system 100 according to at least one embodiment. Z and / or the estimated understeer gradient KUS The ADAS 214 of the vehicle 10 was previously provided with a default moment of inertia I Z and / or default understeer gradient K US The vehicle 10 has been connected to the trailer 900 so that the moment of inertia I defined by the combination of the mass of the vehicle 10 and the mass of the trailer 900 is Z and understeer gradient K US Graph 902 represents the speed of vehicle 10 as a function of time.

[0081] Relationship 904 illustrates the behavior of vehicle 10 without using vehicle parameter estimation system 100. When vehicle 10 enters a curved portion of the road, the acceleration of vehicle 10 decreases as vehicle 10 travels from an initial speed v0 to a first speed v1, and then when vehicle 10 leaves the curved portion of the road, the acceleration of vehicle 10 increases as vehicle 10 travels from the first speed v1 back to the initial speed v0.

[0082] Relationship 906 illustrates the behavior of vehicle 10 using vehicle parameter estimation system 100 according to at least one embodiment. When vehicle 10 enters a curved portion of the road, the acceleration of vehicle 10 decreases as vehicle 10 travels from an initial speed v0 to a second speed v2, and then when vehicle 10 leaves the curved portion of the road, the acceleration of vehicle 10 increases as vehicle 10 travels from the second speed v2 back to the initial speed v0. The second speed v2 is lower than the first speed v1. When vehicle 10 turns along the curved portion of the road at a higher vehicle speed than that illustrated by relationship 904, a temporary excitation acceleration is generated in the lateral direction. The temporary excitation acceleration is applied, causing the vehicle moment of inertia estimation observation model to generate an estimated moment of inertia I Z and / or generating an estimated understeer gradient K from an understeer gradient estimation observation model US Additional lateral excitation required.

[0083] The temporary excitation acceleration generated by the vehicle parameter estimation system 100 is greater than the minimum excitation acceleration and less than the maximum desired acceleration. Use of the vehicle parameter estimation system 100 may result in faster and more accurate generation of the estimated vehicle moment of inertia I Z and / or the estimated understeer gradient K US . In the estimated vehicle moment of inertia I Z and / or the estimated understeer gradient K USUpon convergence, the temporary excitation acceleration for generating the lateral excitation is stopped. In the Super Cruise application, the speed during curve navigation is initially reduced so that the vehicle 10 with the trailer 900 turns at a higher speed on the curved portion of the road, thereby providing additional lateral excitation to generate the estimated understeer gradient K using the associated parameter estimation observation model. US and / or the estimated moment of inertia I Z .

[0084] refer to Fig.10 , a flowchart representation of an exemplary method 1000 for selecting a vehicle path by the vehicle parameter estimation system 100 to apply a temporary acceleration stimulus to the vehicle 10 according to at least one embodiment is shown. The method 1000 will be described with reference to an exemplary implementation of the vehicle parameter estimation system 100. It will be appreciated from the present disclosure that the order of operations within the method 1000 is not limited to the following. Fig.10 The embodiments are not performed in the order shown, but may be performed in one or more alternate orders where applicable and in accordance with the present disclosure.

[0085] At 1002, the vehicle parameter estimation system 100 identifies a candidate vehicle route. In various embodiments, the candidate vehicle route is an available vehicle route from an initial location to a destination location. At 1004, the vehicle parameter estimation system 100 obtains a vehicle speed and a vehicle heading profile. The vehicle state of the vehicle 10 includes the current vehicle speed and the vehicle heading profile. At 1006, the vehicle parameter estimation system 100 identifies estimated vehicle parameters to be generated. Examples of vehicle estimated parameters include estimated vehicle mass, estimated moment of inertia I Z and the estimated understeer gradient K US .

[0086] At 1008, the vehicle parameter estimation system 100 determines a maximum desired vehicle acceleration based on one or more vehicle states. The maximum desired vehicle acceleration defines the maximum temporary excitation acceleration that can be applied to the vehicle 10 in a particular direction while ensuring vehicle safety and vehicle occupant comfort. If the estimated vehicle parameter to be generated is an estimated vehicle mass, the maximum desired vehicle acceleration defines the maximum temporary excitation acceleration that can be applied to the vehicle 10 in the longitudinal direction. If the estimated vehicle parameter to be generated is an estimated moment of inertia I Z and / or the estimated understeer gradient K US , then the maximum desired vehicle acceleration defines the maximum temporary excitation acceleration that can be applied to the vehicle 10 in the lateral direction.

[0087] At 1010, the vehicle parameter estimation system 100 determines a minimum excitation acceleration based on one or more vehicle states. The minimum excitation acceleration is the minimum amount of excitation acceleration required to generate estimated vehicle parameters of the vehicle 10. If the vehicle parameter estimation system 100 is generating an estimated vehicle mass, the vehicle parameter estimation system 100 determines the minimum excitation acceleration of the vehicle 10 in the longitudinal direction. If the vehicle parameter estimation system 100 is generating an estimated moment of inertia I Z and / or the estimated understeer gradient K US , the vehicle parameter estimation system 100 determines the minimum excitation acceleration of the vehicle 10 in the lateral direction.

[0088] At 1012, the vehicle parameter estimation system 100 generates a histogram for each candidate route. At 1014, the vehicle parameter estimation system 100 selects a vehicle route from the candidate vehicle routes that allows the highest temporary incentive acceleration to be applied. The temporary incentive acceleration is greater than the minimum incentive acceleration and less than the maximum desired vehicle acceleration.

