Atmospheric property evaluation system and method using lidar in dynamic environments

Abstract

Systems and methods are provided for evaluating atmospheric properties using a LIDAR sensor. A control system includes a LIDAR sensor configured to detect distances to objects and intensities of light reflected by the objects. A target selection module of the controller determines whether an object is a target for evaluating atmospheric properties. A data acquisition module acquires values of the distances and intensities detected by the LIDAR sensor. Atmospheric properties are determined based on the values of the distances and intensities. In response to the determined atmospheric properties, an actuator is operated to implement an action.

Description

Technical Field

[0001] This disclosure generally relates to the assessment of characteristics such as atmospheric visibility in dynamic environments, and more specifically to systems and methods for determining environmental characteristics such as visibility range and precipitation intensity using light detection and ranging (LIDAR). Background Technology

[0002] All actions, whether performed by humans or machines (autonomously), rely on data collected by various sensors. Applications such as transportation vehicles can use various sensors to operate Advanced Driver Assistance Systems (ADAS) and to enable autonomous vehicle operation. A LiDAR sensor can be used to assess the environment surrounding a vehicle. LiDAR sensors emit and receive light to collect data, thereby creating a virtual representation of the environment. LiDAR sensors can be used to identify stationary and moving objects on or near roads for use in making control decisions.

[0003] Sensors can acquire relevant data under various environmental conditions, which may include variables that affect the data being acquired. For example, for sensors such as LiDAR, which transmits a signal and evaluates the returned signal, environmental conditions can cause a reduction (attenuation) in the returned signal. In some cases, when a signal encounters raindrops at a short distance from the transmitter, the raindrops may reflect enough signal back to the receiver for the raindrops to be detected as objects. In other cases, precipitation may absorb some of the transmitted signal, resulting in a degraded signal being received. Therefore, the performance of a sensor and the ability to use the data acquired by the sensor are influenced by the dominant environmental conditions. When the data is used by a control system, it is useful to understand whether environmental conditions affect the data being acquired.

[0004] Methods for determining signal attenuation are typically calibrated for static environments. However, many sensors are used in dynamic environments with unfamiliar, moving, and constantly changing conditions. Therefore, statically calibrated systems may face challenges in accurately determining the extent to which environmental conditions affect the data being acquired.

[0005] Therefore, it is desirable to provide a system and method for accurately assessing atmospheric properties in real, unfamiliar, and dynamic environments. Furthermore, other desirable features and characteristics of the invention will become apparent from the following detailed description and appended claims, in conjunction with the accompanying drawings and the foregoing technical and background information. Summary of the Invention

[0006] In various embodiments, systems and methods are provided for evaluating atmospheric characteristics in unfamiliar and dynamic environments and using these characteristics to implement control actions. An exemplary system may include a LIDAR sensor configured to detect distance to an object and the intensity of light reflected by the object. A target selection module of the controller may determine whether the object is a feasible target for evaluating atmospheric characteristics. A data acquisition module may acquire values ​​of distance and intensity detected by the LIDAR sensor. Atmospheric characteristics may be determined based on the acquired distance and intensity values. In response to the determined atmospheric characteristics, actuators may be operated to perform actions.

[0007] In an additional embodiment, determining atmospheric characteristics includes: determining the reflectivity of the object and the extinction coefficient of the environment by a solver module and based on the values ​​of distance and intensity.

[0008] In an additional embodiment, determining atmospheric characteristics includes converting the extinction coefficient into the visibility range of the environment via a conversion module.

[0009] In an additional embodiment, determining atmospheric characteristics includes converting the extinction coefficient into the ambient precipitation intensity via a conversion module.

[0010] In an additional embodiment, the controller is configured to determine the optical properties of an object, including the object's reflectivity.

[0011] In an additional embodiment, the optical properties of an object are determined only after the object is first encountered in the environment.

[0012] In an additional embodiment, the target selection module is configured to reject an object as a feasible target based on its orientation relative to the LIDAR sensor; and to reject an object as a feasible target based on the detected color of the object detected by the camera, using the target selection module.

[0013] In an additional embodiment, determining atmospheric characteristics includes correlating the intensity of light reflected by an object with the distance to the object, the object's reflectivity, and the extinction coefficient of the environment.

[0014] In an additional embodiment, the actuator includes a windshield wiper motor. Atmospheric characteristics include rainfall intensity. Operating the actuator to achieve action includes changing the speed of the windshield wiper motor in response to rainfall intensity.

[0015] In an additional embodiment, collecting values ​​includes collecting values ​​from multiple objects over a period of time, and determining atmospheric characteristics includes determining atmospheric characteristics based on the values ​​from the multiple objects.

