Device and method including estimation of driver interaction parameters

Abstract

The invention relates to a device (300, 405) associated with a vehicle, the device comprising one or more memories (315) and one or more processors (310) coupled to the one or more memories (315) and configured to cause the device (300, 405) to: (410) obtain data related to an interaction of a driver with the vehicle; (415) estimate one or more driver interaction parameters based on the data related to the interaction of the driver with the vehicle; (420) update one or more tuning parameters associated with an autonomous driving or driving assistance function based on the one or more driver interaction parameters, thereby resulting in one or more updated tuning parameters; and (425) cause the autonomous driving or driving assistance function to be applied at the vehicle in accordance with the one or more updated tuning parameters.

Description

[0001] Cross-reference to related applications

[0002] This patent application claims priority to U.S. Patent Application No. 18 / 511,364, filed November 16, 2023, entitled “ESTIMATION OF DRIVERINTERACTION BASED TUNING PARAMETERS FOR AUTOMATED DRIVING OR DRIVERASSISTANCE”, which is assigned to the assignee of this application. The disclosure of the earlier application is considered part of this patent application and is incorporated herein by reference. Technical Field

[0003] All aspects of this disclosure relate in general to automated and / or driver assistance systems, and for example to the estimation of driver interaction-based tuning parameters for automated or driver assistance systems. Background Technology

[0004] Autonomous driving systems are an emerging technology that allows vehicles to follow pre-programmed routes or operate in response to real-time environmental conditions without human input. Driver assistance systems (such as Advanced Driver Assistance Systems (ADAS)) include technologies that assist drivers of vehicles, such as those used to help drivers avoid collisions and / or accidents or otherwise make driving a vehicle safer and / or more efficient. Autonomous driving systems and / or driver assistance systems (e.g., ADAS) typically use a combination of sensors, cameras, and software algorithms to perceive the environment and make decisions based on that perception. Autonomous driving and / or driver assistance technologies can be designed to create safer, more efficient, and more convenient modes of transportation that reduce the need for human intervention. The development of autonomous driving systems and driver assistance systems is driven by the convergence of factors that enable vehicles to sense and process information from their surrounding environment (e.g., road conditions, traffic, and pedestrians), such as advances in sensor technology, artificial intelligence, and machine learning. Summary of the Invention

[0005] Some aspects described herein relate to a device associated with a vehicle. The device may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured to cause the device to acquire data related to interactions between a driver and the vehicle. The one or more processors may be configured to cause the device to estimate one or more driver interaction parameters based on the data related to the interactions between the driver and the vehicle. The one or more processors may be configured to cause the device to update one or more tuning parameters associated with autonomous driving or driver assistance functions based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters. The one or more processors may be configured to cause the device to apply the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters.

[0006] Some aspects described herein relate to a method performed by a device associated with a vehicle. The method may include obtaining data related to interactions between a driver and the vehicle by the device. The method may include estimating one or more driver interaction parameters by the device based on the data related to the interactions between the driver and the vehicle. The method may include updating one or more tuning parameters associated with an autonomous driving or driver assistance function by the device based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters. The method may include causing the autonomous driving or driver assistance function to be applied at the vehicle according to the one or more updated tuning parameters.

[0007] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions. When executed by one or more processors of a device associated with a vehicle, the set of instructions enables the device to obtain data related to interactions between a driver and the vehicle. When executed by one or more processors of the device, the set of instructions enables the device to estimate one or more driver interaction parameters based on the data related to the interactions between the driver and the vehicle. When executed by one or more processors of the device, the set of instructions enables the device to update one or more tuning parameters associated with an autonomous driving or driver assistance function based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters. When executed by one or more processors of the device, the set of instructions enables the device to apply the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters.

[0008] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for acquiring data related to interactions between a driver and a vehicle. The apparatus may include components for estimating one or more driver interaction parameters based on the data related to the interactions between the driver and the vehicle. The apparatus may include components for updating one or more tuning parameters associated with an autonomous driving or driver assistance function based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters. The apparatus may include components for causing the autonomous driving or driver assistance function to be applied at the vehicle according to the one or more updated tuning parameters.

[0009] The aspects generally include, as described substantially with reference to the accompanying drawings and description and illustrated as shown in the drawings and description, methods, apparatus, systems, computer program products, non-transitory computer-readable media, user equipment, user gear, wireless communication equipment, and / or processing systems.

[0010] The features and technical advantages of the examples according to this disclosure have been summarized rather extensively above in order to better understand the detailed description below. Additional features and advantages will be described below. The disclosed concepts and specific examples can be readily used as the basis for modifying or designing other structures for achieving the same purpose as this disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein (both their organization and manner of operation) and the associated advantages will be better understood from the following description when considered in conjunction with the accompanying drawings. Each figure in the drawings is provided for illustrative and descriptive purposes and not as a definition of limitation of the claims. Attached Figure Description

[0011] To gain a full understanding of the foregoing features of this disclosure, a more specific description of the invention, briefly outlined above, can be obtained by referring to various aspects, some of which are illustrated in the accompanying drawings. However, it should be noted that the drawings illustrate only certain typical aspects of this disclosure and are therefore not to be considered as limiting its scope, as other equally valid aspects are permissible in this description. The same reference numerals in different drawings may identify the same or similar elements.

[0012] Figure 1 This is an illustration of an example environment in which an autonomous vehicle or a vehicle equipped with an advanced driver assistance system (ADAS) can operate according to this disclosure.

[0013] Figure 2 This is an illustration of an example onboard system for an autonomous vehicle or a vehicle equipped with ADAS according to this disclosure.

[0014] Figure 3This is a diagram illustrating example components of a device according to the present disclosure.

[0015] Figures 4A to 4B This is a diagram illustrating an example associated with the estimation of tuning parameters based on driver interaction for autonomous driving or driver assistance.

[0016] Figure 5 This is a flowchart of an example process associated with the estimation of tuning parameters based on driver interaction for autonomous driving or driver assistance, according to this disclosure. Detailed Implementation

[0017] Various aspects of this disclosure are described more fully below with reference to the accompanying drawings. However, this disclosure may be embodied in many different forms and should not be construed as limited to any particular structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be comprehensive and complete, and will fully convey the scope of protection of this disclosure to those skilled in the art. Those skilled in the art will appreciate that the scope of this disclosure is intended to cover any aspect of this disclosure disclosed herein, whether implemented independently or in combination with any other aspect of this disclosure. For example, any number of aspects set forth herein may be used to implement an apparatus or method of practice. Furthermore, the scope of this disclosure is intended to cover such apparatuses or methods implemented using structures, functions, or structures and functions other than or different from the various aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure herein may be embodied by one or more elements of the claims.

[0018] Vehicles may be equipped with automated driving systems and / or advanced driver assistance systems (ADAS), which may include one or more functions associated with automated driving and / or driver assistance. For example, such functions may be automatic or assisted steering functions that control or assist in controlling the lateral movement of the vehicle. In some examples, the function associated with an automated driving or driver assistance system may be a driver-in-the-loop (DIL) function. That is, the vehicle's automated driving system or driver assistance system (e.g., ADAS) may activate functions controlled by a DIL. A DIL is a mechanism in which control of the vehicle is transferred between automatic control by automated driving or driver assistance functions and manual control by the driver, based on whether the driver interacts with the vehicle passively or actively.

[0019] In some examples, automatic or assisted steering functions that control the lateral movement of a vehicle may be controlled by a DIL (Distributed Inertial Assist). In such examples, when the automatic or assisted steering function is active, it provides torque that can be felt by the driver at the steering wheel. The driver should place his / her hands on the steering wheel and allow the torque applied to the steering wheel by the automatic or assisted steering function to guide the steering wheel (and thus control the lateral movement of the vehicle). If the driver wishes to take over the automatic or assisted steering function, the driver may actively steer the steering wheel and move / push it to the desired position. The DIL control mechanism measures the steering wheel torque applied by the driver (and / or other signals / data related to the interaction between the driver and the vehicle) when the automatic or assisted steering function is active, and determines whether the driver is actively steering (e.g., to take over the automatic or assisted steering function) or passively interacting with the steering wheel (e.g., allowing his / her hands to be guided by the movement of the steering wheel caused by the automatic or assisted steering function). When the driver is actively steering, the steering wheel torque applied by the automatic or assisted steering function can be gradually reduced, so that the driver does not have to fight against the automatic or assisted steering function to control the vehicle's steering wheel. In this situation, once the driver stops actively steering, the DIL control mechanism can detect that the driver is passively interacting with the steering wheel and gradually increase the steering wheel torque applied by the automatic or assisted steering function to return control of the vehicle to the automatic or assisted steering function.

[0020] When automatic or assisted steering is active, different drivers may exhibit different behaviors when gripping the steering wheel (e.g., passively interacting with it) or moving the steering wheel (e.g., actively interacting with it). For example, some drivers may place their hands heavily on the steering wheel, while others may only lightly touch or grip it. When automatic or assisted steering is active and the driver is not actively steering, there is a wide range of steering wheel torque that can be applied by different drivers. Similar wide ranges may exist between data associated with different drivers when other types of data related to driver and vehicle interaction are used for DIL control of automated driving or driver assistance functions. Therefore, it is difficult to tune DIL parameters so that DIL is well-suited to all drivers and detects driver interaction early enough for all drivers. Consequently, DIL may be inaccurate for some drivers, leading to false alarms in active driving detection for some drivers and / or delayed active driving detection for some (other) drivers.

