Methods and systems for vehicle radar coordination and interference reduction

Abstract

To provide a method that includes receiving data by a vehicle from an external computing device indicative of at least one other vehicle in an environment of the vehicle.SOLUTION: The vehicle may include a sensor configured to detect the environment of the vehicle. At least one other vehicle may include at least one sensor. The method also includes determining a likelihood of interference between the at least one sensor of the at least one other vehicle and the sensor of the vehicle. The method also includes initiating an adjustment of the sensor to reduce the likelihood of interference between the sensor of the vehicle and the at least one sensor of the at least one other vehicle in response to the determination.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No. 62 / 043301, filed August 28, 2014, the entirety of which is incorporated herein by reference. [Background technology]

[0002]

[0002] Unless otherwise indicated in this specification, the materials described in this section are not prior art to the claims of this application and are not admitted to be prior art by inclusion in this section.

[0003]

[0003] Radio detection (RADAR) systems can be used to actively estimate the range, angle, and / or Doppler frequency shift relative to environmental features by emitting radio signals and detecting the returning reflected signals. The distance to a radio-reflective feature can be determined as a function of the time delay between transmission and reception. Radar systems can emit signals whose frequency varies over time, such as signals with a time-varying frequency ramp, and then relate the frequency difference between the emitted and reflected signals to a range estimate. Some systems can also estimate the relative motion of reflective objects based on the Doppler frequency shift in the received reflected signals.

[0004]

[0004] In some examples, directional antennas can be used to transmit and / or receive signals to associate each range estimate with a bearing. More generally, directional antennas can also be used to focus radiated energy onto a given field of interest. Combining measured distance and direction information can map surrounding environmental features. In other examples, omnidirectional antennas can alternatively be used. In these examples, the receiving antenna may have a 90-degree field of view and can be configured to use multiple channels with phase offsets to determine the angle of arrival of the received signal. Thus, for example, radar sensors can be used by autonomous vehicle control systems to avoid obstacles indicated by sensor information.

[0005] Some example automotive radar systems may be configured to operate in the 76-77 gigahertz (GHz) electromagnetic frequency range. These radar systems may also use a transmitting antenna that can focus radiated energy into a narrow beam, allowing a receiving antenna (e.g., with a wide beam) in the radar system to measure the vehicle's environment with high accuracy. Summary of the Invention

[0006] In one example, a vehicle is provided that includes a sensor configured to detect an environment of the vehicle based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment. The vehicle may also include a controller configured to receive data from an external computing device indicative of at least one other vehicle in the vehicle's environment, the at least one other vehicle including at least one sensor. The controller may also be configured to determine, based on the data, a likelihood of interference between at least one sensor of the at least one other vehicle and a sensor of the vehicle. The controller may also responsively initiate adjustments of the sensor to improve correlation between the sensor of the vehicle and the at least one sensor of the at least one other vehicle. It can also be configured to reduce the likelihood of interference.

[0007] In another example, a method is provided that includes a vehicle receiving data from an external computing device indicative of at least one other vehicle in the vehicle's environment. The at least one other vehicle can include at least one sensor. The vehicle can include a sensor configured to detect the vehicle's environment based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment. The method further includes determining, based on the data, a likelihood of interference between at least one sensor of the at least one other vehicle and a sensor of the vehicle. The method further includes initiating an adjustment of the sensor based on the likelihood being greater than a threshold likelihood. The adjustment can reduce the likelihood of interference between the sensor of the vehicle and at least one sensor of the at least one other vehicle.

[0008] In yet another example, a method is provided that includes receiving data from a plurality of vehicles by a computing device including one or more processors. The data may be indicative of configuration parameters of sensors in the plurality of vehicles. The data may also be indicative of locations of the plurality of vehicles. A given sensor of the given vehicle may be configured to detect an environment of the given vehicle based on a comparison of electromagnetic (EM) radiation transmitted by the given sensor and reflections of the EM radiation from one or more objects in the environment of the given vehicle. The method further includes determining, based on the data, that the given vehicle is within a threshold distance to at least one other vehicle. The method further includes responsively determining, based on the configuration parameters, a likelihood of interference between at least one sensor of the at least one other vehicle and the given sensor of the given vehicle. The method further includes providing, by the computing device, a request to the given vehicle to adjust a given configuration parameter of the given sensor to reduce a likelihood of interference between the given sensor of the given vehicle and at least one sensor of the at least one other vehicle. The providing of the request may be based on the likelihood being greater than the threshold likelihood.

[0009] In yet another example, a system is provided in which a vehicle includes means for receiving data from an external computing device indicative of at least one other vehicle in the vehicle's environment. The at least one other vehicle may include at least one sensor. The vehicle may include a sensor configured to detect the vehicle's environment based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment. The system further includes means for determining, based on the data, a likelihood of interference between at least one sensor of the at least one other vehicle and a sensor of the vehicle. The system further includes means for initiating an adjustment of the sensor based on the likelihood being greater than a threshold likelihood. The adjustment can reduce the likelihood of interference between the sensor of the vehicle and at least one sensor of the at least one other vehicle.

[0010] In yet another example, a system is provided that includes means for receiving data from a plurality of vehicles by a computing device including one or more processors. The data may be indicative of configuration parameters of sensors in the plurality of vehicles. The data may also be indicative of the locations of the plurality of vehicles. A given sensor in a given vehicle may be configured to detect the environment of the given vehicle based on a comparison of electromagnetic (EM) radiation transmitted by the given sensor with reflections of the EM radiation from one or more objects in the environment of the given vehicle. The system further includes means for determining, based on the data, that the given vehicle is within a critical distance to at least one other vehicle. The system further includes means for responsively determining, based on the configuration parameters, a likelihood of interference between at least one sensor of the at least one other vehicle and the given sensor of the given vehicle. The system adjusts a given configuration parameter of the given sensor to enhance the likelihood of interference between the given sensor of the given vehicle and the at least one other vehicle. The method further includes means for the computing device to provide a request to the given vehicle to reduce a likelihood of interference with at least one sensor of the vehicle, the providing of the request being based on the likelihood being greater than a limit likelihood.