[0016] In several other embodiments, a method for assessing atmospheric characteristics in an environment is provided, the method comprising: detecting the distance to an object and the intensity of light reflected by the object using a LIDAR sensor; a target selection module of a controller determining whether the object is a feasible target for assessing the atmospheric characteristics; a data acquisition module of the controller acquiring the distance and intensity values ​​detected by the LIDAR sensor; determining the atmospheric characteristics based on the distance and intensity values; and operating an actuator to perform an action in response to the determined atmospheric characteristics.

[0017] In an additional embodiment, determining atmospheric characteristics includes: determining the reflectivity of the object and the extinction coefficient of the environment by means of the controller's solver module and based on the values ​​of distance and intensity.

[0018] In an additional embodiment, determining atmospheric characteristics includes converting the extinction coefficient into the visibility range of the environment via a conversion module of the controller.

[0019] In an additional embodiment, determining atmospheric characteristics includes converting the extinction coefficient into the ambient precipitation intensity via a conversion module of the controller.

[0020] In an additional embodiment, the controller determines the optical properties of the object, including the object's reflectivity.

[0021] In an additional embodiment, the optical properties of an object are determined only after the object is first encountered in the environment.

[0022] In an additional embodiment, the target selection module rejects objects as feasible targets based on their orientation relative to the LIDAR sensor.

[0023] In an additional embodiment, determining atmospheric characteristics includes correlating the intensity of light reflected by an object with the distance to the object, the object's reflectivity, and the extinction coefficient of the environment.

[0024] In an additional embodiment, the actuator is a windshield wiper motor, and the atmospheric characteristics include rainfall intensity. Operating the actuator to achieve the action includes changing the speed of the windshield wiper motor in response to the rainfall intensity.

[0025] In several other embodiments, the vehicle includes a system for assessing atmospheric characteristics in the environment. A LIDAR sensor is configured to detect the distance to an object and the intensity of light reflected by the object. An actuator is mounted on the vehicle. A controller is carried by the vehicle and configured to: determine whether the object is a feasible target for assessing atmospheric characteristics; acquire distance and intensity values ​​detected by the LIDAR sensor via a data acquisition module; determine atmospheric characteristics based on the distance and intensity values; and, in response to the determined atmospheric characteristics, operate the actuator to achieve movement of the vehicle. Attached Figure Description

[0026] Exemplary embodiments will now be described with reference to the following figures, wherein the same numbers denote the same elements, and wherein:

[0027] Figure 1 This is a functional diagram illustrating a system for evaluating and using atmospheric properties in a vehicle application, based on various exemplary embodiments.

[0028] Figure 2 According to various embodiments Figure 1 The system flowchart;

[0029] Figure 3 Various embodiments are shown and depicted using Figure 1 A schematic diagram of the system's transportation vehicles; and

[0030] Figure 4 It is shown, according to various embodiments, that it can be used Figure 1 A flowchart of a system implementation method for evaluating and using atmospheric properties. Detailed Implementation

[0031] The following detailed description is exemplary in nature only and is not intended to limit application and use. Furthermore, it is not intended to be bound by any express or implied theory set forth in the foregoing technical fields, background art, summary of the invention, or the following detailed description. As used herein, the term "module" refers to any hardware, software, firmware, electronic control components, processing logic, and / or processor device, individually or in any combination, including, but not limited to: application-specific integrated circuits (ASICs), electronic circuits, processors (shared, dedicated, or grouped) and memories executing one or more software or firmware programs, combinational logic circuits, and / or other suitable components providing the described functionality.

[0032] Embodiments of this disclosure may be described herein in terms of functional and / or logical block components and various processing steps. It should be understood that such block components can be implemented by any number of hardware, software, and / or firmware components configured to perform specified functions. For example, embodiments of this disclosure may employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, etc., which can perform various functions under the control of one or more microprocessors or other control devices. Furthermore, those skilled in the art will understand that embodiments of this disclosure can be implemented in conjunction with any number of steering systems, and the transportation system described herein is merely one exemplary embodiment of this disclosure.

[0033] For the sake of brevity, conventional techniques related to signal processing, data transmission, signaling, control, and other functional aspects of the system (and its individual operating components) may not be detailed herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to illustrate exemplary functional relationships and / or physical couplings between various elements. It should be noted that various alternative or additional functional relationships or physical connections may exist in the embodiments of this disclosure.

[0034] In several embodiments, systems and methods are provided for accurately assessing atmospheric characteristics in realistic, unfamiliar, and dynamic environments. For example, a LIDAR system can assess environmental characteristics such as visibility and precipitation intensity without using system pre-calibration based on known objects. Alternatively, environmental characteristics are determined in real time without prior knowledge of what objects might be encountered in the environment and without knowledge of the optical properties of these unknown objects. In embodiments, the attenuation of the LIDAR signal due to environmental conditions is typically determined by tracking multiple objects over a period of time, learning the optical properties of these objects, calculating the signal attenuation due to the environment, and using the degree of attenuation and empirical relationships to determine useful characteristics such as visibility range and precipitation rate, and using these determined characteristics to perform control operations.