[0021] Various aspects involve estimating driver interaction-based tuning parameters for autonomous driving or driver assistance. In some aspects, a device associated with a vehicle can acquire data related to interactions between the driver and the vehicle. In some examples, the device can acquire data related to driver-vehicle interactions via online data collection while the vehicle is being driven. In some other examples, the device can acquire data related to driver-vehicle interactions via a vehicle-driver interaction sequence while the vehicle is stationary (e.g., not being driven). The device can estimate one or more driver interaction parameters based on the data related to driver-vehicle interactions. For example, one or more driver interaction parameters may include or relate to steering wheel torque values, and / or other parameters associated with active steering by the driver of the vehicle and / or passive interactions with the steering wheel of the vehicle by the driver of the vehicle. The device can update one or more tuning parameters associated with autonomous driving or driver assistance functions based on one or more driver interaction parameters. For example, one or more tuning parameters may be DIL tuning parameters. The device enables the application of autonomous driving or driver assistance functions at the vehicle based on one or more updated tuning parameters. For example, control of the vehicle can be transferred between autonomous driving or driver assistance functions and the driver, at least in part, based on detecting passive or active interactions between the driver and the vehicle using one or more updated tuning parameters.

[0022] Specific aspects of the subject matter described in this disclosure can be implemented to achieve one or more of the following potential advantages. In some examples, by estimating one or more driver interaction parameters based on data related to the interaction between the driver and the vehicle, and updating one or more tuning parameters associated with autonomous driving or driver assistance functions, a device associated with a vehicle can utilize vehicle-specific driver tuning parameters to update tuning parameters (e.g., DIL tuning parameters). By causing the autonomous driving or driver assistance function to be applied according to the updated tuning parameters, the function is applied with improved accuracy. For example, using updated tuning parameters to apply a DIL-controlled function can improve accuracy, such as by reducing false alarms in the detection of active interactions between the driver and the vehicle's steering wheel and / or reducing the delay in the detection of active interactions between the driver and the vehicle's steering wheel, compared to tuning parameters that are not updated based on driver interaction data associated with the driver of the vehicle.

[0023] Figure 1 This is a diagram illustrating an example environment 100 in which an autonomous vehicle or a vehicle equipped with ADAS can operate, according to this disclosure. Figure 1As shown, environment 100 may include, for example, a vehicle 110, an onboard system 120 of vehicle 110, a remote device 130, a network node 150, and a network 160. Devices in environment 100 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections. Figure 1 As further shown, environment 100 may include vehicle 110 configured to detect one or more objects 140 (e.g., using onboard system 120).

[0024] In some aspects, vehicle 110 may include any form of transportation capable of carrying one or more human occupants and / or cargo and powered by any suitable energy source. For example, vehicle 110 may include land vehicles (e.g., cars, trucks, vans, or trains), aircraft (e.g., unmanned aerial vehicles), and / or boats. Figure 1 In the illustrated example, vehicle 110 is a land vehicle and is shown as a car. Furthermore, in Figure 1 In the example, vehicle 110 is an autonomous vehicle. For example, an autonomous vehicle (AV) is a vehicle with a processor, programming instructions, and drivetrain components that can be controlled by the processor without a human operator. An autonomous vehicle can be fully autonomous, meaning that for most or all driving conditions and functions, an autonomous vehicle does not require a human operator, or an autonomous vehicle can be semi-autonomous, meaning that under certain conditions or for certain operations a human operator may be required, or a human operator can take over the autonomous driving system and control the autonomous vehicle. In some aspects, an autonomous vehicle (e.g., vehicle 110) may support one or more DIL (Driver In-Service) functions. For example, an autonomous vehicle (e.g., vehicle 110) may support one or more autonomous driving functions controlled by a DIL (e.g., automatic steering and / or other automatic functions). Additionally or alternatively, vehicle 110 may be equipped with ADAS (Advanced Driver Assistance Systems) that support one or more safety functions and / or technologies to help the driver avoid collisions and / or accidents (e.g., adaptive cruise control, lane departure warning, automatic emergency braking) or otherwise make driving vehicle 110 safer and / or more efficient. In some respects, ADAS (e.g., ADAS of vehicle 110) may support one or more DIL functions. For example, ADAS may support one or more autonomous driving or driver assistance functions controlled by DIL (e.g., automatic or assisted steering functions and / or other automatic or assisted functions).

[0025] like Figure 1As shown, vehicle 110 may include an onboard system 120 integrated into and / or coupled thereto. Generally, the onboard system 120 may be used to control vehicle 110, sense information about vehicle 110 and / or the environment in which vehicle 110 operates, detect one or more objects 140 near the vehicle, provide outputs to or receive inputs from the occupants of vehicle 110, and / or communicate with one or more devices (such as another vehicle and / or remote devices 130) located away from vehicle 110. Therefore, as described herein, vehicle 110 may be an ego vehicle, which refers to an active vehicle using autonomous driving technology, ADAS, and / or one or more sensors (e.g., cameras, lidar, and radar) to perceive its surroundings and make decisions related to the trajectory, speed, and / or actions of vehicle 110 on a road. The following is combined with… Figure 2 The onboard system 120 is described in more detail.

[0026] In some aspects, vehicle 110 may travel along a road in a semi-autonomous or autonomous manner. Vehicle 110 may be configured to detect objects 140 in the vicinity of vehicle 110. Object 140 may include, for example, another vehicle (e.g., an autonomous vehicle or a non-autonomous vehicle that requires a human operator for most or all driving conditions and functions), cyclists (e.g., riders of bicycles, e-scooters, or motorcycles), pedestrians, road features (e.g., road boundaries, lane markings, sidewalks, median strips, guardrails, roadblocks, signs, traffic signals, railroad crossings, or bicycle paths) and / or another object that may be on or near the road, such as a tree or an animal. In some aspects, to detect object 140, vehicle 110 may be equipped with a camera-based vision system and / or one or more sensors, such as a lidar system. In some aspects, the camera-based vision system and / or one or more sensors may be included in another system other than vehicle 110 (such as a robot, satellite, and / or traffic lights).

[0027] In some aspects, one or more sensors may provide object detection data, such as information about a detected object 140 (e.g., information about the distance to the object 140, the speed of the object 140, and / or the direction of movement of the object 140), to one or more other components of the onboard system 120. Additionally or alternatively, the vehicle 110 may transmit the object detection data to a remote device 130 (e.g., a server, cloud computing system, and / or database) via a network 160 (e.g., via network node 150). The remote device 130 may be configured to process the object detection data and / or transmit the results of processing the object detection data to the vehicle 110 via the network 160 (e.g., via network node 150). In some examples, the remote device 130 may be a server device.

[0028] In some aspects, network node 150 includes one or more devices configured to receive, generate, store, process, and / or provide information relating to one or more aspects described herein. For example, network node 150 may include a base station (Node B, gNB, and / or 5G Node B (NB), etc.), user equipment (UE), relay equipment, network controller, access point, transmit / receive point (TRP), apparatus, device, computing system, and / or another suitable processing entity configured to perform one or more aspects described herein. For example, in some aspects, network node 150 may include one or more components of a decomposed base station (e.g., a central unit, distributed unit, and / or radio unit) and / or a clustered base station, which one or more components enable onboard system 120 to communicate over network 160 (e.g., invoke or otherwise utilize processing capabilities associated with remote device 130).

[0029] Network 160 includes one or more wired and / or wireless networks. For example, network 160 may include cellular networks (e.g., Long Term Evolution (LTE) networks, Code Division Multiple Access (CDMA) networks, 3G networks, 4G networks, 5G networks, another type of next-generation network, etc.), Public Land Mobile Networks (PLMNs), Local Area Networks (LANs), Wide Area Networks (WANs), Metropolitan Area Networks (MANs), telephone networks (e.g., Public Switched Telephone Networks (PSTN)), private networks, self-organizing networks, intranets, the Internet, fiber-optic networks, cloud computing networks, etc., and / or combinations of these or other types of networks. In some aspects, network 160 enables communication between devices in environment 100.

[0030] In some respects, as described herein, the onboard system 120 or remote device 130 may be configured to: acquire data relating to the interaction between the driver and the vehicle 110; estimate one or more driver interaction parameters based on the data relating to the interaction between the driver and the vehicle 110; update one or more tuning parameters associated with autonomous driving or driver assistance functions based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters; and cause the autonomous driving or driver assistance functions to be applied at the vehicle 110 according to the one or more updated tuning parameters.

[0031] As indicated above, Figure 1 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 1 The examples described are different. Figure 1 The number and arrangement of devices shown are provided as an example. In reality, similar arrangements are possible. Figure 1 The equipment shown is compared to additional equipment, fewer equipment, different equipment, or equipment arranged in a different manner. Furthermore, Figure 1 The two or more devices shown can be implemented within a single device, or Figure 1 The single device shown can be implemented as multiple distributed devices. Additionally or alternatively, Figure 1 The set of devices shown (e.g., one or more devices) can be executed as described by Figure 1 The other set of devices shown performs one or more functions.

[0032] Figure 2 This is a diagram illustrating an example onboard system 200 of an automated driving vehicle or a vehicle equipped with ADAS according to this disclosure. In some aspects, onboard system 200 may correspond to onboard system 120 included in vehicle 110, as described above. Figure 1 As described. Figure 2 As shown, the onboard system 200 may include one or more of the illustrated components 202-256. The onboard system 200 may include, for example, a power subsystem 202, a sensor subsystem 204, a control subsystem 206, and / or an onboard device 208. The components of the onboard system 200 may communicate via a bus such as a Controller Area Network (CAN) bus (e.g., one or more wired and / or wireless connections).