[0011]

[0011] These and other aspects, advantages, and alternatives will become apparent to those skilled in the art from a reading of the following detailed description in conjunction with the accompanying drawings, where applicable. [Brief explanation of the drawings]

[0012] [Figure 1] 1 illustrates a vehicle according to an example embodiment. [Figure 2]

[0013] 1 is a simplified block diagram of a vehicle according to an example embodiment; [Figure 3]

[0014] FIG. 1 is a simplified block diagram of a system according to an example embodiment. [Figure 4]

[0015] FIG. 1 is a block diagram of a method according to an example embodiment. [Figure 5]

[0016] FIG. 10 is a block diagram of another method according to an example embodiment. [Figure 6]

[0017] 1 illustrates multiple vehicles in a vehicle environment including sensors according to an example embodiment. [Figure 7]

[0018] FIG. 1 is a simplified block diagram of a sensor according to an example embodiment. [Figure 8]

[0019] 1 illustrates a modulation pattern of electromagnetic (EM) radiation from a sensor according to an example embodiment. [Figure 9A]

[0020] An example scenario is presented for adjusting the modulation pattern of EM emissions from a sensor to reduce interference with other sensors, in accordance with at least some embodiments herein. [Figure 9B]

[0020] In accordance with at least some embodiments herein, an example scenario is presented for adjusting the modulation pattern of EM emissions from a sensor to reduce interference with other sensors. [Figure 9C]

[0020] In accordance with at least some embodiments herein, an example scenario is presented for adjusting the modulation pattern of EM emissions from a sensor to reduce interference with other sensors. [Figure 9D]

[0020] In accordance with at least some embodiments herein, an example scenario is presented for adjusting the modulation pattern of EM emissions from a sensor to reduce interference with other sensors. [Figure 9E]

[0020] In accordance with at least some embodiments herein, an example scenario is presented for adjusting the modulation pattern of EM emissions from a sensor to reduce interference with other sensors. [Figure 10]

[0021] 1 depicts an example of a computer-readable medium configured in accordance with an example embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013]

[0022] The following detailed description describes various features and functions of the disclosed systems and methods in connection with the accompanying drawings. In the drawings, like symbols identify like components unless the context dictates otherwise. The exemplary system, apparatus, and method embodiments described herein are not intended to be limiting. Those skilled in the art will readily appreciate that certain aspects of the disclosed systems, apparatus, and methods can be arranged and combined in a wide variety of different configurations, all of which are contemplated herein.

[0014]

[0023] Efforts to improve vehicle safety are continually underway, including the development of autonomous vehicles equipped with accident prevention systems that may have the ability to avoid accidents. Autonomous vehicles may include various sensors, such as radio wave detection (RADAR) sensors and light detection and ranging (LIDAR) sensors, among other possibilities, to detect obstacles and / or other vehicles in the autonomous vehicle's environment, thereby facilitating accident prevention. However, more As more vehicles employ such accident prevention systems and the density of sensor-equipped vehicles increases, interference between sensors can reduce the accuracy and effectiveness of the sensors for use in accident prevention.

[0015]

[0024] Within examples, systems and methods herein can be configured to adjust a vehicle's sensor to reduce the likelihood of interference between the sensor and other sensors of other vehicles. As an example, a vehicle herein can include a sensor configured to detect the vehicle's environment. The vehicle can further include a controller configured to receive data from an external computing device indicative of at least one other vehicle in the vehicle's environment. The external computing device can be, for example, a server that wirelessly communicates with the vehicle and other vehicles in the environment. In one case, the controller can be configured to determine, based on the data, that at least one sensor of at least one other vehicle is pointed toward the vehicle's sensor. In another case, the controller can be configured to determine that the vehicle and at least one other vehicle are within a critical distance from each other, thereby increasing the likelihood of interference. Thus, for example, the data can include the location of the at least one other vehicle and / or the orientation of the at least one sensor. The controller can also be configured to responsively initiate a sensor adjustment to reduce the likelihood of interference between the vehicle's sensor and at least one sensor of at least one other vehicle.

[0016]

[0025] Various adjustments of the sensor are possible, such as adjusting the sensor's orientation, output, modulation pattern, or any other parameter, to reduce interference with at least one sensor of at least one other vehicle.

[0017]

[0026] Alternatively, in some examples, the external computing device may receive configuration parameters of the vehicle's sensors and other sensors of other vehicles in the vicinity of the vehicle. In these examples, the external computing device may provide instructions to the vehicle and / or other vehicles with appropriate adjustments to the corresponding sensors to reduce interference between the various sensors. Thus, in some embodiments, some of the above-described functions for the vehicle may alternatively be performed by the external computing device depending on various conditions, such as network latency between the external computing device and the vehicle, or other safety considerations.

[0018]

[0027] The embodiments disclosed herein can be used on any type of vehicle, including conventional automobiles and automobiles with autonomous modes of operation. However, the term "vehicle" should be interpreted broadly to cover any moving object, including, for example, a truck, van, semi-trailer truck, motorcycle, golf cart, off-road vehicle, warehouse transport vehicle, or farm vehicle, as well as a tracked vehicle such as a roller coaster, trolley, streetcar, or train car, among other examples.

[0019]

[0028] Referring now to the drawings, FIG. 1 illustrates a vehicle 100 according to an example embodiment. In particular, FIG. 1 illustrates right side, front, rear, and top views of vehicle 100. Vehicle 100 is illustrated in FIG. 1 as an automobile, although, as noted above, other embodiments are possible. Additionally, although this example vehicle 100 is illustrated as a vehicle that can be configured to operate in an autonomous mode, the embodiments described herein are also applicable to vehicles that are not configured to operate autonomously. Accordingly, this example vehicle 100 is not intended to be limiting.

[0020]

[0029] As shown, the vehicle 100 includes a first sensor unit 102, a second sensor unit 104, a third sensor unit 106, a wireless communication system 108, and a camera 11. 0. Each of the first, second, and third sensor units 102-106 may include any combination of global positioning system sensors, inertial measurement units, radio wave detection (RADAR) units, laser range finders, light detection and ranging (LIDAR) units, cameras, and acoustic sensors. Other types of sensors are possible.

[0021]

[0030] Although the first, second, and third sensor units 102-106 are shown mounted in particular locations on the vehicle 100, in some embodiments, the sensor units 102-106 may be mounted elsewhere on the vehicle 100, either inside or outside the vehicle 100. For example, the sensor units may be mounted on the rear of the vehicle (not shown in FIG. 1 ). Additionally, while only three sensor units are shown, in some embodiments, more or fewer sensor units may be included on the vehicle 100.

[0022]

[0031] In some embodiments, one or more of the first, second, and third sensor units 102-106 may include one or more movable mounts (e.g., "steering gear") on which sensors may be movably mounted. The movable mount may include, for example, a swivel base. A sensor mounted on a swivel base may rotate so that the sensor can obtain information from various directions around the vehicle 100. Alternatively or additionally, the movable mount may include a tilt base. A sensor mounted on a tilt base may tilt within a particular range of angles and / or azimuth angles so that the sensor can obtain information from various angles. The movable mount may take other forms as well.

[0023]

[0032] Additionally, in some embodiments, one or more of the first, second, and third sensor units 102-106 may include one or more actuators configured to adjust the position and / or orientation of the sensor within the sensor unit by moving the sensor and / or the movable mount. Examples of actuators include motors, pneumatic actuators, hydraulic pistons, relays, solenoids, and piezoelectric actuators. Other actuators are possible.