[0035] The systems and methods disclosed in this paper provide accurate assessments of environmental characteristics in a variety of environments. Current visibility assessments can be advantageously made without relying solely on static pre-calibration, determined independently of road conditions (e.g., wet roads), and can be made using objects with unknown optical properties such as reflectivity. Previously characterized optical properties of objects can be saved and retrieved to provide rapid assessments or refinements when encountering the same objects in the future.

[0036] In this embodiment, the sensor transmits signals, receives the returned signals, and collects the returned signals as data to select multiple objects (targets) and track feasible targets over a period of time. The data may include the returned signal strength, which is a function of the range to the target. Data for each target may be averaged, and the average value may be used in one or more empirical relationships to determine the target's optical characteristics, such as target reflectivity, from which the atmospheric extinction coefficient can be determined. Values ​​such as visibility distance and precipitation intensity may be determined. The determined values ​​may be used to implement control actions, such as operating actuators (to slow down the vehicle via throttle control and / or to increase the vehicle's guidance / following distance via adaptive cruise control), providing alerts, transmitting information to other users, and for other purposes. In this embodiment, data related to the characterized target may be stored in a reference map for use in future encounters with the same object.

[0037] refer to Figure 1An example of an atmospheric characteristics assessment system 100 for determining environmental characteristics and using these determined characteristics to implement control actions of a vehicle 102 is shown. As will be discussed further herein, the atmospheric characteristics assessment system 100 is capable of achieving accurate assessments of environmental conditions using available sensors. The disclosed atmospheric characteristics assessment system 100 is advantageous in the applications described herein because it can function by targeting unknown objects encountered, rather than relying on predicting what objects will actually be present in the environment. Furthermore, the disclosed atmospheric characteristics assessment system 100 does not rely solely on pre-calibrations based on such predictions. Moreover, the disclosed atmospheric characteristics assessment system 100 does not focus on reading potentially unpredictable road surface information.

[0038] The disclosed atmospheric characteristics assessment system 100 can be used in vehicle applications and other applications where improved performance of sensing systems in variable and complex environments is desired. Therefore, although this disclosure can be described in the context of passenger vehicles, the various features and characteristics disclosed herein can also be used in other contexts and any application where improved sensor / system fidelity is desired. For example, various other control system and electromechanical system environments, as well as different types of moving and stationary systems, can benefit from the features described herein. Thus, no particular feature or characteristic is limited to passenger vehicle or transportation systems; these principles can be equivalently implemented in other vehicles, other machinery or equipment, and other applications.

[0039] In some embodiments, the atmospheric characteristics assessment system 100 is associated with the vehicle 102, such as Figure 1 As shown in the illustration. In various embodiments, vehicle 102 may be an automobile, such as a sedan, SUV, truck, or other land vehicle. In other applications, vehicle 102 may be an aircraft, spacecraft, ship, or any other type of vehicle. In other embodiments, the application may not involve a vehicle but may include a static application of other objects moving in the environment. For illustrative purposes, this disclosure will be discussed in the context of use with vehicle 102. Figure 1 As shown, the vehicle 102 generally includes a body 104, wheels 106, an electrical system 108, and a power system 110. Each wheel 106 is rotatably coupled to the vehicle 102 near a corresponding corner of the body 104. The body 104 may be mounted on or integrated with a chassis and generally surrounds the other components of the vehicle 102. Typically, the electrical system 108 includes a controller 112, a power supply 114, and various coupling components. Typically, the power system 110 includes torque generation devices, such as an internal combustion engine, an electric motor, or a combination thereof, and mechanisms for changing the generated speed / torque amount based on operating conditions.

[0040] It should be understood that vehicle 102 can be any of a wide variety of conventional or autonomous vehicles, such as, for example, sedans, vans, trucks, or sports utility vehicles (SUVs), and can be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD). Vehicle 102 can also incorporate any of a wide variety of propulsion systems or combinations thereof, such as, for example, internal combustion engines that use gasoline or diesel fuel, "flexible fuel vehicle" (FFV) engines (i.e., those using a mixture of gasoline and ethanol), engines that use gaseous compounds (e.g., hydrogen or natural gas), internal combustion engine / electric motor hybrid engines, and electric motors.

[0041] Vehicle 102 includes a steering system 116, which may have a steering actuator 118 and / or a steering wheel 120. In various embodiments, the steering system 116 also includes various other features (not listed here). Figure 1 (as shown in the diagram), thereby enabling the desired articulation angles, such as the angle between the intermediate connecting shaft and the tie rod. The steering actuator 140 can enable steer-by-wire and / or autonomous steering, which uses electrical and / or electromechanical systems to control the vehicle's steering in response to or in place of the conventional steering wheel 120.