[0033] The power subsystem 202 may be configured to generate mechanical energy for the vehicle 110 to move the vehicle 110. For example, the power subsystem 202 may include an engine that converts fuel into mechanical energy (e.g., via combustion) and / or a motor that converts electrical energy into mechanical energy.

[0034] The sensor subsystem 204 may include one or more sensors configured to detect operating parameters of the vehicle 110 and / or environmental conditions in the environment in which the vehicle 110 operates (e.g., around the vehicle 110). For example, sensor subsystem 204 may include engine temperature sensor 210, battery voltage sensor 212, engine revolutions per minute (RPM) sensor 214, throttle position sensor 216, battery sensor 218 (e.g., for measuring battery current, voltage and / or temperature), motor current sensor 220, motor voltage sensor 222, motor position sensor 224 (e.g., resolver and / or encoder), motion sensor 226 (e.g., accelerometer, gyroscope and / or inertial measurement unit), speed sensor 228, odometer sensor 230, clock 232, positioning sensor 234 (e.g., Global Navigation Satellite System (GNSS) sensor and / or Global Positioning System (GPS) sensor), one or more cameras 236, lidar system 238, one or more other ranging systems 240 (e.g., radar system and / or sonar system) and / or environmental sensor 242 (e.g., precipitation sensor and / or ambient temperature sensor).

[0035] The control subsystem 206 may include one or more controllers configured to control the operation of the vehicle 110. For example, the control subsystem 206 may include a brake controller 244 for controlling the braking of the vehicle 110, a steering controller 246 for controlling the steering and / or direction of the vehicle 110, a throttle controller 248 and / or a speed controller 250 for controlling the speed and / or acceleration of the vehicle 110, a gear controller 252 for controlling the shifting of the vehicle 110, a route selection controller 254 for controlling the navigation and / or route selection of the vehicle 110 (e.g., using map data), and / or an auxiliary equipment controller 256 for controlling one or more auxiliary devices associated with the vehicle 110, such as testing equipment, auxiliary sensors, and / or mobile equipment transported by the vehicle 110.

[0036] Onboard device 208 may be configured to receive sensor data from one or more sensors included in sensor subsystem 204 and / or provide commands to one or more controllers included in control subsystem 206. For example, onboard device 208 may control the operation of vehicle 110 by providing commands to controllers included in control subsystem 206 based on sensor data received from sensors included in sensor subsystem 204. In some aspects, onboard device 208 may be configured to process sensor data to generate commands. Onboard device 208 may include memory, one or more processors, input components, output components, and / or communication components, as described elsewhere herein.

[0037] As an example, onboard device 208 may receive navigation data, such as information associated with a navigation route from the starting point of vehicle 110 to its destination. In some aspects, the navigation data is accessed and / or generated by route selection controller 254. For example, route selection controller 254 may access map data and identify possible routes and / or segments that vehicle 110 can travel to move from the starting point to the destination. In some aspects, route selection controller 254 may identify preferred routes, such as by scoring multiple possible routes, applying one or more route selection techniques (e.g., minimum Euclidean distance, Dijkstra's algorithm, and / or Bellman-Ford algorithm), taking into account traffic data, and / or receiving user route selections. Onboard device 208 may use the navigation data to control the operation of vehicle 110. As the vehicle travels along the route, onboard device 208 may receive sensor data from various sensors in sensor subsystem 204. For example, the positioning sensor 234 can provide geographic location information to the onboard device 208, which can then access a map associated with the geographic location information to determine known fixed features associated with the geographic location that can be used to control the operation of the vehicle 110, such as streets, buildings, stop signs, and / or traffic signals.

[0038] In some aspects, onboard device 208 may receive one or more images captured by one or more cameras 236, analyze one or more images (e.g., to detect object data), and control the operation of vehicle 110 based on the analyzed images (e.g., to avoid detected objects). For example, onboard device 208 may obtain from camera 236 a series of images depicting a reference vehicle traveling along a road segment in front of vehicle 110, and onboard device 208 may analyze the series of images to estimate the size of the reference vehicle and / or the position of the reference vehicle relative to vehicle 110. Onboard device 208 may track the trajectory of the reference vehicle along the road segment in front of vehicle 110 based on the estimated size and / or estimated position of the reference vehicle on the series of images, and may estimate the surface geometry associated with the road segment in front of vehicle 110 based on the tracked trajectory of the reference vehicle. Therefore, the onboard system 208 can generate one or more control signals (e.g., to control the vehicle 110, stay in a designated lane, avoid obstacles, and / or plan a route) based on the estimated surface geometry associated with the road segment in front of the vehicle 110.

[0039] In some aspects, onboard device 208 may receive object data associated with one or more objects detected in the vicinity of vehicle 110, and / or may generate object data based on sensor data. Object data may indicate the presence or absence of an object, the object's location, the distance between the object and vehicle 110, the object's speed, the object's direction of movement, the object's acceleration, the object's trajectory (e.g., direction of travel), the object's shape, the object's size, the area occupied by the object, and / or the object's type (e.g., vehicle, pedestrian, cyclist, stationary object, or moving object). Object data may be detected, for example, by one or more cameras 236 (e.g., as image data), a lidar system 238 (e.g., as lidar data), and / or one or more other ranging systems 240 (e.g., as radar or sonar data). Onboard device 208 may process object data to detect objects near vehicle 110 and / or control the operation of vehicle 110 based on the object data (e.g., to avoid detected objects).

[0040] In some aspects, onboard device 208 can use object data (e.g., current object data) to predict future object data for one or more objects. For example, onboard device 208 can predict the future position of an object, the future distance between the object and vehicle 110, the future speed of the object, the future direction of movement of the object, the future acceleration of the object, and / or the future trajectory of the object (e.g., future direction of travel). For example, if the object is a vehicle and map data indicates that the vehicle is at an intersection, onboard device 208 can predict whether the object will likely travel in a straight line or turn. As another example, if sensor data and / or map data indicate that there are no traffic lights at the intersection, onboard device 208 can predict whether the object will stop before entering the intersection.

[0041] Onboard device 208 can generate motion plans for vehicle 110 based on sensor data, navigation data, and / or object data (e.g., current object data and / or future object data). For example, based on the current position of an object and / or its predicted future position, onboard device 208 can generate motion plans to move vehicle 110 along a surface and avoid collisions with other objects. In some aspects, the motion plan may include the speed, direction, and / or acceleration of vehicle 110 at one or more points in time. Additionally or alternatively, the motion plan may instruct one or more actions regarding detected objects, such as whether to catch up with the object, give way to the object, or overtake the object. Onboard device 208 can generate one or more commands or instructions based on the motion plan and can provide those commands to one or more controllers associated with control subsystem 206 for execution.

[0042] In some aspects, the autonomous driving or driver assistance functions supported by the onboard system 200 may be controlled by the DIL. In such examples, based on whether the interaction between the driver and the vehicle is passive or active, the onboard device 208 may transfer control of the vehicle associated with the autonomous driving or driver assistance function between the onboard system 200 (e.g., control subsystem 206) and the driver of the vehicle. For example, in the case of an automatic or assisted steering function supported by the onboard system 200, the onboard device 208 may, in conjunction with (e.g., based on the steering wheel torque value measured by sensors in the sensor subsystem 204), determine that the driver is actively interacting with the steering wheel (e.g., actively steering) to transfer control from the steering controller 246 (e.g., gradually decreasing the steering wheel torque provided by the steering controller 246). The onboard device 208 may, in conjunction with (e.g., based on the steering wheel torque value measured by sensors in the sensor subsystem 204), determine that the driver is passively interacting with the steering wheel to transfer control to the steering controller 246 (e.g., gradually increasing the steering wheel torque provided by the steering controller 246).

[0043] As indicated above, Figure 2 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 2 The examples described are different. Figure 2 The number and arrangement of components shown are provided as an example. In reality, they can exist in... Figure 2 The components shown are compared to additional components, fewer components, different components, or components arranged in a different manner. Furthermore, Figure 2 The two or more components shown can be implemented within a single component, or Figure 2 The single component shown can be implemented as multiple distributed components. Additionally or alternatively, Figure 2 The component collection shown (e.g., one or more components) can be executed as described by Figure 2 The other set of components shown performs one or more functions. For example, although Figure 2 Some components are primarily associated with land vehicles, but other types of vehicles are also within the scope of this disclosure.

[0044] Figure 3 This is a diagram illustrating example components of device 300 according to the present disclosure. Device 300 may correspond to... Figure 1 The depicted onboard system 120, remote device 130, or network node 150 Figure 2The depicted onboard system 200 or onboard device 208 and / or any other device, system, subsystem, or component described herein. In some aspects, onboard system 120, remote device 130, network node 150, onboard system 200, onboard device 208, and / or other device, system, subsystem, or component described herein may include one or more devices 300 and / or one or more components of device 300. Figure 3 As shown, device 300 may include bus 305, processor 310, memory 315, input component 320, output component 325, communication component 330 and / or estimation component 335.

[0045] Bus 305 may include one or more components enabling wired and / or wireless communication between components of device 300. Bus 305 may connect components such as via operative coupling, communicative coupling, electronic coupling, and / or electrical coupling. Figure 3 Two or more components are coupled together. For example, bus 305 may include electrical connections (e.g., wires, traces, and / or leads) and / or wireless buses. Processor 310 may include a central processing unit, graphics processing unit, microprocessor, controller, microcontroller, digital signal processor, field-programmable gate array, application-specific integrated circuit, and / or another type of processing component. Processor 310 may be implemented in hardware, firmware, or a combination of hardware and software. In some aspects, processor 310 may include one or more processors capable of being programmed to perform one or more operations or processes described elsewhere herein.