[0024]

[0033] The wireless communication system 108 may be any system configured to wirelessly couple to one or more other vehicles, sensors, or other entities, either directly or through a communication network. To this end, the wireless communication system 108 may include an antenna and a chipset for communicating with other vehicles, sensors, servers, or other entities, either directly or through a communication network. The chipset or wireless communication system 108 may generally be arranged to communicate according to one or more types of wireless communication (e.g., protocols), such as Bluetooth, a communication protocol described in IEEE 802.11 (including any IEEE 802.11 revisions), cellular technologies (such as GSM, CDMA, UMTS, EV-DO, WiMAX, or LTE), Zigbee, dedicated short-range communications (DSRC), and radio frequency identification (RFID) communications, among other possibilities. The wireless communication system 108 may also take other forms.

[0025]

[0034] Although the wireless communication system 108 is shown positioned on the roof of the vehicle 100, in other embodiments the wireless communication system 108 may be located in whole or in part elsewhere.

[0026]

[0035] Camera 110 can be any camera (e.g., a still camera, a video camera, etc.) configured to acquire images of the environment in which vehicle 100 is located. To this end, camera 110 can be configured to detect visible light or to detect light from other parts of the spectrum, such as infrared or ultraviolet. Other types of cameras are possible. Camera 110 can be a two-dimensional detector or can have three-dimensional spatial coverage. In some embodiments, camera 110 can be, for example, a camera The camera 110 may be a range detector configured to generate a two-dimensional image showing the distance from the camera 110 to several points in the environment. To this end, the camera 110 may use one or more range detection techniques. For example, the camera 110 may use a structured light technique in which the vehicle 100 illuminates an object in the environment with a predetermined light pattern, such as a grid or checkerboard pattern, and uses the camera 110 to detect the reflection of the predetermined light pattern from the object. Based on the distortion in the reflected light pattern, the vehicle 100 can determine the distance to the point on the object. The predetermined light pattern may include infrared or other wavelengths of light. As another example, the camera 110 may use a laser scanning technique in which the vehicle 100 emits a laser and scans several points on an object in the environment. As it scans the object, the vehicle 100 uses the camera 110 to detect the reflection of the laser from the object for each point. Based on the amount of time it takes for the laser to reflect off the object at each point, the vehicle 100 can determine the distance to the point on the object. As yet another example, the camera 110 may use a time-of-flight technique in which the vehicle 100 emits a light pulse and uses the camera 110 to detect the reflection of the light pulse from an object at several points on the object. In particular, the camera 110 may include several pixels, each capable of detecting the reflection of the light pulse from a point on the object. Based on the length of time it takes for the light pulse to reflect off the object at each point, the vehicle 100 can determine the distance to the point on the object. The light pulse may be a laser pulse. Other range detection techniques are also possible, including stereo triangulation, light sheet triangulation, interferometry, and coded aperture techniques, among others. The camera 110 may take other forms as well.

[0027]

[0036] In some embodiments, the camera 110 may include a movable mount and / or actuator configured to adjust the position and / or orientation of the camera 110 by moving the camera 110 and / or the movable mount, as described above.

[0028]

[0037] Although camera 110 is shown mounted inside the windshield of vehicle 100, in other embodiments camera 110 may be mounted elsewhere on vehicle 100, either inside or outside vehicle 100.

[0029]

[0038] Vehicle 100 may include one or more other components in addition to or instead of those shown.

[0030]

[0039] Figure 2 is a simplified block diagram of a vehicle 200 according to an example embodiment. Vehicle 200 may be similar to vehicle 100 described above in connection with Figure 1, for example. However, vehicle 200 may take other forms.

[0031]

[0040] As shown, vehicle 200 includes a propulsion system 202, a sensor system 204, a control system 206, peripheral devices 208, and a computer system 210 that includes a processor 212, data storage 214, and instructions 216. In other embodiments, vehicle 200 may include more, fewer, or different systems, each of which may include more, fewer, or different components. Additionally, the illustrated systems and components may be combined or divided in any number of ways.

[0032]

[0041] The propulsion system 202 may be configured to provide powered motion for the vehicle 200. As shown, the propulsion system 202 includes an engine / motor 218, an energy source 220, a transmission 222, and wheels / tires 224.

[0033]

[0042] Engines / Motors 218 includes internal combustion engines, electric motors, steam engines, and Stalin The propulsion system 202 may be or include any combination of a gasoline engine, a gasoline engine, or an electric motor. Other motors and engines are possible. In some embodiments, the propulsion system 202 may include multiple types of engines and / or motors. For example, a gasoline-electric hybrid vehicle may include a gasoline engine and an electric motor. Other examples are possible.

[0034]

[0043] Energy source 220 may be a source of energy that, in whole or in part, powers engine / motor 218. That is, engine / motor 218 may be configured to convert energy source 220 into mechanical energy. Examples of energy source 220 include gasoline, diesel, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electrical power. Energy source(s) 220 may additionally or alternatively include any combination of a fuel tank, a battery, a capacitor, and / or a flywheel. In some embodiments, energy source 220 may also provide energy to other systems of vehicle 200.

[0035]

[0044] Transmission 222 may be configured to transfer mechanical power from engine / motor 218 to wheels / tires 224. To this end, transmission 222 may include a gearbox, a clutch, a differential, a driveshaft, and / or other elements. In embodiments in which transmission 222 includes a driveshaft, the driveshaft may include one or more axles configured to be coupled to wheels / tires 224.

[0036]

[0045] The wheels / tires 224 of the vehicle 200 can be configured in a variety of formats, including a unicycle, bicycle / motorcycle, tricycle, or car / truck four-wheel format. Other wheel / tire formats, such as those including six or more wheels, are also possible. In either case, the wheels / tires 224 of the vehicle 224 can be configured to rotate differentially relative to the other wheels / tires 224. In some embodiments, the wheels / tires 224 can include at least one wheel fixedly attached to the transmission 222 and at least one tire coupled to a wheel rim that can contact a drive surface. The wheels / tires 224 can include any combination of metal and rubber or other combinations of materials. The propulsion system 202 can additionally or alternatively include components other than those shown.

[0037]

[0046] Sensor system 204 may include a number of sensors configured to sense information about the environment in which vehicle 200 is located and one or more actuators 236 configured to modify the position and / or orientation of the sensors. As shown, the sensors of sensor system 204 include a global positioning system (GPS) 226, an inertial measurement unit (IMU) 228, a RADAR unit 230, a laser range finder and / or LIDAR unit 232, and a camera 234. Sensor system 204 may also include additional sensors (e.g., an O2 monitor, a fuel gauge, engine oil temperature, etc.), including, for example, sensors that monitor internal systems of vehicle 200. Other sensors are possible.