[0042] The atmospheric characteristics assessment system 100 also includes a sensor suite 122 with one or more sensors that sense observable environmental or other conditions associated with the vehicle 102. The sensor suite 122 is coupled to a controller 112. In this embodiment, the sensor suite includes, but is not limited to, a LIDAR sensor 124 and a camera 126. The LIDAR sensor 124 emits a near-infrared beam. The beam can be reflected by objects in its path and return to the detector of the LIDAR sensor 124. Components (not shown) of the LIDAR sensor 124 may include a transmitter and a receiver. The transmitter of the LIDAR sensor 124 emits light that is reflected back to the receiver of the LIDAR sensor 124 when it touches a nearby object. Typically, the atmospheric characteristics assessment system 100 receives, records, and processes information about the round-trip data of the beam, which may include measuring the return intensity, distance, and time. The atmospheric characteristics assessment system 100 can use the data acquired by the LIDAR sensor 124 to present a three-dimensional representation of the environment surrounding the vehicle 102. The camera 126 provides a two-dimensional optical image of the same environment, thus providing additional data, including the color of sensed objects. LiDAR sensor 124 and camera 126 capture complementary information about the environment. This information can be co-registered by calibrating the two sensors, such as by evaluating a rigid body transformation between their reference coordinate systems. The rigid body transformation allows the three-dimensional points of the LiDAR sensor 124's coordinate system to be reprojected using the two-dimensional coordinate system of camera 126. The co-registered camera images and LiDAR data can then be used to construct a dynamic map incorporating environmental features.

[0043] The atmospheric characteristics assessment system 100 includes an actuator system 128 that can be used to implement actions of the vehicle 102, including responding to data acquired by the sensor suite 122 and determinations made by the controller 112 based on that data. Thus, the actuator system 128 is communicatively coupled to the controller 112. In this embodiment, the actuator system 128 includes a throttle valve 130 of the powertrain 110, an adaptive cruise control actuator 132, an operator interface 134, a windshield wiper actuator 136, a light 138, a steering actuator 140, and a transmitter 142. In other embodiments, any number of other actuators may be coupled to the controller 112. The throttle valve 130 may be a valve plate actuator, a motor controller, or other actuators such as those that change the output of the powertrain 110 by altering speed and / or output torque. The adaptive cruise control actuator 132 may be a cruise control controller or other devices that control aspects of the cruise system such as guide / follow distance, speed, or other parameters. The operator interface 134 may be a visual display, an audio speaker, a haptic actuator, or other human-machine interface that provides output that can be felt by a human operator. The windshield wiper actuator 136 may be an electric motor, or a motor operated by other means, for driving the wipers at a variable speed. The light 138 may be a headlight (including high beam and low beam), a taillight, a hazard light, or other light for illumination and / or warning purposes. The steering actuator 140 may be an electric motor or other actuator for controlling the angle of the front wheels 106. The transmitter 142 may be a cellular device or other wireless / radio device for transmitting information; in several embodiments, it may be a transceiver with bidirectional communication capabilities.

[0044] Controller 112 receives various signals from sensor suite 122 and controls the operation of atmospheric characteristic assessment system 100 based on these signals, including making determinations and implementing control of actuator system 128 in response to these determinations. Typically, controller 112 generates control signals that are transmitted to actuator system 128 to control the response of various actuators, for example, to implement operation in operating / driving vehicle 102. In various embodiments, controller 112 includes any number of modules 144 that are communicatively coupled to each other and to other aspects of atmospheric characteristic assessment system 100, such as via a communication bus. The control logic of atmospheric characteristic assessment system 100 may reside on any one of control modules 144 and / or reside in one or more controllers. For example, vehicle 102 may include more control modules 144 to control aspects such as atmospheric characteristic assessment system 100 (including actuator system 128), along with power system 110, body 104, braking of wheels 106, and other functions and system aspects of vehicle 102. Alternatively, one or more network communication protocols, such as CAN or Flexray communication, can be used to interface between the various control modules 144 and other devices in the vehicle 102.