[0046] Memory 315 may include volatile memory and / or non-volatile memory. For example, memory 315 may include random access memory (RAM), read-only memory (ROM), hard disk drive, and / or another type of memory (e.g., flash memory, magnetic memory, and / or optical memory). Memory 315 may include internal memory (e.g., RAM, ROM, or hard disk drive) and / or removable memory (e.g., removable via a universal serial bus connection). Memory 315 may be a non-transitory computer-readable medium. Memory 315 may store information related to the operation of device 300, one or more instructions, and / or software (e.g., one or more software applications). In some aspects, memory 315 may include one or more memories, such as those coupled (e.g., communicatively coupled) to one or more processors (e.g., processor 310) via bus 305. The communicative coupling between processor 310 and memory 315 enables processor 310 to read and / or process information stored in memory 315, and / or store information in memory 315.

[0047] Input component 320 enables device 300 to receive input, such as user input and / or sensed input. For example, input component 320 may include a touchscreen, keyboard, keypad, mouse, button, microphone, switch, sensor, GPS sensor, GNSS sensor, accelerometer, gyroscope, and / or actuator. Output component 325 enables device 300 to provide output, such as via a display, speaker, and / or light-emitting diode. Communication component 330 enables device 300 to communicate with other devices via wired and / or wireless connections. For example, communication component 330 may include a receiver, transmitter, transceiver, modem, network interface card, and / or antenna.

[0048] The estimation component 335 may: obtain data related to the interaction between the driver and the vehicle; estimate one or more driver interaction parameters based on the data related to the interaction between the driver and the vehicle; and / or update one or more tuning parameters associated with autonomous driving or driver assistance functions based on one or more driver interaction parameters, thereby generating one or more updated tuning parameters.

[0049] Device 300 may perform one or more operations or procedures described herein. For example, a non-transitory computer-readable medium (e.g., memory 315) may store a set of instructions (e.g., one or more instructions or code) for execution by processor 310. Processor 310 may execute the set of instructions to perform one or more operations or procedures described herein. In some aspects, execution of the set of instructions by one or more processors 310 causes one or more processors 310 and / or device 300 to perform one or more operations or procedures described herein. In some aspects, hardwired circuitry may be used in place of or in combination with instructions to perform one or more operations or procedures described herein. Additionally or alternatively, processor 310 may be configured to perform one or more operations or procedures described herein. Thus, the aspects described herein are not limited to any particular combination of hardware circuitry and software.

[0050] In some aspects, device 300 may include: components for acquiring data related to interactions with a driver and a vehicle; components for estimating one or more driver interaction parameters based on the data related to the interactions with the driver and the vehicle; components for updating one or more tuning parameters associated with autonomous driving or driver assistance functions based on one or more driver interaction parameters, thereby generating one or more updated tuning parameters; and / or components for causing autonomous driving or driver assistance functions to be applied at the vehicle according to one or more updated tuning parameters. In some aspects, the components for device 300 to perform the processes and / or operations described herein may include components combining... Figure 3One or more components of the described device 300, such as bus 305, processor 310, memory 315, input component 320, output component 325, communication component 330, and / or estimation component 335. Additionally or alternatively, components for the device 300 to perform the processes and / or operations described herein may include combinations of... Figure 2 One or more components of the described onboard system 200, such as sensor subsystem 204, control subsystem 206 and / or onboard device 208, etc.

[0051] Figure 3 The number and arrangement of components shown are provided as an example. Device 300 may include components with... Figure 3 The components shown are compared to additional components, fewer components, different components, or components arranged in a different manner. Additionally or alternatively, a set of components of device 300 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of device 300.

[0052] Figures 4A to 4B This is a diagram illustrating example 400 associated with the estimation of tuning parameters based on driver interaction for autonomous driving or driver assistance. Figures 4A to 4B As shown, Example 400 includes a vehicle (e.g., vehicle 110) and vehicle equipment 405. The vehicle may be an autonomous vehicle or a vehicle equipped with ADAS. For example, the vehicle may be equipped with an onboard system (e.g., onboard system 120 and / or onboard system 200) that supports autonomous driving and / or ADAS technologies. Vehicle equipment 405 may be equipment associated with the vehicle. In some aspects, such as Figures 4A to 4B As shown, vehicle equipment 405 can be onboard equipment (e.g., onboard equipment 208) or onboard systems (e.g., onboard systems 120 and / or 200) of a vehicle. In some other aspects, vehicle equipment 405 can be remote equipment associated with a vehicle (e.g., remote equipment 130), such as server equipment communicating with the onboard systems of the vehicle. Therefore, in combination Figure 4A and Figure 4B The described operations may be performed by onboard equipment and / or onboard systems of the vehicle, or by remote equipment outside the vehicle.

[0053] like Figure 4AAs indicated by reference numeral 410, the vehicle device 405 can acquire data related to the interaction between the driver and the vehicle (referred to herein as "driver interaction data"). Driver interaction data may include data related to the interaction between a specific driver (e.g., the current driver of the vehicle) and the vehicle. Driver interaction data may be collected by one or more sensors of the vehicle (e.g., one or more sensors in sensor subsystem 204). In some aspects, the vehicle device 405 may acquire driver interaction data by causing or controlling one or more sensors to collect driver interaction data. In some aspects, the vehicle device 405 may acquire driver interaction data by receiving driver interaction data from one or more sensors. In some aspects (e.g., where the vehicle device 405 is a remote device), the vehicle device 405 may acquire driver interaction data by receiving a transmission (or multiple transmissions) including driver interaction data from another device associated with the vehicle (e.g., an onboard device).

[0054] In some aspects, vehicle device 405 may acquire driver interaction data via online data collection while the vehicle is being driven. That is, driver interaction data may be collected while the vehicle is being driven (e.g., by one or more sensors and / or vehicle device 405). In some examples, driver interaction data may be collected continuously while the vehicle is being driven. In some other examples, driver interaction data may be collected periodically or in response to certain triggering conditions (e.g., corresponding to target driving conditions) while the vehicle is being driven. In some examples, driver interaction data may be collected while the driver is driving the vehicle, without the driver's knowledge that driver interaction data has been collected. In some aspects, driver interaction data may be collected while the vehicle is being driven and when no autonomous driving or driver assistance (e.g., ADAS) function is active. In some aspects, driver interaction data may be collected while the vehicle is being driven and when a particular autonomous driving or driver assistance function whose tuning parameters are estimated / updated is not active. In some respects, driver interaction data can be collected when the vehicle is being driven, both when the autonomous driving or driver assistance functions (e.g., when their tuning parameters are estimated / updated) are active and when the autonomous driving or driver assistance functions are not active.

[0055] In some aspects, where driver interaction data is obtained via online data collection while the vehicle is being driven, the estimation of one or more driver interaction parameters (discussed in conjunction with reference numeral 415) and the updating of one or more tuning parameters associated with autonomous driving or driver assistance functions (discussed in conjunction with reference numeral 420) can also be performed online by the vehicle device 405 while the vehicle is being driven. In such examples, the vehicle device 405 may repeatedly (e.g., continuously, periodically, or in response to certain triggering conditions) estimate one or more driver interaction parameters (discussed in conjunction with reference numeral 415) based on driver interaction data, and update one or more tuning parameters associated with autonomous driving or driver assistance functions (discussed in conjunction with reference numeral 420) based on one or more driver interaction parameters to improve / adjust the tuning parameters (e.g., DIL tuning parameters) during the period when the vehicle is being driven. In this case, the updating of one or more tuning parameters may restart each time the vehicle is started / driven, or may be combined with previously updated tuning parameters.

[0056] In some aspects, (e.g., driver interaction data collected while the vehicle is being driven) may include one or more of the following: driver steering data, brake input data, accelerator input data, and / or driver condition monitoring data. Driver steering data may include measurements of steering wheel torque (e.g., measurements of the torque applied by the driver to the steering wheel of the vehicle (at different times)). Braking input may include measurements of the force or pressure applied by the driver to the brake pedal of the vehicle and / or measurements of the angle of the brake pedal of the vehicle. Accelerator input data may include measurements of the force or pressure applied to the accelerator pedal of the vehicle and / or measurements of the angle of the accelerator pedal of the vehicle.

[0057] In some aspects, vehicle device 405 can classify driver interaction data into different categories for estimating driver interaction parameters. Vehicle device 405 can classify driver interaction data into multiple datasets associated with different corresponding driving scenarios. That is, driver interaction data associated with different driving scenarios can be stored in separate datasets. In some examples, vehicle device 405 can classify driver interaction data into different datasets based on whether the interaction between the driver and the vehicle is actively changing the movement of the vehicle (e.g., to distinguish between active and passive phases of driver-vehicle interaction performed by the driver). In such examples, driver interaction data can be classified into a first dataset (or multiple first datasets) and a second dataset (or multiple second datasets), the first dataset including driver interaction data associated with active interactions with the vehicle performed by the driver (e.g., active interactions with the vehicle's steering wheel), and the second dataset including driver interaction data associated with passive interactions with the vehicle performed by the driver (e.g., passive interactions with the vehicle's steering wheel). Alternatively or additionally, the vehicle device 405 may classify driver interaction data into different datasets based on different road geometries (e.g., straight driving and different curvature ranges). Alternatively or additionally, the vehicle device 405 may classify driver interaction data into different datasets based on different speed ranges of the vehicle and / or different acceleration states of the vehicle (e.g., acceleration, deceleration, or steady-state driving). Alternatively or additionally, the vehicle device 405 may classify driver interaction data into different datasets based on different road conditions and / or environmental conditions.