[0038]

[0047] GPS 226 may be any sensor (e.g., a position sensor) configured to estimate the geographic position of vehicle 200. To this end, GPS 226 may include a transceiver configured to estimate the position of vehicle 200 relative to the Earth. GPS 226 may also take other forms.

[0039]

[0048] IMU 228 may be any combination of sensors configured to sense changes in position and orientation of vehicle 200 based on inertial acceleration. In some embodiments, this combination of sensors may include, for example, accelerometers and gyroscopes. Other sensor combinations are possible.

[0040]

[0049] RADAR unit 230 may be any sensor configured to use radio signals to sense objects in the environment in which vehicle 200 is located. In some embodiments, in addition to sensing objects, RADAR unit 230 may additionally be configured to sense the speed and / or heading of the objects.

[0041]

[0050] Similarly, laser range finder or LIDAR unit 232 may be any sensor configured to sense objects in an environment in which vehicle 200 is located using a laser. In particular, laser range finder or LIDAR unit 232 may include a laser source and / or laser scanner configured to emit a laser, and a detector configured to detect reflections of the laser. Laser range finder or LIDAR unit 232 may be configured to operate in a coherent (e.g., using heterodyne detection) or incoherent detection mode.

[0042]

[0051] Camera 234 may be any camera (e.g., a still camera, a video camera, etc.) configured to acquire images of the environment in which vehicle 200 is located. To this end, the camera may take any of the forms described above. Sensor system 204 may additionally or alternatively include components other than those shown.

[0043]

[0052] The control system 206 may be configured to control the operation of the vehicle 200 and its components. To this end, the control system 206 may include a steering unit 238, a throttle 240, a braking unit 242, a sensor fusion algorithm 244, a computer vision system 246, a navigation or routing system 248, and an obstacle avoidance system 250.

[0044]

[0053] The steering unit 238 may be any combination of mechanisms configured to adjust the heading of the vehicle 200 .

[0045]

[0054] The throttle 240 may be any combination of mechanisms configured to control the operating speed of the engine / motor 218 and, consequently, the speed of the vehicle 200 .

[0046]

[0055] Brake unit 242 may be any combination of mechanisms configured to slow vehicle 200. For example, brake unit 242 may use friction to slow wheels / tires 224. As another example, brake unit 242 may convert the kinetic energy of wheels / tires 224 into electrical current. Brake unit 242 may take other forms as well.

[0047]

[0056] Sensor fusion algorithm 244 may be an algorithm (or a computer program product storing an algorithm) configured to accept data from sensor system 204 as input. This data may include, for example, data representing information sensed by sensors in sensor system 204. Sensor fusion algorithm 244 may include, for example, a Kalman filter, a Bayesian network, or other algorithm. Sensor fusion algorithm 244 may further be configured to provide various assessments based on the data from sensor system 204, including, for example, an assessment of individual objects and / or features in the environment in which vehicle 200 is located, an assessment of a particular situation, and / or an assessment of possible effects based on a particular situation. Other assessments are possible.

[0048]

[0057] The computer vision system 246 detects obstacles, including, for example, traffic signals and obstacles. Computer vision system 246 may be any system configured to process and analyze images captured by camera 234 to identify objects and / or features in the environment in which vehicle 200 is located. To this end, computer vision system 246 may use object recognition algorithms, structure-from-motion (SFM) algorithms, video tracking, or other computer vision techniques. In some embodiments, computer vision system 246 may additionally be configured to map the environment, track objects, estimate object velocities, etc.

[0049]

[0058] Navigation and routing system 248 may be any system configured to determine a driving route for vehicle 200. Navigation and routing system 246 may additionally be configured to dynamically update the driving route while vehicle 200 is in operation. In some embodiments, navigation and routing system 248 may be configured to incorporate data from sensor fusion algorithm 244, GPS 226, and one or more predetermined maps to determine a driving route for vehicle 200.

[0050]

[0059] Obstacle avoidance system 250 may be any system configured to identify, evaluate, avoid, or otherwise take action on obstacles in the environment in which vehicle 200 is located. Control system 206 may additionally or alternatively include components other than those shown.

[0051]

[0060] Peripherals 208 may be configured to enable vehicle 200 to interact with external sensors, other vehicles, and / or a user. To this end, peripherals 208 may include, for example, a wireless communication system 252, a touchscreen 254, a microphone 256, and / or a speaker 258.

[0052]

[0061] The wireless communication system 252, like the wireless communication system 108 of the vehicle 100, can take any of the forms described above.

[0053]

[0062] Touchscreen 254 can be used by a user to input commands to vehicle 200. To this end, touchscreen 254 can be configured to sense at least one of the position and movement of a user's finger via electrostatic sensing, resistive sensing, or surface acoustic wave processes, among other possibilities. Touchscreen 254 can sense finger movement parallel or planar to the touchscreen surface, perpendicular to the touchscreen surface, or both, and can also sense a level of pressure applied to the touchscreen surface. Touchscreen 254 can be formed of one or more semi-transparent or transparent insulating layers and one or more semi-transparent or transparent conductive layers. Touchscreen 254 can take other forms as well.

[0054]

[0063] Microphone 256 may be configured to receive audio (e.g., voice commands or other audio input) from a user of vehicle 200. Similarly, speaker 258 may be configured to output audio to a user of vehicle 200. Peripherals 208 may additionally or alternatively include components other than those shown.

[0055]

[0064] Computer system 210 may be configured to transmit data to and receive data from one or more of propulsion system 202, sensor system 204, control system 206, and peripheral devices 208. To this end, computer system 210 may be connected to propulsion system 202, sensor system 204, control system 206, and peripheral devices 208 by a system bus, network, and / or other connection mechanism (not shown). The device 208 may be communicatively linked to one or more of the devices 208 .

[0056]

[0065] Computer system 210 may be further configured to interact with and control one or more components of propulsion system 202, sensor system 204, control system 206, and / or peripherals 208. For example, computer system 210 may be configured to control the operation of transmission 222 to improve fuel efficiency. As another example, computer system 210 may be configured to cause camera 234 to acquire images of the environment. As yet another example, computer system 210 may be configured to store and execute instructions corresponding to sensor fusion algorithm 244. As yet another example, computer system 210 may be configured to store and execute instructions for displaying a display on touchscreen 254. As yet another example, computer system 110 may be configured to adjust radar unit 230 (e.g., adjust direction, power, modulation pattern, etc.). Other examples are possible.

[0057]

[0066] As shown, computer system 210 includes a processor 212 and a data storage device 214. Processor 212 may include one or more general-purpose processors and / or one or more special-purpose processors. To the extent that processor 212 includes more than one processor, such processors may function separately or cooperatively. Data storage device 214, in turn, may include one or more volatile storage components and / or one or more non-volatile storage components, such as optical storage, magnetic storage, and / or organic storage, and data storage device 214 may be integrated in whole or in part with processor 212.