[0045] Typically, the atmospheric characteristics assessment system 100 includes a control system 146 that can generally be operated by a controller 112. The controller 112 can be configured as any number of interconnecting controllers and / or microcontrollers. The controller 112 is coupled to each of a power supply 114 (which may include a battery), a sensor suite 122, and an actuator system 128, and may be coupled to other devices of the vehicle 102. The controller 112 can accept information from various sources, process that information, and provide control commands based on that information to achieve results such as the operation of the vehicle 102 and its systems (including the atmospheric characteristics assessment system 100). In the illustrated embodiment, the controller 112 includes a processor 150 and a memory device 152, coupled to a storage device 154. The processor 150 performs the computational and control functions of the controller 112 and may include any type of processor or multiple processors, a single integrated circuit such as a microprocessor, or any suitable number of integrated circuit devices and / or circuit boards working together to perform the functions of a processing unit. During operation, processor 150 may execute one or more programs 156 via module 144 and may use data 158, all of which may be contained within storage device 154. Processor 150 thereby controls the overall operation of controller 112 to perform the processes described herein, such as in the following combinations. Figure 4 The process is described further.

[0046] Memory device 152 can be any suitable type of memory. For example, memory device 152 can include volatile and non-volatile storage devices such as read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is persistent or non-volatile memory that can be used to store various operational variables when processor 150 is powered off. Memory device 152 can be implemented using any of a variety of known memory devices, such as PROM (programmable read-only memory), EPROM (electrical PROM), EEPROM (electrically erasable PROM), flash memory, or any other electrical, magnetic, optical, or combined memory device capable of storing data, some of which represents executable instructions used by controller 112. In some embodiments, memory device 152 may reside on and / or co-reside with processor 150 on the same computer chip. In the illustrated embodiment, memory device 152 may store the program 156 described above, as well as one or more stored values ​​such as data 158 for short-term data access.

[0047] Storage device 154 stores data 158, such as data for long-term data access, for use in the automated control of vehicle 102 and its systems. Storage device 154 can be any suitable type of storage device, including direct-access storage devices such as hard disk drives, flash memory systems, floppy disk drives, and optical disk drives. In one exemplary embodiment, storage device 154 includes a source of a program 156 from which a memory device 152 receives data, which performs one or more embodiments of one or more processes of this disclosure, such as in the following combinations. Figure 4The steps of process 400 (and any of its subprocesses) are discussed further. In another exemplary embodiment, program 156 may be stored directly in memory device 152 and / or otherwise accessed through memory device 152. Program 156 represents executable instructions of electronic controller 112 for processing information and controlling vehicle 102 and its systems (including atmospheric characteristics assessment system 100). Instructions may include one or more separate programs 156, each including an ordered list of executable instructions for implementing logical functions. When executed by processor 150, the instructions support the reception and processing of signals such as those from sensors, and the execution of logic, calculations, methods, and / or algorithms for automatically controlling components and systems of vehicle 102. Processor 150 may generate control signals for actuator system 128 to automatically control various components and systems of vehicle 102 based on logic, calculations, methods, and / or algorithms. It should be understood that storage device 154 for data 158 may be part of controller 112, separate from controller 112, part of one or more controllers, or part of multiple systems. Memory device 152 and data storage device 154 work together with processor 150 to access and use program 156 and data 158.

[0048] Although the components of control system 146 are depicted as part of the same system, it should be understood that in some embodiments, these features may include multiple systems. Additionally, in various embodiments, control system 146 may include all or part of a variety of other vehicle equipment and systems, and / or may be coupled to a variety of other vehicle equipment and systems, such as atmospheric characteristics assessment system 100 and / or other systems of vehicle 102.

[0049] exist Figure 2 In the illustrated embodiment, the configuration of the control system 146 may include multiple modules 144. Module 144 may include a target selection module 202 for evaluating and selecting feasible objects for the atmospheric characteristics assessment system 100. Various information may be provided to the target selection module 202, for example, from sensor suite 122 (e.g., LiDAR sensor 124, camera 126) and data storage area 204, for identifying objects as targets for further evaluation. Data storage area 204 may reside in, or may include, data storage device 154 or other devices, and may be a source of data 158 and programs 156 used by the various modules 144. Association module 206 may evaluate the potential association between the identified target and previously encountered and evaluated targets that may have been previously stored in data storage area 204. Data acquisition module 208 manages data acquisition. Data may be acquired over a period of time from multiple targets at various distances (ranges) from vehicle 102.

[0050] The solver module 210 can perform calculations using available data 158 and program 156, such as data accessible from data storage area 204. LIDAR intensity can be recorded as the returned intensity of the emitted beam and is typically related to the reflectivity (an optical property) of the target object. The solver module 210 can utilize empirical relationships between the returned signal intensity, distance to the target, target reflectivity, and ambient extinction coefficient to determine the characteristics of the selected target (e.g., reflectivity) and useful environmental characteristics (e.g., extinction coefficient). The determined characteristics of the selected target can be stored in data storage area 204 at its GPS location within a map for later reference, such as by the association module 206. In various embodiments, data 158 can be stored in map, tabular, or other forms and includes values ​​such as location and reflectivity corresponding to the evaluated target for future identification and retrieval.