[0058] In some aspects, vehicle equipment 405 may acquire driver interaction data via a vehicle-driver interaction sequence executed when the vehicle is stationary (e.g., in a stationary state). For example, the vehicle-driver interaction sequence may be used to collect driver interaction data offline when the vehicle is not being driven. In some examples, the vehicle-driver interaction sequence may be executed in response to explicit activation of the vehicle's driver. For example, the vehicle-driver interaction sequence may be executed before the driver drives the vehicle (e.g., in response to the driver activating the vehicle-driver interaction sequence). The vehicle-driver interaction sequence may include a sequence of interactions with the vehicle (e.g., with the steering wheel, brake pedal, and / or accelerator pedal, etc.) to be performed by the driver. For example, the interaction sequence may include active interactions with the vehicle (e.g., active steering of the steering wheel) and / or passive interactions with the vehicle (e.g., passively guiding the driver's hands through automatic control of the vehicle's steering wheel). In some examples, the vehicle-driver interaction sequence may include one or more actuators (e.g., actuators of steering controller 246 that control the steering wheel of the vehicle) to move a part of the vehicle, while the driver allows his / her hands to be guided by the movement of that part of the vehicle (e.g., the steering wheel) without interfering with that movement. In such examples, the vehicle-driver interaction sequence may also include instructing the driver to perform one or more additional tasks so that the driver is not focused on the movement controlled by the one or more actuators, but rather on what is as intuitive as possible. Driver inputs (e.g., driver steering input, driver braking input, and / or driver accelerator input, etc.) may be measured during the vehicle-driver interaction sequence to obtain driver interaction data. That is, driver interaction data may include measurements of the interaction between the driver and the vehicle in the vehicle-driver interaction sequence.

[0059] In some aspects, where driver interaction data is obtained via a vehicle-driver interaction sequence when the vehicle is not being driven (e.g., stationary), the estimation of one or more driver interaction parameters (discussed in conjunction with reference numeral 415) and the updating of one or more tuning parameters associated with autonomous driving or driver assistance functions (discussed in conjunction with reference numeral 420) may also be performed by the vehicle device 405 when the vehicle is not being driven. In such examples, the vehicle device 405 may estimate one or more driver interaction parameters (discussed in conjunction with reference numeral 415) based on the driver interaction data and update one or more tuning parameters associated with autonomous driving or driver assistance functions (discussed in conjunction with reference numeral 420) offline based on the one or more driver interaction parameters before the vehicle is driven by a driver. In some examples, the driver may be guided (e.g., controlled by the vehicle device 405) to interact with the vehicle during the vehicle-driver interaction sequence, as discussed above. In some other examples, the vehicle-driver interaction sequence may be performed by the vehicle as part of a service (e.g., at a garage) (e.g., controlled by vehicle equipment 405) to tune the tuning parameters of autonomous driving or driver assistance functions.

[0060] like Figure 4A Furthermore, as shown by reference numeral 415, the vehicle device 405 can estimate one or more driver interaction parameters based on driver interaction data. In some aspects, the vehicle device 405 can estimate one or more driver interaction parameters online when the vehicle is being driven. In some other aspects, when the vehicle is not being driven (e.g., when the vehicle is stationary), the vehicle device 405 can estimate one or more driver interaction parameters offline.

[0061] In some aspects, vehicle device 405 may estimate one or more driver interactions by applying one or more estimation techniques to the collected driver interaction data. For example, the one or more estimation techniques applied to the driver interaction data may include one or more of linear regression, averaging, three-sigma (and / or six-sigma) computational geometric curve fitting, and / or machine learning-based estimation. In some aspects, where the driver interaction data is categorized into multiple datasets (e.g., associated with different driving scenarios), vehicle device 405 may estimate corresponding driver interaction parameters for one or more datasets among the multiple datasets. In some examples, vehicle device 405 may estimate one or more corresponding driver interaction parameters for each dataset among the multiple datasets. In some examples, one or more datasets among the multiple datasets may be retained for estimating driver interaction parameters, and one or more datasets among the multiple datasets may be discarded (e.g., not used for estimating driver interaction parameters). In this case, vehicle device 405 may estimate one or more corresponding driver interaction parameters for each dataset that is not discarded. In some aspects, the vehicle device 405 may estimate one or more driver interaction parameters associated with active interactions between the driver and the vehicle (e.g., with the steering wheel of the vehicle) and / or passive interactions between the driver and the vehicle (e.g., with the steering wheel of the vehicle).

[0062] The driver interaction data in the dataset can be driver input signals, including measurements of driver-vehicle interactions at various time points (e.g., steering wheel torque measurements, driver braking input measurements, driver accelerator input measurements, and / or driver condition monitoring inputs). In some aspects, vehicle equipment 405 can estimate driver interaction parameters and / or signals of interest for the dataset by applying estimation techniques (e.g., averaging, linear regression, three sigma, geometric curve fitting, or machine learning-based estimation) to the driver input signals included in the dataset.

[0063] In some aspects, driver interaction parameters and / or driver interaction parameter signals of interest can be intermediate parameters or values ​​that can be used to determine tuning parameters (e.g., DIL tuning parameters) for autonomous driving or driver assistance functions. In some examples, one or more driver interaction parameters may include one or more steering wheel torque values ​​(and / or parameters associated with steering wheel torque values) associated with active steering performed by the driver of the vehicle, and one or more steering wheel torque values ​​(and / or parameters associated with steering wheel torque values) associated with passive interaction with the steering wheel of the vehicle performed by the driver of the vehicle. For example, the steering wheel torque value may be an average steering wheel torque value estimated based on driver input steering wheel torque values ​​in a corresponding dataset associated with active steering and passive interaction (or a value produced by other estimation techniques performed on the driver input steering wheel torque values). Additionally or alternatively, driver interaction parameters may include derivatives (e.g., rates of change) of the driver input signal (e.g., derivatives associated with driver input steering wheel torque signals for active steering and passive interaction) and / or integrals of the driver input signal (e.g., integrals associated with driver input steering wheel torque signals for active steering and passive interaction), etc. In some examples, the steering wheel torque value, the derivative associated with the steering wheel torque value, and / or the integral associated with the steering wheel torque value can be parameters used to estimate the DIL tuning parameters for automatic or assisted steering functions.

[0064] In some aspects, one or more driver interaction parameters may include tuning parameters (e.g., driver-specific DIL tuning parameters) estimated based on driver interaction data for autonomous driving or driver assistance functions. For example, one or more driver interaction parameters may include one or more thresholds, gains, integral parameters, derivative parameters, and / or rate limits, as well as other examples that can be used (e.g., in logic associated with the function) to detect active or passive interactions with the vehicle performed by the driver. Integral parameters may include one or more parameters associated with integrating driver input data and / or parameters estimated based on driver input data for detecting active or passive interactions with the vehicle performed by the driver. For example, a decay rate parameter may be associated with an integral calculation performed to detect active or passive interactions with the vehicle performed by the driver. Derivative parameters may include one or more parameters associated with calculating a derivative (e.g., rate of change) based on driver input data and / or parameters estimated based on driver input data for detecting active or passive interactions with the vehicle performed by the driver. In some examples, one or more driver interaction parameters may include one or more thresholds, gains, integral parameters, derivative parameters and / or rate limits, as well as other examples associated with the detection of steering wheel torque-based actions by the driver in active or passive interactions with the vehicle.

[0065] like Figure 4A Furthermore, as shown by reference numeral 420, the vehicle device 405 can update one or more tuning parameters associated with an autonomous driving or driver assistance function based on one or more driver interaction parameters, thereby generating one or more updated tuning parameters. In some aspects, the tuning parameters may be DIL tuning parameters associated with an autonomous driving or driver assistance function. For example, the tuning parameters (e.g., updated tuning parameters) may be associated with the transfer of control of the vehicle between the autonomous driving or driver assistance function and the driver of the vehicle based on detection (e.g., based on detection of passive or active interactions with the vehicle by the driver). In some aspects, the autonomous driving or driver assistance function may be an automatic or assisted steering function that controls the lateral movement of the vehicle.

[0066] In some aspects, one or more updated tuning parameters may include one or more updated thresholds, gains, integral parameters, derivative parameters, or rate limits associated with the detection of active or passive interactions with the vehicle by the driver. In some examples, one or more updated tuning parameters may include one or more updated thresholds, gains, integral parameters, derivative parameters, or rate limits associated with the detection of active or passive interactions with the vehicle's steering wheel by the driver. For example, updated thresholds may include one or more updated steering wheel torque thresholds and / or one or more updated integral thresholds (e.g., for comparison with integral values ​​associated with driver-input steering wheel torque). Updated gains may include one or more updated gains for weighted values ​​used to detect active or passive interactions. Updated integral and / or derivative parameters may include one or more updated parameters (such as decay rate parameters) associated with calculating the integral and / or derivative used to detect active or passive interactions. The updated rate limit may include one or more updated rate limits that are compared with the rate of change (e.g., derivative) of the driver’s steering wheel torque input to detect active or passive interaction.