[0058]

[0067] In some embodiments, data storage device 214 may contain instructions 216 (e.g., program logic) executable by processor 212 to perform various vehicle functions. Data storage device 214 may also contain additional instructions, including instructions for transmitting data to, receiving data from, and / or controlling one or more of propulsion system 202, sensor system 204, control system 206, and peripheral devices 208. Computer system 210 may additionally or alternatively include components other than those shown.

[0059]

[0068] As shown, vehicle 200 further includes a power source 260 that can be configured to provide power to some or all of the components of vehicle 200. To this end, power source 260 can include, for example, rechargeable lithium-ion or lead-acid batteries. In some embodiments, one or more strings of batteries can be configured to provide the power. Other power source materials and configurations are also possible. In some embodiments, such as in some all-electric vehicles, power source 260 and energy source 220 can be implemented together.

[0060]

[0069] In some embodiments, one or more of propulsion system 202, sensor system 204, control system 206, and peripherals 208 may be configured to function in an interconnected manner with other components within and / or outside of their respective systems.

[0061]

[0070] Additionally, vehicle 200 may include one or more elements in addition to or instead of those shown. For example, vehicle 200 may include one or more additional interfaces and / or power sources. Other additional components are possible. In such an embodiment, data storage device 214 may further include instructions executable by processor 212 to control and / or communicate with the additional components.

[0062]

[0071] Additionally, although each of these components and systems is shown as being integrated within vehicle 200, in some embodiments one or more components or systems may be removably mounted on vehicle 200 or otherwise connected (mechanically or electrically) to vehicle 200 using wired or wireless connections. Vehicle 200 may take other forms as well.

[0063]

[0072] 3 is a simplified block diagram of a system 300 according to an example embodiment. The system 300 includes vehicles 302a-302d communicatively linked (e.g., via a wired and / or wireless interface) to an external computing device 304. The vehicles 302a-302d and the computing device 304 may communicate within a network. Alternatively, the vehicles 302a-302d and the computing device 304 may each reside within their own respective networks.

[0064]

[0073] Vehicles 302a-302d can be similar to vehicles 100-200. For example, vehicles 302a-302d can be partially or fully autonomous vehicles, each including sensors (e.g., RADAR, etc.) to detect the environment of vehicle 302a-302d. Vehicles 302a-302d can include components not shown in FIG. 3 , such as a user interface, a communication interface, a processor, and a data storage device that includes instructions executable by the processor to perform one or more functions related to data transmitted to or received by computing device 304. Furthermore, these functions can also relate to the control of vehicle 302a-302d or its components, such as sensors. To that end, these functions can also include the methods and systems described herein.

[0065]

[0074] The computing device 304 may be configured as a server or any other entity arranged to perform the functions described herein. Furthermore, the computing device 304 may be configured to transmit data / requests to and / or receive data from the vehicles 302a-302d. For example, the computing device 304 may receive location information and sensor configurations (e.g., direction, modulation pattern, etc.) from the vehicles 302a-302d and responsively provide requests to nearby vehicles to adjust corresponding sensor configurations to reduce interference between the corresponding sensors. Additionally or alternatively, for example, the computing device 304 may serve as a medium for sharing data (e.g., sensor configuration, location, etc.) between the vehicles 302a-302d. While FIG. 3 depicts the vehicles 302a-302d communicating via the computing device 304, in some examples, the vehicles 302a-302d may additionally or alternatively communicate directly with each other.

[0066]

[0075] The computing device 304 includes a communication system 306, a processor 308, and a data storage device 310. The communication system 306 may be any system configured to communicate with the vehicles 302a-302d or other entities, either directly or via a communication network, such as a wireless communication network. For example, the communication system 306 may include an antenna and a chipset for wirelessly communicating with the vehicles 302a-302d, a server, or other entity, either directly or via a wireless communication network. Alternatively, in some examples, the communication system 306 may include a wired connection to a server or other entity that wirelessly communicates with the vehicles 302a-302d. Thus, the chipset or communication system 306 may generally be configured to communicate with a communication protocol such as Bluetooth, a communication protocol described in IEEE 802.11 (including any IEEE 802.11 revision), a cellular technology (such as GSM, CDMA, UMTS, EV-DO, WiMAX, or LTE), Zigbee, Dedicated Short Range Communications (DSRC), and Wireless Authentication ( The communication system 306 may also be arranged to communicate according to one or more types of wireless communication (e.g., protocols), such as RFID (Radio Frequency Identification) communication, or one or more types of wired communication, such as a local area network (LAN). The communication system 306 may also take other forms.

[0067]

[0076] Processor 308 may include one or more general-purpose processors and / or one or more special-purpose processors. To the extent processor 308 includes more than one processor, such processors may function separately or cooperatively. Data storage 310, in turn, may include one or more volatile and / or one or more non-volatile storage components, such as optical, magnetic, and / or organic storage devices, and data storage 310 may be integrated in whole or in part with processor 308.

[0068]

[0077] In some embodiments, data storage device 310 may contain instructions 312 (e.g., program logic) executable by processor 308 to perform various functions described herein. Data storage device 310 may also contain additional instructions, including instructions for transmitting data to, receiving data from, interacting with, and / or controlling one or more of vehicles 302a-302d. Computer system 210 may additionally or alternatively include components other than those shown.

[0069]

[0078] FIG. 4 is a block diagram of a method 400 according to an example embodiment. The method 400 illustrated in FIG. 4 represents one embodiment of a method that may be used, for example, in conjunction with the vehicle 100, 200, 302a-302d or the computing device 304. The method 400 may include one or more operations, functions, or actions illustrated by one or more of blocks 402-406. While these blocks are illustrated sequentially, in some cases they may be performed in parallel and / or in a different order than described herein. Additionally, various blocks may be combined into fewer blocks, divided into additional blocks, and / or eliminated based on the desired implementation.

[0070]

[0079] Additionally, for method 400 and other processes and methods disclosed herein, a flowchart illustrates the functionality and operation of one possible implementation of the current embodiment. In this regard, each block may represent a module, segment, portion of a manufacturing or operational process, or portion of program code, which includes one or more instructions executable by a processor to implement a particular logical function or step within the process. The program code may be stored on any type of computer-readable medium, such as storage devices including, for example, a disk or hard drive. Computer-readable media may include non-transitory computer-readable media, such as register memory, processor cache, and computer-readable media that store data for short periods of time, such as random access memory (RAM). Computer-readable media may also include non-transitory media, such as secondary storage or persistent long-term storage, such as read-only memory (ROM), optical or magnetic disks, and compact disk read-only memory (CD-ROM). Computer-readable media may also be any other volatile or non-volatile storage system. Computer-readable media may be considered, for example, a computer-readable storage medium or tangible storage device.