[0051] The conversion module 212 converts the determined environmental characteristics into useful parameters. For example, the determined extinction coefficient (also known as attenuation coefficient) can be converted into the visibility range and / or precipitation intensity in the environment. The output control module 214 can transmit the parameters to the user, or can use the parameters to generate control signals to initiate control actions such as operating the actuator system 128 to initiate the vehicle 102. The foregoing arrangement of module 144 is an example, and this disclosure is not limited to the exemplary arrangement. Additionally, other modules or submodules may be used in the control scheme / algorithm of the control system 146 for the same or other functions or for cooperative purposes.

[0052] Additionally, refer to Figure 3 The scenario shows vehicle 102 as the primary vehicle operating on road 302. The environment 304 in which vehicle 102 operates can be characterized by a number of characteristics, including, in this embodiment, the presence of precipitation 306. Multiple objects may be present in environment 304, such as other vehicles 308 and other objects 311-315. These objects may be unknown, meaning they may not have been encountered before, their optical properties are unknown, and their suitability as targets for determining environmental characteristics is unknown. To provide useful information for vehicle operation, available objects 308 and 311-315 within the range of sensor suite 122 can be considered as targets. Utilizing input from LIDAR sensor 124 and camera 126, atmospheric characteristics assessment system 100 considers available objects, such as through target selection module 202. Criteria for selecting objects as feasible targets may include shape, color, surface homogeneity, orientation, and other factors that influence the ability to determine the object's optical properties, such as reflectivity. For sensor kit 122, it is preferred to give preference to objects that exhibit uniform optical properties, and can ignore or reject objects with highly varying light intensity.

[0053] In this embodiment, the target selection module 202 considers the shape of the object, giving preference to relatively easily identifiable shapes, such as spheres (object 311), cylinders (object 312), flat signs (object 313), and rectangles / walls (object 315). Therefore, after applying the shape filtering filter, objects 311, 312, 313, and 315 can remain as candidates for potential targets. Other vehicles 318 and irregular shrubs (object 314) may be rejected as target candidates due to their complex shapes, which may tend to reflect light in multiple directions, including away from the main vehicle 102. Input from the camera 126 can be used to consider the color consistency of the objects, giving preference to those with consistent colors. Therefore, objects with multiple shadows / colors may be rejected due to their uneven reflectivity. Furthermore, objects made of multiple materials with different optical properties may be rejected due to inconsistent reflectivity. Additionally, the orientation of the object is considered. Objects that are typically oriented toward the main vehicle 102 are given preference so that light is consistently reflected back toward the main vehicle 102 as the main vehicle 102 moves. For example, if object 313 (road sign) is lateral to road 302, it may be rejected as a target candidate due to the low intensity level of the returned beam reaching the LIDAR sensor 124.

[0054] refer to Figure 4 A flowchart of a process 400 including an atmospheric characteristics assessment method is shown. According to an exemplary embodiment, process 400 can be combined with... Figures 1 to 3 The vehicle 102 and the atmospheric characteristics assessment system 100 are used. As can be understood from this disclosure, the sequence of operations within process 400 is not limited to... Figure 4 The steps shown are not performed in the order shown, but may be performed in one or more different orders as applicable and in accordance with this disclosure. Furthermore, process 400 may include fewer steps than all shown, and / or may include other steps / operations.

[0055] Process 400 can be initiated 402 when vehicle 102 and atmospheric characteristics assessment system 100 are operating in a given environment. Atmospheric characteristics assessment system 100 can operate continuously or intermittently, or it can be triggered by other inputs, such as based on weather conditions, lighting conditions, or other factors. For example, process 400 can be initiated 402 automatically, or it can be initiated in response to a signal indicating that environmental conditions may deteriorate. Process 400, such as through target selection module 202, considers objects 404 detected in the point cloud of LIDAR sensor 124.

[0056] 404 available objects can be considered, and a group of multiple objects that best match the definition criteria of feasible targets can be selected. As mentioned above, the criteria for selecting objects as targets can include shape, color, surface uniformity, orientation, and other factors that affect the ability to determine the optical properties of an object (such as consistent reflectivity). Objects with shapes that help determine their optical properties are considered target candidates. Objects with consistent shapes (spheres, cylinders, rectangles, wall planes, etc.) are acceptable. Objects without consistent shapes may be rejected. Objects exhibiting reflected light intensity variations above a threshold may be discarded as candidates (406). For example, an object that, as a reflected light source, does not uniformly distribute the reflected light back toward the main vehicle 102 may be rejected. The threshold can be set based on modeling or characteristic testing for a given application and can be retrieved from data storage area 204. Objects that are not typically oriented toward the main vehicle 102 may be rejected (408). For example, an object may be rejected as a candidate (408) when the angle between the surface normal of the object and the line connecting it to the main vehicle exceeds a threshold. A threshold, such as forty-five degrees, can be set for the amplitude at which insufficient light reflects towards the main vehicle 102. This threshold can be set based on modeling or characteristic testing for a given application and can be retrieved from data storage area 204. Objects exhibiting color changes exceeding the threshold may be discarded 410. For example, using input from camera 126, the target selection module may discard 410 objects whose color changes do not support easily identifiable optical characteristics. The threshold can be set based on modeling or characteristic testing for a given application and can be retrieved from data storage area 204.