[0067] Vehicle device 405 may update the current tuning parameters (e.g., DIL tuning parameters) of an automated driving or driver assistance function based on estimated driver interaction parameters, thereby producing updated tuning parameters. In some examples, the current tuning parameters may be initial or default tuning parameters. In some other examples, the current tuning parameters may be previously updated tuning parameters. In some aspects, vehicle device 405 may update the current tuning parameters to updated tuning parameters by estimating an update to the current tuning parameters based at least in part on one or more estimated driver interaction parameters. In some aspects, where one or more driver interaction parameters include one or more estimated tuning parameters, vehicle device 405 may update the tuning parameters by combining or mixing the tuning parameters estimated based on driver interaction data with the current tuning parameters. In some aspects, where one or more driver interaction parameters include one or more estimated tuning parameters, vehicle device 405 may update the tuning parameters by changing (e.g., gradually changing) from the current tuning parameters to the tuning parameters estimated based on driver interaction data.

[0068] In some aspects, vehicle equipment 405 may update the tuning parameters in response to one or more conditions associated with updating the tuning parameters. For example, in the case where driver interaction data is collected online while the vehicle is being driven, vehicle equipment 405 may update the tuning parameters once by incorporating a threshold amount of driver interaction data that has been collected and used to estimate the driver interaction parameters. The threshold amount of driver interaction data ensures that sufficient driver interaction data to represent the current driving situation has been collected before updating the tuning parameters. Additionally or alternatively, vehicle equipment 405 may perform a reasonableness check on the updated tuning parameters (e.g., DIL parameters) by checking boundaries and / or compatibility with other DIL parameters. In this case, vehicle equipment 405 may update the tuning parameters by incorporating the updated tuning parameters that have passed the reasonableness check (e.g., boundary check and / or compatibility check).

[0069] like Figure 4B As indicated by reference numeral 425, vehicle equipment 405 enables the application of automatic driving or driver assistance functions at the vehicle based on one or more updated tuning parameters. Vehicle equipment 405 enables the application of automatic driving or driver assistance functions at the vehicle based on one or more updated tuning parameters when the vehicle is being driven. In some aspects, where vehicle equipment 405 is an onboard device or system of the vehicle, vehicle equipment 405 can control the automatic driving or driver assistance functions based on one or more updated tuning parameters, enabling the application of automatic driving or driver assistance functions at the vehicle based on one or more updated tuning parameters.

[0070] Figure 4B An example 430 of a vehicle device 405 controlling an autonomous driving or driver assistance function based on one or more updated tuning parameters is shown. As indicated by reference numeral 432, the vehicle device 405 may activate an autonomous driving or driver assistance function. For example, an autonomous driving or driver assistance function may be an automatic or assisted steering function that controls the lateral movement of the vehicle. As indicated by reference numeral 434, the vehicle device 405 may monitor driver interaction data. The vehicle device 405 may acquire driver interaction data from one or more sensors. In some examples, driver interaction data may include data related to the interaction between the driver and the vehicle's steering wheel. For example, driver interaction data may include a measurement of the steering wheel torque value applied by the driver to the vehicle's steering wheel. In some examples, other driver interaction data may be monitored in addition to or in lieu of the steering wheel torque measurement.

[0071] As indicated by reference numeral 436, vehicle device 405 can detect passive or active driver interactions based on driver interaction data and one or more updated tuning parameters. The one or more updated tuning parameters may include one or more updated DIL tuning parameters for automated driving or driver assistance functions. In some aspects, the one or more updated tuning parameters may include one or more updated thresholds, gain, integral parameters, derivative parameters, or rate limits associated with the detection of active or passive interactions with the vehicle by the driver. Vehicle device 405 can detect passive or active interactions with the vehicle by the driver by applying one or more updated thresholds, gain, integral parameters, derivative parameters, or rate limits to the driver interaction data. In some aspects, the driver interaction data may include a measurement of the steering wheel torque value applied by the driver to the steering wheel of the vehicle, and the one or more updated tuning parameters may include one or more updated thresholds, gain, integral parameters, derivative parameters, or rate limits associated with the detection of active or passive interactions with the steering wheel of the vehicle by the driver. Vehicle equipment 405 can detect passive interactions (e.g., active steering) between the driver and the vehicle's steering wheel by applying one or more updated thresholds, gains, integral parameters, differential parameters, or rate limits to a measurement of the steering wheel torque value applied by the driver.

[0072] As indicated by reference numeral 438, vehicle device 405 can transfer control of the vehicle between an automated driving or driver assistance function and the driver of the vehicle based on the detection of passive or active driver interaction. When an automated driving or driver assistance function (e.g., automatic or assisted steering) is controlling the vehicle (e.g., controlling the lateral movement of the vehicle) and vehicle device 405 detects active interaction between the driver and the vehicle (e.g., active steering performed by the driver) based on updated tuning parameters and driver interaction data, vehicle device 405 can transfer control of the vehicle from the automated driving or driver assistance function to the driver. For example, in this case, vehicle device 405 can control a gradual reduction in the steering wheel torque applied by the automated driving or driver assistance function. When an automated driving or driver assistance function (e.g., automatic or assisted steering) is not controlling the vehicle (e.g., control of the vehicle has previously been transferred to the driver) and vehicle device 405 detects passive interaction between the driver and the vehicle (e.g., with the vehicle's steering wheel) based on updated tuning parameters and driver interaction data, vehicle device 405 can transfer control of the vehicle (e.g., from the driver) to the automated driving or driver assistance function. For example, in this case, vehicle equipment 405 can control the steering wheel torque applied by the automatic driving or driving assistance function to increase slowly.

[0073] In some aspects, where vehicle equipment 405 is a remote device associated with a vehicle, vehicle equipment 405 can send updated tuning parameters (e.g., updated DIL tuning parameters) to onboard equipment or systems of the vehicle for use by the onboard equipment or systems to control automatic driving or driver assistance functions, such that automatic driving or driver assistance functions are applied at the vehicle based on one or more updated tuning parameters. In this case, the onboard equipment or systems can control the automatic driving or driver assistance functions as discussed above in conjunction with Example 430.

[0074] As indicated above, Figures 4A to 4B This is provided as an example. Other examples are available with reference to [the relevant information]. Figures 4A to 4B The content described is different.

[0075] Figure 5 This is a flowchart of an example process 500 associated with the estimation of driver interaction-based tuning parameters for autonomous driving or driver assistance, according to this disclosure. In some aspects, Figure 5 One or more process frames are executed by a device (e.g., vehicle device 405, onboard system 120, onboard system 200, or onboard device 208). In some aspects, Figure 5One or more process frames are executed by another device or a group of devices separate from or including that device (such as remote devices (e.g., remote device 130) and / or network nodes (e.g., network node 150)). Additionally or alternatively, Figure 5 One or more process frames may be executed by one or more components of the device 300, such as processor 310, memory 315, input component 320, output component 325, communication component 330 and / or estimation component 335.

[0076] like Figure 5 As shown, process 500 may include obtaining data related to the interaction between the driver and the vehicle (box 510). For example, the device may obtain data related to the interaction between the driver and the vehicle, as described above.

[0077] like Figure 5 As further shown, process 500 may include estimating one or more driver interaction parameters based on data related to the interaction between the driver and the vehicle (box 520). For example, the device may estimate one or more driver interaction parameters based on data related to the interaction between the driver and the vehicle, as described above.

[0078] like Figure 5 As further shown, process 500 may include updating one or more tuning parameters associated with autonomous driving or driver assistance functions based on one or more driver interaction parameters, thereby generating one or more updated tuning parameters (box 530). For example, the device may update one or more tuning parameters associated with autonomous driving or driver assistance functions based on one or more driver interaction parameters, thereby generating one or more updated tuning parameters, as described above.

[0079] like Figure 5 As further shown, process 500 may include enabling the application of autonomous driving or driver assistance functions at the vehicle based on one or more updated tuning parameters (box 540). For example, the device may enable the application of autonomous driving or driver assistance functions at the vehicle based on one or more updated tuning parameters, as described above.

[0080] Process 500 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0081] In the first aspect, obtaining data related to the interaction between the driver and the vehicle includes obtaining data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven.

[0082] In the second aspect, either alone or in combination with the first aspect, obtaining data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven includes obtaining data related to the interaction between the driver and the vehicle via online data collection when the vehicle is being driven and autonomous driving or driver assistance functions are not activated.

[0083] In the third aspect, alone or in combination with one or more of the first and second aspects, the data relating to the interaction between the driver and the vehicle includes at least one of driver steering data, brake input data, accelerator input data, or condition monitoring data.

[0084] In the fourth aspect, either alone or in combination with one or more of the first to third aspects, process 500 includes classifying data related to the interaction between the driver and the vehicle into multiple datasets associated with different corresponding driving scenarios.

[0085] In the fifth aspect, data relating to the interaction between the driver and the vehicle is classified into multiple datasets associated with different driving scenarios, either alone or in combination with one or more of the first to fourth aspects. This classification is based on at least one of the following: whether the interaction between the driver and the vehicle is actively altering the motion of the vehicle, different road geometries, different speed ranges, different acceleration states of the vehicle, or different road or environmental conditions.

[0086] In the sixth aspect, estimating one or more driver interaction parameters based on data related to the interaction between the driver and the vehicle, either alone or in combination with one or more of the first to fifth aspects, includes estimating corresponding driver interaction parameters for one or more datasets among a plurality of datasets.

[0087] In the seventh aspect, obtaining data related to the interaction between the driver and the vehicle, either alone or in combination with one or more of the first to sixth aspects, includes obtaining data related to the interaction between the driver and the vehicle via a vehicle-driver interaction sequence when the vehicle is stationary.

[0088] In the eighth aspect, either alone or in combination with one or more of the first to seventh aspects, one or more updated tuning parameters are associated with the transfer of control of the vehicle between autonomous driving or driver assistance functions and the driver of the vehicle.