[0071]

[0080] Additionally, for method 400 and other processes and methods disclosed herein, each block in FIG. 4 may represent, for example, circuitry hardwired to perform a particular logical function within the process.

[0072]

[0081] The method 400 reduces the likelihood of interference between the vehicle's sensors and other sensors on other vehicles. Describe methods to reduce

[0073]

[0082] At block 402, method 400 includes a vehicle receiving data from an external computing device indicating at least one other vehicle in the vehicle's environment, the data including at least one sensor. In some examples, the vehicle's sensor can be configured to detect the vehicle's environment based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment. For example, the sensor can include a radio-detection (RADAR) sensor similar to radar unit 230 of vehicle 200.

[0074]

[0083] The external computing device may be similar to computing device 304 of system 300. Thus, for example, a vehicle may receive data from the external computing device indicating the proximity of at least one other vehicle and / or the presence of at least one sensor in at least one other vehicle that may interfere with the vehicle's sensor.

[0075]

[0084] Thus, in block 404, method 400 includes determining, based on the data, a likelihood of interference between at least one sensor of at least one other vehicle and a sensor of the vehicle. As an example, the data may indicate that a given vehicle is in front of the vehicle of block 402. Further, the data may indicate that the given vehicle has a rear-facing RADAR that is pointed toward the vehicle's forward-facing RADAR (e.g., sensor). Thus, the data from the external computing device may include information such as the location of the at least one other vehicle and the configuration of at least one sensor in the at least one other vehicle. In another example, the vehicle and the at least one other vehicle may be facing the same direction toward a large reflective object, and thus a forward-facing transmitter of one vehicle may interfere with a forward-facing receiver of the other vehicle.

[0076]

[0085] To facilitate the determination at block 404, in some examples, the vehicle may include a position sensor similar to GPS 226 of vehicle 200 or any other position sensor. In these examples, method 400 may perform the determination at block 404 based on a comparison of the position of the vehicle (e.g., as indicated by the data) to the position of the at least one other vehicle. Additionally, the vehicle may include an orientation sensor similar to IMU 228 of vehicle 200. For example, the orientation sensor may be used to determine the heading and / or heading of the vehicle to facilitate the determination of the likelihood of interference at block 404. For example, the vehicle may compare this heading to the heading of at least one other vehicle (and sensors thereon) to determine the likelihood of interference. Similarly, for example, the position of the vehicle may be compared to the position of at least one other vehicle. Other examples are possible.

[0077]

[0086] Thus, in some examples, method 400 may also include identifying a location of the vehicle within the environment based on a position sensor within the vehicle. In these examples, method 400 may also include determining that at least one other vehicle is within a critical distance to the vehicle based on the position from the position sensor and data from an external computing device.

[0078]

[0087] At block 406, method 400 includes initiating a sensor adjustment in response to the determination at block 404. The adjustment may reduce the likelihood of interference between the vehicle's sensor and at least one sensor of at least one other vehicle. Various implementations of method 400 are possible for performing the sensor adjustment at block 406.

[0079]

[0088] In a first implementation, the sensor and / or the direction of the EM radiation transmitted by the sensor can be adjusted by the vehicle. In one example, the vehicle can actuate a steering device (e.g., a mounting) of the sensor to move the sensor away from at least one sensor of at least one other vehicle. In another example, the vehicle can adjust the direction (e.g., beam steering) of the EM radiation transmitted by the sensor by switching antenna elements in the sensor and / or changing the relative phase of the RF signals driving the antenna elements. Thus, in some examples, method 400 can also include correcting the orientation of the sensor.

[0080]

[0089] In a second implementation, the power of EM radiation transmitted by the sensor may be modified. For example, data may indicate that at least one other vehicle is a given distance from the vehicle. In this example, the vehicle (and / or at least one other vehicle) may be operated by method 400 to reduce the power of EM radiation transmitted by the sensor (and / or at least one sensor of the at least one other vehicle) to reduce interference. For example, an external computing device may provide a request to the vehicle and / or at least one other vehicle to modify the power of corresponding EM radiation transmitted by each vehicle to reduce interference. Thus, in some examples, method 400 may also include modifying the power of EM radiation transmitted by the sensor.

[0081]

[0090] Further, in some embodiments of the second implementation, the vehicle may include a speed sensor similar to the GPS 226 and / or IMU 228 of the vehicle 200 or any other speed sensor. In these embodiments, the speed sensor may be configured to detect the vehicle's direction of travel and / or speed. In one example, if the direction of travel is toward at least one other vehicle, the method 400 may optionally include reducing the power of the EM emissions based on the determination. In another example, the vehicle and the at least one other vehicle may be traveling in the same direction, with the vehicle traveling ahead of the at least one other vehicle. On the other hand, if the vehicle is traveling at a faster speed than the at least one other vehicle, the vehicle's rear-facing RADAR may reduce its power output due to a lower likelihood of an accident. On the other hand, if the vehicle is traveling at a slower speed, the power output may be increased in anticipation of at least one other vehicle approaching the vehicle. Furthermore, in some examples, the method 400 may also include reducing the power of the EM emissions by an amount based on the vehicle's speed. For example, the power reduction may be scaled based on the rate at which the two vehicles are traveling apart from each other.

[0082]

[0091] In a third implementation, the method 400 can also include modifying the modulation pattern of the EM radiation to reduce interference. Modifying the modulation pattern can include, for example, applying a time offset to the modulation pattern, applying a frequency offset to the modulation pattern, adjusting the frequency bandwidth of the modulation pattern, and / or adjusting the shape of the modulation pattern, among other possibilities.

[0083]

[0092] As an example, the modulation pattern of the EM radiation can be a frequency modulated continuous wave (FMCW) RADAR modulation, in which the frequency of the EM radiation is adjusted over time according to the modulation pattern. A receiver (e.g., a RADAR receiver) of the sensor can filter the incoming EM radiation based on the modulation pattern.

[0084]

[0093] Thus, in one example, the vehicle may adjust the modulation pattern of the sensor by applying an offset to differentiate the modulation pattern of the sensor from the modulation pattern of at least one sensor of at least one other vehicle, among other possibilities. In this example, the offset may be a frequency offset or a time offset. In another example, the vehicle The modulation pattern can be adjusted by adjusting the frequency bandwidth or shape of the modulation pattern. In yet another example, a vehicle can adjust the modulation pattern by applying a specific phase-shift keying (PSK) modulation scheme to the EM radiation transmitted by the sensor, and the receiver can filter the incoming EM radiation based on the specific PSK scheme (e.g., to distinguish the EM radiation transmitted by the sensor from other EM radiation transmitted by other sensors on other vehicles). PSK is a digital modulation scheme that converts data by changing or modulating the phase of the transmitted EM radiation. For example, the transmitted EM radiation can be conditioned to have a finite number of phases, each assigned a unique pattern of binary digits, which can be detected by a digital signal processor coupled to the sensor's receiver to identify the source of the EM radiation. Various PSK schemes are possible, such as binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), higher-order PSK, and differential phase-shift keying (DPSK).