[0057] Once a set of targets has been selected, process 400 continues to determine whether the selected targets (412) match existing objects stored in the data storage area 204, such as the area where vehicle 102 operates. If the determination is negative, meaning the selected target does not match a stored object, process 400 continues to track the target and acquire data (414) such as via data acquisition module 208. The reflection intensity and distance of each target are recorded within a time window at different ranges (distances) from the main vehicle 102. The time window is set based on object availability and scene movement speed. For example, when vehicle 102 is traveling at high speed, the time window can be relatively short (e.g., 1-2 seconds), while when vehicle 102 is traveling at relatively low speed, the time window can be longer, lasting several seconds. The recorded intensity and distance are stored in pairs in the data storage area 204, with the intensity value recorded as a function of the range (distance between vehicle 102 and the target object).

[0058] Using data collected for the target, the reflectivity of the target object and the extinction factor of the environment can be determined through a solution module 210, etc. Intensity p, distance z, target reflectivity ρ, and environmental extinction factor α are determined through empirical relationships. Related. Assuming the extinction coefficient α is constant, solve for the relationship between the extinction coefficient α and reflectivity ρ given multiple measurements of intensity p and distance z. Each different target will have a different reflectivity value ρ. C is a known value from the LIDAR sensor 124 specification. Considering two unknown parameters (target reflectivity ρ and ambient extinction coefficient α) and multiple target objects (M):

[0059] Let θ T =(α ρ1 … ρ M Let Z be the unknown parameters of M objects, and let Z = [z...]. ij ] and P = [p ij [ ] is an N×M matrix representing the j-th distance and intensity measurement of object i.

[0060] General Explanation Given as follows:

[0061]

[0062] It can be solved using any constrained optimization method, such as the solver module 210, to obtain the reflectivity of the target and the extinction coefficient of the environment.

[0063] Alternatively, the solver module 210 can use a linear least squares method that requires less computational power, such as by the following formula:

[0064] make and but

[0065]

[0066] for and Where e i Let i be the N-dimensional basis vector at coordinate i, and Where q i It is the index of the object corresponding to an element in the vector (Z).

[0067] The following yields a more numerically stable solution:

[0068]

[0069] Where λ is the regularization parameter.

[0070] The first solution value can be initialized using the methods described above, and constraints can be introduced using methods such as clipping solutions. If the reflectance coefficients of some target objects are known, such as those from the map in data storage area 204, they can be treated as constants to simplify the optimization process, or previous evaluations can be fused with newly acquired data to improve the saved map values. In several embodiments, the solution value can be obtained iteratively using methods such as Kalman filters, and the results can be made more stable by using algorithms such as random sampling consensus.

[0071] With the reflectivity of the target object determined 416, the value for that specific object can be stored in a data storage area, such as 204, for later retrieval. The object's data can be stored along with its corresponding GPS coordinates to obtain precise location information. For this purpose, the description of process 400 now returns to step 412. When determination 412 is positive, meaning the object matches the object stored in data storage area 204, process 400 continues to retrieve 422 the stored reflectivity of the object at the given GPS coordinates. Process 400 can then track and acquire data 414, specifically regarding the object's intensity and distance. The extinction factor 416 can then be determined without solving for the reflectivity. However, as mentioned above, the stored reflectivity values ​​of the object can be refined using the data, and once refined, can be re-stored as needed 418.

[0072] Proceeding to step 420, process 400, such as using transformation module 212, transforms the determined value of 416 into a useful parameter. For example, the empirical relation α = aR can be used. b The extinction coefficient α is converted to a rainfall rate R, where constant a = 0.01 and constant b = 0.6. This can be used... The evaluation value of the extinction coefficient α is converted to 420 to the visibility distance x (where the attenuation is caused by water vapor, and other constants can be used depending on the cause of atmospheric attenuation).

[0073] A dynamic object map overlay can be created using the collected data and can be transmitted for aggregation with other vehicle inputs. Thus, process 400 may include sharing data (including object maps) with other nearby vehicles, such as via vehicle-to-vehicle communication, to the cloud via cellular signals or other mechanisms. Transmitter 142 can be used for external communication with vehicle 102. Further data fusion can be performed on other vehicles and / or other remote resources and can be further shared, including in available route planning and information applications. For example, collected data and determination results can be transmitted to warn against driving in areas with limited visibility. Process 400 can continue while vehicle 102 is operating or can terminate 424, such as when vehicle 102 loses power or when atmospheric characteristics assessment is no longer necessary.