[0089] In the ninth aspect, data relating to the interaction between the driver and the vehicle, either alone or in combination with one or more of the first to eighth aspects, includes data relating to the interaction between the driver and the steering wheel of the vehicle.

[0090] In the tenth aspect, individually or in combination with one or more of the first to ninth aspects, one or more driver interaction parameters include one or more driver steering wheel torque values ​​associated with active steering performed by the driver of the vehicle, and one or more driver steering wheel torque values ​​associated with passive interaction of the driver of the vehicle with the steering wheel of the vehicle.

[0091] In the eleventh aspect, individually or in combination with one or more of the first to tenth aspects, one or more driver interaction parameters include one or more steering wheel torque thresholds, integrals, derivatives, or gains associated with detecting active or passive interactions with the steering wheel of the vehicle by the driver of the vehicle.

[0092] In the twelfth aspect, either alone or in combination with one or more of the first to eleventh aspects, one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits associated with the detection of active or passive interaction with the steering wheel of the vehicle by the driver of the vehicle based on steering wheel torque.

[0093] In the thirteenth aspect, alone or in combination with one or more of the first to twelfth aspects, the application of an automated driving or driver assistance function at a vehicle based on one or more updated tuning parameters includes at least one of the following: detecting active interaction with the steering wheel of the vehicle based at least in part on one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits, thereby transferring control of the vehicle from the automated driving or driver assistance function to the driver of the vehicle; or detecting passive interaction with the steering wheel of the vehicle based at least in part on one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits, thereby transferring control of the vehicle to the automated driving or driver assistance function.

[0094] In the fourteenth aspect, alone or in combination with one or more of the first to thirteenth aspects, one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits associated with detecting active or passive interactions with the vehicle by the driver of the vehicle.

[0095] In the fifteenth aspect, alone or in combination with one or more of the first to fourteenth aspects, the application of an automated driving or driver assistance function at a vehicle based on one or more updated tuning parameters includes at least one of the following: detecting active interaction with the vehicle based at least in part on updated thresholds, gain, integral parameters, differential parameters, or rate limits, transferring control of the vehicle from the automated driving or driver assistance function to the driver of the vehicle; or detecting passive interaction with the vehicle based at least in part on one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits, transferring control of the vehicle to the automated driving or driver assistance function.

[0096] although Figure 5 An example box of process 500 is shown, but in some respects, process 500 includes... Figure 5 The depicted boxes may be fewer, different, or arranged differently compared to additional boxes, boxes, or boxes in different ways. Alternatively, two or more boxes in the process 500 may be executed in parallel.

[0097] The following provides an overview of some aspects of this disclosure: Aspect 1: A method performed by a device associated with a vehicle, the method comprising: obtaining data related to an interaction between a driver and the vehicle by the device; estimating one or more driver interaction parameters by the device based on the data related to the interaction between the driver and the vehicle; updating one or more tuning parameters associated with an autonomous driving or driver assistance function by the device based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters; and causing the device to apply the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters.

[0098] Aspect 2: According to the method of aspect 1, obtaining the data related to the interaction between the driver and the vehicle includes: obtaining the data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven.

[0099] Aspect 3: According to the method of aspect 2, wherein obtaining the data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven includes: obtaining the data related to the interaction between the driver and the vehicle via online data collection when the vehicle is being driven and the autonomous driving or driving assistance function is not activated.

[0100] Aspect 4: The method according to any one of Aspects 2 to 3, wherein the data related to the interaction between the driver and the vehicle includes at least one of the following: driver steering data, brake input data, accelerator input data, or driver condition monitoring data.

[0101] Aspect 5: The method according to any one of Aspects 2 to 4, the method further comprising: classifying the data related to the interaction between the driver and the vehicle into multiple datasets associated with different corresponding driving scenarios.

[0102] Aspect 6: According to the method of aspect 5, classifying the data related to the interaction between the driver and the vehicle into multiple datasets associated with different driving scenarios includes classifying the data related to the interaction between the driver and the vehicle into the multiple datasets based on at least one of: whether the interaction between the driver and the vehicle is actively changing the motion of the vehicle, different road geometry, different speed range, different acceleration state of the vehicle, or different road conditions or environmental conditions.

[0103] Aspect 7: The method according to any one of Aspects 5 to 6, wherein estimating one or more driver interaction parameters based on the data related to the interaction between the driver and the vehicle comprises: estimating corresponding driver interaction parameters for one or more of the plurality of datasets.

[0104] Aspect 8: According to the method of aspect 1, obtaining the data related to the interaction between the driver and the vehicle includes: obtaining the data related to the interaction between the driver and the vehicle via a vehicle-driver interaction sequence when the vehicle is stationary.

[0105] Aspect 9: The method according to any one of Aspects 1 to 8, wherein the one or more updated tuning parameters are associated with the transfer of control of the vehicle between the autonomous driving or driving assistance function and the driver of the vehicle.

[0106] Aspect 10: The method according to any one of Aspects 1 to 9, wherein the data related to the interaction between the driver and the vehicle includes data related to the interaction between the driver and the steering wheel of the vehicle.

[0107] Aspect 11: According to the method of aspect 10, the one or more driver interaction parameters include: one or more driver steering wheel torque values ​​associated with active steering performed by the driver of the vehicle, and one or more driver steering wheel torque values ​​associated with passive interaction between the driver of the vehicle and the steering wheel of the vehicle.

[0108] Aspect 12: The method according to any one of Aspects 10 to 11, wherein one or more driver interaction parameters include one or more steering wheel torque thresholds, integrals, derivatives, or gains associated with detecting active or passive interactions with the steering wheel of the vehicle performed by the driver of the vehicle.

[0109] Aspect 13: The method according to any one of Aspects 10 to 12, wherein the one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters or rate limits associated with the detection of steering wheel torque based on active or passive interaction with the steering wheel of the vehicle by the driver of the vehicle.

[0110] Aspect 14: The method according to aspect 13, wherein applying the autonomous driving or driver assistance function at the vehicle based on the one or more updated tuning parameters includes at least one of: transferring control of the vehicle from the autonomous driving or driver assistance function to the driver of the vehicle by detecting active interaction with the steering wheel of the vehicle based at least in part on the one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits; or transferring control of the vehicle to the autonomous driving or driver assistance function by detecting passive interaction with the steering wheel of the vehicle based at least in part on the one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits.

[0111] Aspect 15: The method according to any one of Aspects 1 to 14, wherein the one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters or rate limits associated with detecting active or passive interactions with the vehicle by the driver of the vehicle.

[0112] Aspect 16: The method according to aspect 15, wherein applying the autonomous driving or driver assistance function at the vehicle based on the one or more updated tuning parameters includes at least one of: transferring control of the vehicle from the autonomous driving or driver assistance function to the driver of the vehicle by detecting active interaction with the vehicle based at least in part on the updated threshold, gain, integral parameter, differential parameter, or rate limit; or transferring control of the vehicle to the autonomous driving or driver assistance function by detecting passive interaction with the vehicle based at least in part on the one or more updated threshold, gain, integral parameter, differential parameter, or rate limit.

[0113] Aspect 17: A system configured to perform one or more of the operations described in aspects 1 to 16.

[0114] Aspect 18: An apparatus comprising components for performing one or more of the operations described in aspects 1 to 16.

[0115] Aspect 19: A non-transitory computer-readable medium storing an instruction set comprising one or more instructions that, when executed by a device, cause the device to perform one or more of the operations described in aspects 1 to 16.

[0116] Aspect 20: A computer program product comprising instructions or code for performing one or more of the operations described in aspects 1 to 16.

[0117] While the foregoing disclosure provides examples and descriptions, it is not intended to be exhaustive or to limit the aspects to the precise form disclosed. Modifications and variations may be made based on the foregoing disclosure, or from various forms of practice.

[0118] As used herein, the term "component" is intended to be interpreted broadly as hardware and / or a combination of hardware and software. Whether referred to as software, firmware, middleware, microcode, hardware description language, or other names, "software" should be interpreted broadly as meaning instructions, instruction sets, code, code segments, program code, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, and / or functions, etc. As used herein, a "processor" is implemented in hardware and / or a combination of hardware and software. It will be apparent to those skilled in the art that the systems and / or methods described herein can be implemented in various forms of hardware and / or combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limiting in any way. Therefore, no specific software code is referenced in this document to describe the operation and behavior of the systems and / or methods, as those skilled in the art will understand that the software and hardware can be designed, at least in part, based on the descriptions herein, to implement the systems and / or methods.

[0119] As used in this article, depending on the context, "meeting the threshold" can mean a value greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, not equal to the threshold, etc.

[0120] Although specific combinations of features are set forth in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. Many of these features may be combined in ways not specifically set forth in the claims and / or not disclosed in the specification. The disclosure of various aspects includes each dependent claim in combination with each other claim in the set of claims. As used herein, the phrase referring to “at least one of” the list of items means any combination of these items, including a single member. As an example, “at least one of a, b, or c” is intended to cover: a, b, c, a+b, a+c, b+c, and a+b+c, as well as any combination having multiple identical elements (e.g., a+a, a+a+a, a+a+b, a+a+c, a+b+b, a+c+c, b+b, b+b+b, b+b+c, c+c, and c+c+c, or any other ordering of a, b, and c).