[0085]

[0094] FIG. 5 is a block diagram of another method 500 according to an example embodiment. The method 500 illustrated in FIG. 5 represents one embodiment of a method that may be used, for example, in conjunction with the vehicle 100, 200, 302a-302d or the computing device 304. The method 500 may include one or more operations, functions, or actions illustrated by one or more of blocks 502-508. While these blocks are illustrated sequentially, in some cases they may be performed in parallel and / or in a different order than described herein. Additionally, various blocks may be combined into fewer blocks, divided into additional blocks, and / or eliminated based on the desired implementation.

[0086]

[0095] At block 502, method 500 includes receiving data from a plurality of vehicles indicating configuration parameters of sensors within the plurality of vehicles. This data may be received, for example, by a computing device including one or more processors, similar to computing device 304, coupled to the plurality of vehicles via one or more wired / wireless mediums. As an example, the computing device may reside in a network including a broadcast tower configured to receive wireless signals from the plurality of vehicles. The plurality of vehicles (e.g., cars, trucks, trains, ships, etc.) may include sensors, such as RADARs, configured to detect the environment of the plurality of vehicles. In one example scenario, a given vehicle may be traveling along a road in a city (e.g., environment), and a given sensor of the given vehicle may receive objects or other vehicles in the vicinity of the given vehicle. In this example scenario, the given sensor may detect the environment based on a comparison of EM radiation transmitted by the given sensor with reflections of EM radiation from one or more objects in the vehicle's environment. Additionally, the data may indicate configuration parameters of the sensor, such as the direction, power, and modulation pattern of the sensor and / or its EM radiation. In some examples, the data may also indicate the location of the plurality of vehicles.

[0087]

[0096] At block 504, method 500 includes determining, based on the data, that the given vehicle is within a critical distance to at least one other vehicle. As an example, the given vehicle and the at least one other vehicle may be following each other or approaching an intersection, and data received by the computing device may indicate that the two vehicles are within a critical distance to each other, thereby potentially causing interference between the respective sensors of the two vehicles.

[0088]

[0097] At block 506, the method 500 includes determining a likelihood of interference between at least one sensor of at least one other vehicle and a given sensor of a given vehicle based on the configuration parameters. For example, a first RADAR (e.g., a given sensor) in a given vehicle may be pointed toward a second RADAR in at least one other vehicle. In this example, a signal from the second RADAR may be received by the first RADAR and cause interference (e.g., the first RADAR may erroneously infer that the second RADAR signal is a reflection of EM radiation from the first RADAR). Thus, the computing device of method 500 may use information from multiple vehicles, such as sensor configuration parameters and / or the locations of the multiple vehicles, to determine the likelihood of interference.

[0089]

[0098] At block 508, method 500 includes providing a request to the given vehicle to adjust a given configuration parameter of the given sensor to reduce interference between the given sensor of the given vehicle and at least one sensor of at least one other vehicle. Providing the request may be based on a likelihood of interference being greater than a marginal likelihood. Similar to the adjustment at block 406 of method 400, various adjustments to the given configuration parameter of the given sensor are possible. For example, the request at block 508 may indicate a direction, power, modulation pattern, bandwidth, or any other adjustment. Additionally, in some examples, method 500 may also include providing a similar request to at least one other vehicle to further reduce the likelihood of interference.

[0090]

[0099] As one example, each of a plurality of vehicles may be instructed by the computing device to have a respective binary phase shift keying (BPSK) scheme to reduce the likelihood of interference. For example, adjacent vehicles may include different BPSK schemes. Further, for example, BPSK schemes may be reused for vehicles that are not adjacent or that have a low likelihood of receiving EM emissions from each other. Thus, for example, BPSK codes may be spatially reused based on the likelihood determination in block 506.

[0091]

[0100] Additionally, in some examples, the computing device at block 508 can provide requests for combinations of adjustments. For example, the request can dictate adjustments to frequency offset, time offset, and / or power to reduce the likelihood of a particular interference effect (e.g., overload) on the radar's front-facing receiver. Additionally, in this example, the request can also dictate BPSK coding adjustments to help distinguish sources of EM radiation in nearby vehicles. Other examples are possible.

[0092]

[0101] FIG. 6 illustrates a number of sensors within the environment of a vehicle 602 including a sensor 606 according to an example embodiment. Vehicles 612a-612c are shown. Vehicles 602 and 612a-612c can be similar to vehicles 100, 200, and 302a-302d of FIGS. 1-3. For example, vehicle 602 can include a sensor 606 (e.g., a RADAR, a LIDAR, etc.) similar to radar unit 230 and / or LIDAR unit 232 of vehicle 200. Vehicle 602 further includes a mount 604 (a "steering device") configured to adjust the orientation of sensor 606. Mount 604 can be, for example, a movable mount including a material suitable for supporting sensor 606 and can be operated by a control system (not shown) to rotate sensor 606 about a mounting axis to correct the orientation of sensor 606. Alternatively, mount 604 can correct the orientation of sensor 606 in a different manner. For example, mount 604 (e.g., a steering device) can translate sensor 606 along a horizontal plane, etc.

[0093]

[0102] As shown in FIG. 6, vehicles 602 and 612a-612c are traveling along a road 610. Additionally, vehicles 612a-612c may include sensors (not shown in FIG. 6) that may interfere with the operation of sensor 606 of vehicle 602. Various scenarios for reducing interference between such sensors and sensor 606 according to the present invention are presented below.

[0094]

[0103] In the first scenario, the vehicle 612a is pointed towards the sensor 606 and then Vehicle 602 may include a steering sensor (not shown) that points toward vehicle 612a. Vehicle 602 may determine such a scenario via a method such as methods 400-500. For example, vehicle 602 may receive data from a server (not shown) indicating that the sensors are pointed toward each other. In this scenario, vehicle 602 may adjust the direction of sensor 606, for example, via mount 604 ("steering device"), to reduce such interference. For example, mount 604 may rotate sensor 606 so that it deviates slightly from the direction of vehicle 612a.

[0095]

[0104] In the second scenario, vehicle 612b may also include a rear-facing sensor (not shown) directed towards sensor 606. In this scenario, for example, vehicle 602 can adjust the modulation pattern of the EM radiation from sensor 606 to reduce interference between the sensors of vehicle 612b and sensor 606 of vehicle 602. For example, the EM radiation of the sensors of vehicle 612b may have a triangular wave shape, and vehicle 602 may adjust the shape of the EM radiation from sensor 606 to correspond to a sawtooth shape or may adjust the slope of the triangular wave. Other examples are possible.