[0089] If the estimated vehicle parameter to be generated is the estimated vehicle mass, the vehicle parameter estimation system 100 selects the vehicle path that allows the maximum temporary excitation acceleration to be applied in the longitudinal direction from the candidate vehicle paths. If the estimated vehicle parameter to be generated is the estimated moment of inertia I Z and / or the estimated understeer gradient K US , the vehicle parameter estimation system 100 selects a vehicle route that allows the maximum temporary excitation acceleration amount to be applied in the lateral direction from the candidate vehicle routes.

[0090] refer to Fig.11 , shows exemplary graphs and histograms associated with two candidate vehicle routes A, B according to at least one embodiment. A graph 1102 shows two candidate routes A, B. The vehicle parameter estimation system 100 is generating an estimated vehicle mass. Graph 1104 shows the vehicle speed along each candidate route A, B. Graph 1106 shows the maximum temporary excitation acceleration that can be applied to the vehicle 10 along the two candidate routes A, B.

[0091] Adding a trailer to the vehicle 10 can affect the longitudinal and lateral response of the vehicle 10 and affect the implementation of one or more ADAS features. Examples of these features include, but are not limited to, adaptive cruise control (ACC) and super cruise (SC) control. Generating accurate estimated vehicle parameters can improve the longitudinal and lateral performance of the vehicle 10. The intentional addition of longitudinal and / or lateral temporary excitation accelerations that fall within the boundaries of vehicle safety and vehicle occupant comfort can improve the accuracy of generating estimated vehicle parameters.

[0092] The adjustment of the ACC correction gain can more aggressively follow the speed setpoint. The vehicle driver mode can be temporarily adjusted to increase the responsiveness of the accelerator pedal. Examples of vehicle driver modes include, but are not limited to, comfort (tour) mode and sport mode. The selection of vehicle routes can achieve a greater temporary incentive acceleration amount to generate improved vehicle parameter estimates. For example, a winding city route may be preferred over a highway route to generate an improved estimated moment of inertia I Z and the estimated understeer gradient K US value.

[0093] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that there are a large number of variations. It should also be understood that one or more exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of the present disclosure in any way. On the contrary, the foregoing detailed description will provide a convenient roadmap for those skilled in the art to implement one or more exemplary embodiments. It should be understood that various changes may be made to the functions and arrangements of the elements without departing from the scope of the present disclosure as set forth in the attached claims and their legal equivalents.

Claims

1. A vehicle parameter estimation system for a vehicle, comprising: at least one processor; as well as at least one memory communicatively coupled to the at least one processor, the at least one memory comprising instructions that, when executed by the at least one processor, cause the at least one processor to: determining a maximum expected vehicle acceleration in a first direction; determining a minimum excitation acceleration in the first direction, the minimum excitation acceleration associated with generating an estimated vehicle parameter; generating a first control input for transmission to an advanced driver assistance system (ADAS) of the vehicle to apply a temporary incentive acceleration to the vehicle in the first direction that is greater than the minimum incentive acceleration and less than the maximum desired vehicle acceleration; generating the estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, the vehicle data being generated in response to applying the temporary excitation acceleration to the vehicle; as well as The estimated vehicle parameters are transmitted to the ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS.

2. The system according to claim 1, wherein: The at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to determine the maximum expected vehicle acceleration based at least on a maximum safe acceleration in the first direction.

3. The system according to claim 1, wherein: The at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to determine the maximum desired vehicle acceleration based at least on a maximum occupant comfort acceleration in the first direction.

4. The system according to claim 1, wherein: The at least one memory includes further instructions which, when executed by the at least one processor, cause the at least one processor to generate the first control input for transmission to the ADAS of the vehicle to apply the temporary stimulus acceleration to the vehicle in the first direction, the first direction being a longitudinal direction.

5. The system according to claim 1, wherein: The at least one memory includes further instructions that, when executed by the at least one processor, cause the at least one processor to generate the first control input for transmission to the ADAS of the vehicle to apply the temporary excitation acceleration to the vehicle in the first direction, the first direction being a lateral direction.

6. A method for estimating a vehicle parameter of a vehicle, comprising: determining a maximum expected vehicle acceleration in a first direction; determining a minimum excitation acceleration in the first direction, the minimum excitation acceleration associated with generating an estimated vehicle parameter; generating a first control input for transmission to an advanced driver assistance system (ADAS) of the vehicle to apply a temporary incentive acceleration to the vehicle in the first direction that is greater than the minimum incentive acceleration and less than the maximum desired vehicle acceleration; generating the estimated vehicle parameters using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor, the vehicle data being generated in response to applying the temporary excitation acceleration to the vehicle; as well as The estimated vehicle parameters are transmitted to the ADAS of the vehicle for replacing previous vehicle parameters with the estimated vehicle parameters at the ADAS. 7 . The method of claim 6 , further comprising determining the maximum desired vehicle acceleration based at least on a maximum safe acceleration in the first direction. 8 . The method of claim 6 , further comprising determining the maximum desired vehicle acceleration based at least on a maximum occupant comfort acceleration in the first direction. 9 . The method of claim 6 , further comprising generating the first control input for transmission to the ADAS of the vehicle to apply the temporary excitation acceleration to the vehicle in the first direction, the first direction being a longitudinal direction.

10. The method of claim 6, further comprising generating the first control input for transmission to the ADAS of the vehicle to apply the temporary stimulus acceleration to the vehicle in the first direction, the first direction being a lateral direction.

Images