[0121] No element, action, or instruction used herein should be construed as essential or necessary unless explicitly stated otherwise. Furthermore, as used herein, the articles “a” and “an” are intended to include one or more items and are used interchangeably with “one or more.” Furthermore, as used herein, the article “described” is intended to include one or more items mentioned in connection with the article “described” and is used interchangeably with “one or more.” Furthermore, as used herein, the terms “set” and “group” are intended to include one or more items and are used interchangeably with “one or more.” If only one item is desired, the phrase “only one” or similar terminology will be used. Furthermore, as used herein, the terms “have,” “possess,” “have,” etc., are intended to be open-ended terms that do not limit the elements they modify (e.g., an element “having” A may also have B). Furthermore, the phrase “based on” is intended to mean “at least partially based on” unless otherwise explicitly stated. Furthermore, as used herein, the term “or” is intended to be inclusive when used in a series and is interchangeable with “and / or” unless otherwise explicitly stated (e.g., in the case of its use in conjunction with “any” or “only one”).

Claims

1. A device associated with a vehicle, the device comprising: One or more memory units; and One or more processors, said one or more processors coupled to said one or more memories and configured such that the device: Obtain data related to the interaction between the driver and the vehicle; One or more driver interaction parameters are estimated based on the data related to the interaction between the driver and the vehicle; Based on the one or more driver interaction parameters, update one or more tuning parameters associated with autonomous driving or driver assistance functions to generate one or more updated tuning parameters; as well as This enables the application of the autonomous driving or driving assistance function at the vehicle based on one or more updated tuning parameters.

2. The device of claim 1, wherein, in order for the device to obtain the data related to the interaction between the driver and the vehicle, the one or more processors are configured to cause the device to: The data relating to the interaction between the driver and the vehicle is obtained via online data collection while the vehicle is being driven.

3. The device of claim 2, wherein, in order for the device to obtain the data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven, the one or more processors are configured to cause the device to: When the vehicle is being driven and the autonomous driving or driver assistance function is not activated, the data related to the interaction between the driver and the vehicle is obtained via online data collection.

4. The device of claim 2, wherein the data relating to the interaction between the driver and the vehicle includes at least one of the following: Driver steering data, Braking input data, Accelerator input data, or Driver condition monitoring data.

5. The device of claim 2, wherein the one or more processors are further configured such that the device: The data related to the interaction between the driver and the vehicle is categorized into multiple datasets associated with different corresponding driving scenarios.

6. The device of claim 5, wherein, in order for the device to classify the data related to the interaction between the driver and the vehicle into multiple datasets associated with different driving scenarios, the one or more processors are configured to cause the device to: The data relating to the interaction between the driver and the vehicle is classified into the plurality of datasets based on at least one of the following: Is the interaction between the driver and the vehicle actively altering the movement of the vehicle? Different road geometries, Different speed ranges, The different acceleration states of the vehicle, or Different road conditions or environmental conditions.

7. The device of claim 5, wherein, in order for the device to estimate one or more driver interaction parameters based on the data relating to the interaction between the driver and the vehicle, the one or more processors are configured to cause the device to: Estimate the corresponding driver interaction parameters for one or more of the plurality of datasets.

8. The device of claim 1, wherein, in order for the device to obtain the data related to the interaction between the driver and the vehicle, the one or more processors are configured to cause the device to: The data related to the interaction between the driver and the vehicle is obtained via a vehicle-driver interaction sequence when the vehicle is stationary.

9. The device of claim 1, wherein the one or more updated tuning parameters are associated with the transfer of control of the vehicle between the autonomous driving or driving assistance function and the driver of the vehicle.

10. The device of claim 1, wherein the data relating to the interaction between the driver and the vehicle includes data relating to the interaction between the driver and the steering wheel of the vehicle.

11. The device of claim 10, wherein the one or more driver interaction parameters include: One or more driver steering wheel torque values ​​associated with active steering performed by the driver of the vehicle, and One or more driver steering wheel torque values ​​associated with passive interactions between the driver of the vehicle and the steering wheel of the vehicle.

12. The device of claim 10, wherein one or more driver interaction parameters include one or more steering wheel torque thresholds, integrals, derivatives, or gains associated with detecting active or passive interactions with the steering wheel of the vehicle performed by the driver of the vehicle.

13. The device of claim 10, wherein the one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits associated with the detection of steering wheel torque-based active or passive interaction with the steering wheel of the vehicle by the driver of the vehicle.

14. The device of claim 13, wherein, in order for the device to apply the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters, the one or more processors are configured to cause the device to: By combining active interaction with the steering wheel of the vehicle with detection based at least in part on one or more updated thresholds, gains, integral parameters, differential parameters, or rate limits, control of the vehicle is transferred from the autonomous driving or driver assistance functions to the driver of the vehicle; or By combining the detection of passive interaction with the steering wheel of the vehicle with at least in part based on one or more updated thresholds, gains, integral parameters, differential parameters, or rate limits, control of the vehicle is transferred to the autonomous driving or driver assistance function.

15. The device of claim 1, wherein the one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits associated with detecting active or passive interactions with the vehicle by the driver of the vehicle.

16. The device of claim 15, wherein, in order for the device to apply the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters, the one or more processors are configured to cause the device to: By combining the detection of active interaction with the vehicle with at least in part based on the updated threshold, gain, integral parameter, differential parameter, or rate limit, control of the vehicle is transferred from the autonomous driving or driver assistance function to the driver of the vehicle; or By combining the detection of passive interactions with the vehicle with at least in part based on one or more updated thresholds, gains, integral parameters, differential parameters, or rate limits, control of the vehicle is transferred to the autonomous driving or driver assistance function.

17. A method performed by equipment associated with a vehicle, the method comprising: The device acquires data related to the interaction between the driver and the vehicle; The device estimates one or more driver interaction parameters based on the data related to the interaction between the driver and the vehicle; The device updates one or more tuning parameters associated with autonomous driving or driver assistance functions based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters; as well as The device enables the application of the autonomous driving or driving assistance function in the vehicle based on one or more updated tuning parameters.

18. The method of claim 17, wherein obtaining the data related to the interaction between the driver and the vehicle comprises: The data relating to the interaction between the driver and the vehicle is obtained via online data collection while the vehicle is being driven.

19. The method of claim 18, wherein obtaining the data related to the interaction between the driver and the vehicle via online data collection while the vehicle is being driven comprises: When the vehicle is being driven and the autonomous driving or driver assistance function is not activated, the data related to the interaction between the driver and the vehicle is obtained via online data collection.

20. The method of claim 18, wherein the data relating to the interaction between the driver and the vehicle comprises at least one of the following: Driver steering data, Braking input data, Accelerator input data, or Driver condition monitoring data.

21. The method according to claim 18, further comprising: The data related to the interaction between the driver and the vehicle is categorized into multiple datasets associated with different corresponding driving scenarios.

22. The method of claim 21, wherein classifying the data related to the interaction between the driver and the vehicle into multiple datasets associated with different driving scenarios comprises: The data relating to the interaction between the driver and the vehicle is classified into the plurality of datasets based on at least one of the following: Is the interaction between the driver and the vehicle actively altering the movement of the vehicle? Different road geometries, Different speed ranges, The different acceleration states of the vehicle, or Different road conditions or environmental conditions.

23. The method of claim 21, wherein estimating one or more driver interaction parameters based on the data relating to the interaction between the driver and the vehicle comprises: Estimate the corresponding driver interaction parameters for one or more of the plurality of datasets.

24. The method of claim 17, wherein obtaining the data related to the interaction between the driver and the vehicle comprises: The data related to the interaction between the driver and the vehicle is obtained via a vehicle-driver interaction sequence when the vehicle is stationary.

25. The method of claim 17, wherein the one or more updated tuning parameters are associated with the transfer of control of the vehicle between the autonomous driving or driving assistance function and the driver of the vehicle.

26. The method of claim 17, wherein the data relating to the interaction between the driver and the vehicle includes data relating to the interaction between the driver and the steering wheel of the vehicle.

27. The method of claim 17, wherein the one or more updated tuning parameters include one or more updated thresholds, gain, integral parameters, differential parameters, or rate limits associated with detecting active or passive interactions with the vehicle by the driver of the vehicle.

28. The method of claim 27, wherein applying the autonomous driving or driver assistance function at the vehicle according to the one or more updated tuning parameters comprises at least one of the following: By combining the detection of active interaction with the vehicle with at least in part based on the updated threshold, gain, integral parameter, differential parameter, or rate limit, control of the vehicle is transferred from the autonomous driving or driver assistance function to the driver of the vehicle; or By combining the detection of passive interactions with the vehicle with at least in part based on one or more updated thresholds, gains, integral parameters, differential parameters, or rate limits, control of the vehicle is transferred to the autonomous driving or driver assistance function.

29. A non-transitory computer-readable medium storing an instruction set, the instruction set comprising: One or more instructions, which, when executed by one or more processors of a device associated with a vehicle, cause the device to: Obtain data related to the interaction between the driver and the vehicle; One or more driver interaction parameters are estimated based on the data related to the interaction between the driver and the vehicle; Based on the one or more driver interaction parameters, update one or more tuning parameters associated with autonomous driving or driver assistance functions to generate one or more updated tuning parameters; as well as This enables the application of the autonomous driving or driving assistance function at the vehicle based on one or more updated tuning parameters.

30. An apparatus for wireless communication, the apparatus comprising: Components used to acquire data related to interactions with drivers and vehicles; A component for estimating one or more driver interaction parameters based on the data related to the interaction between the driver and the vehicle; Components for: updating one or more tuning parameters associated with autonomous driving or driver assistance functions based on the one or more driver interaction parameters, thereby generating one or more updated tuning parameters; as well as Components for enabling the application of the autonomous driving or driving assistance functions in the vehicle according to the one or more updated tuning parameters.

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