[0074] Information such as converting 420 to precipitation intensity and visibility range can be used for control actions. For example, refer to... Figures 1 to 3 The controller 112 can adjust the throttle valve 130 of the powertrain 110 according to conditions, such as rainfall intensity and / or visibility range. In another embodiment, the controller 112 can adjust the adaptive cruise control actuator 132, for example, by sending signal 222, using rainfall intensity and / or visibility range. For example, the guide distance between the primary vehicle 102 and the vehicle 303 can be increased. In some embodiments, the operator interface 134 can be activated by the controller 112 to provide warnings and / or suggestions for action to the operator of the vehicle 102 based on the current conditions, using rainfall intensity and / or visibility range.

[0075] In several embodiments, controller 112 can adjust the speed of windshield wiper actuator 136 proportionally to precipitation intensity via signal 226. In another embodiment, controller 112 can adjust light 138 (high beam, low beam, or hazard lights) in response to precipitation intensity and / or visibility distance via signal 228. Controller 112 can operate steering actuator 140 via signal 230. For example, in snowy conditions, autonomous steering can be altered to achieve a different steering rate than used in dry conditions.

[0076] Therefore, by evaluating available objects, including unknown objects with unknown optical properties, LIDAR sensors can be used to determine atmospheric characteristics useful for making control decisions. The disclosed system can operate effectively in dynamic environments with moving vehicles surrounded by moving and unknown objects. Furthermore, effective results are achieved regardless of the presence of wet, snowy, icy, or poorly maintained roads. Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that numerous variations exist. It should also be understood that the exemplary embodiments or multiple exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of this disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient roadmap for implementing the exemplary embodiments or multiple exemplary embodiments. It should be understood that various changes can be made to the function and arrangement of the elements without departing from the scope of this disclosure as set forth in the appended claims and their legal equivalents.

Claims

1. A system for assessing atmospheric properties in an environment, the system comprising: A light detection and ranging LIDAR sensor is configured to detect the distance to an object and the intensity of light reflected by the object; Actuator; and The controller is configured as follows: The target selection module determines whether the object is a feasible target for evaluating the atmospheric characteristics. The data acquisition module acquires the values ​​of the distance and the intensity detected by the LIDAR sensor; The atmospheric characteristics are determined based on the values ​​of the distance and the intensity. as well as In response to the determined atmospheric characteristics, the actuator is operated to achieve the action. The target selection module is configured as follows: Based on the object's orientation relative to the LIDAR sensor, the object is rejected as a feasible target; and The target selection module rejects an object as a feasible target based on the color of the object detected by the camera.

2. The system of claim 1, wherein determining the atmospheric characteristics comprises: The reflectivity of the object and the extinction coefficient of the environment are determined by the solution module based on the values ​​of the distance and the intensity.

3. The system of claim 2, wherein determining the atmospheric characteristics further includes: The extinction coefficient is converted into the visibility range of the environment using a conversion module.

4. The system of claim 2, wherein determining the atmospheric characteristics further comprises: The extinction coefficient is converted into the precipitation intensity of the environment through a conversion module.

5. The system of claim 1, wherein the controller is configured to determine the optical properties of the object, including the reflectivity of the object.

6. The system of claim 1, wherein acquiring the value includes acquiring the value of a plurality of objects over a period of time, and wherein determining the atmospheric characteristic includes determining the atmospheric characteristic based on the value of the plurality of objects.

7. A method for assessing atmospheric properties in an environment, the method comprising: The distance to an object and the intensity of light reflected by the object are detected using a light detection and ranging LIDAR sensor. The target selection module of the controller determines whether the object is a feasible target for evaluating the atmospheric characteristics. The controller's data acquisition module acquires the distance and intensity values ​​detected by the LIDAR sensor. The atmospheric characteristics are determined based on the values ​​of the distance and the intensity. as well as In response to the determined atmospheric characteristics, the actuator is operated to achieve the action. The target selection module is configured as follows: Based on the object's orientation relative to the LIDAR sensor, the object is rejected as a feasible target; and The target selection module rejects an object as a feasible target based on the color of the object detected by the camera.

8. The method of claim 7, wherein determining the atmospheric characteristics comprises: The reflectivity of the object and the extinction coefficient of the environment are determined by the solver module of the controller based on the values ​​of the distance and the intensity.

9. The method of claim 8, wherein determining the atmospheric characteristics further comprises: The extinction coefficient is converted into the precipitation intensity of the environment through the conversion module of the controller.

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