[0096]

[0105] In the third scenario, vehicle 612c may also include a rear-facing sensor (not shown) directed towards sensor 606. In this scenario, the sensors of vehicle 612c may receive signals from sensor 606 that interfere with the sensors of vehicle 612c. Therefore, in this scenario, vehicle 602 can reduce the output of the EM radiation from sensor 606 so that the EM radiation from sensor 606 does not significantly interfere with the sensors of vehicle 612c after crossing a given distance to vehicle 612c.

[0097]

[0106] Other scenarios are possible according to the present invention.

[0107]

[0098] FIG. 7 is a simplified block diagram of a sensor 700 according to an example of an embodiment. Sensor 700 can include, for example, a frequency-modulated continuous wave (FMCW) RADAR. Sensor 700 includes a local oscillator 702, a transmitter 704, a receiver 706, a mixer 708, an intermediate frequency (IF) filter 710, an analog-to-digital converter (ADC) 712, and a digital signal processor (DSP) 714. Sensor 700 can be made similar to, for example, the radar unit 230 of vehicle 200.

[0108]

[0099] It is worth noting that blocks 702-714 are for illustrative purposes only. In some examples, some of the blocks in sensor 700 can be combined or divided into other blocks. For example, FIG. 7 shows a single-channel transmitter 704 and receiver 706. In some embodiments, sensor 700 can include multiple transmitters and / or receivers. In one example configuration, sensor 700 can include two transmitters and four receivers. In another example configuration, sensor 700 can include four transmitters and eight receivers. Other examples are possible. Further, for example, receiver 706 can include a mixer 708.

[0100]

[0109] The local oscillator 702 may be any oscillator configured to output a continuous wave (e.g., The local oscillator 702 may include a continuous wave (e.g., a coherent oscillator, etc.) that can be used by a transmitter 704 (e.g., a transmitter antenna) to emit electromagnetic (EM) radiation toward the environment of the sensor 700. As an example, the local oscillator 702 may be configured to sweep a particular bandwidth (e.g., 76 GHz to 77 GHz) at a particular rate to provide the transmitter 704 with a continuous wave.

[0101]

[0110] EM radiation can be reflected from one or more objects in the environment, and the reflected EM The emissions can be received by receiver 706 according to methods 400-500. In some examples, transmitter 704 and receiver 706 can include any antenna, such as a dipole antenna, a waveguide antenna, a waveguide array antenna, or any other type of antenna.

[0102]

[0111] The signal from the receiver 706 is mixed with the signal from the local oscillator 702 in the mixer 70 8. Mixer 708 may include any electronic mixer device, such as an unbalanced crystal mixer, a point contact crystal diode, a Schottky barrier diode, or any other mixer. Mixer 708 may be configured to provide an output that includes a mixture of multiple frequencies in the input signal, such as a sum or difference of multiple frequencies.

[0103]

[0112] The signal from the mixer 708 is mixed to the desired intermediate frequency. The signal may be received by an IF filter 710 configured to filter out frequency components. In some examples, the IF filter 710 may include one or more bandpass filters. The IF filter 710 may have a particular bandwidth related to the resolution of the sensor 700. The ADC 712 may then receive the signal from the IF filter 710 and provide a digital representation of the output of the IF filter 710 to the DSP 714.

[0104]

[0113] The DSP 714 may measure the range, angle, or The DSP 714 may include any digital signal processing device or algorithm for processing data from the ADC 712 to determine the velocity. The DSP 714 may include, for example, one or more processors. In one example, the DSP 714 may be configured to determine the binary phase shift keying (BPSK) format of the signal received by the receiver 706. In this example, the DSP 714 may identify the source of the received EM radiation. For example, the BPSK format of the EM radiation transmitted by the transmitter 704 may be compared to the BPSK format of the EM radiation received by the receiver 706.

[0105]

[0114] FIG. 8 illustrates a modulation pattern 8 of electromagnetic (EM) radiation from a sensor according to an example embodiment. 8 shows modulation pattern 800 along frequency axis 802 (vertical axis) and time axis 804 (horizontal axis).

[0106]

[0115] So, for example, EM radiation may occur between a minimum frequency 806 and a maximum frequency 808. The modulation pattern 800 may have a continuously varying frequency. The minimum frequency 806 and maximum frequency 808 may span, for example, a frequency range of 76 GHz to 77 GHz, a portion of this frequency range, or some other frequency range. In the example shown in Figure 8, the modulation pattern 800 corresponds to a triangular pattern. However, in other examples, the shape of the modulation pattern 800 may correspond to any other shape, such as a sawtooth pattern, a square wave pattern, a sinusoidal pattern, or any other shape.

[0107]

[0116] In an example of operation of a sensor such as sensor 700, EM radiation having modulation pattern 800 is emitted. The modulation pattern 800 can be transmitted by a transmitter (e.g., transmitter 704), and a reflection of the modulation pattern 800 can be received by a receiver (e.g., receiver 706). By comparing the modulation pattern 800 of the transmitted wave with the modulation pattern of the reflected wave, the distance and velocity of an object in the sensor's environment can be determined. For example, the time offset between the transmitted and received waves can be used to determine the distance (e.g., range) to the object. Furthermore, for example, changes in slope of the modulated pattern 800 can be used to determine the velocity (e.g., Doppler velocity, etc.) of the object relative to the sensor.

[0108]

[0117] 9A-9E illustrate a method for detecting a magnetic field from a sensor according to at least some embodiments herein. 9A-9E illustrate example scenarios 900a-900e for adjusting the modulation pattern of EM emissions from a first sensor in a first vehicle to reduce interference with other sensors. Scenarios 900a-900e present modulated patterns along a frequency axis 902 and a time axis 904, respectively, similar to frequency axis 802 and time axis 804 of FIG. 8. In FIGS. 9A-9E, modulated patterns 910a-910e may correspond to modulated patterns of EM emissions from a first sensor in a first vehicle, and modulated patterns 912a-912e may correspond to modulated patterns of EM emissions from a second sensor in a second vehicle. Scenarios 900a-900e present various adjustments of the corresponding modulation patterns to reduce interference in accordance with the present invention.

[0109]

[0118] In the scenario 900a of FIG. 9A, the modulated pattern 912a of the second sensor is: To distinguish between modulated pattern 910a and modulated pattern 912a, they can be offset by a time offset 924. For example, time offset 924 can cause a frequency offset between the two waveforms 910a and 912a from frequency 920a to frequency 922a. Thus, a filter, such as IF filter 710 of sensor 700, can distinguish between the emissions of the corresponding waveforms. For example, frequency offset 920a-922a can be selected to be greater than the bandwidth of the IF filter of a first sensor associated with waveform 910a and / or the IF filter of a second sensor associated with waveform 912a.

[0110]

[0119] In scenario 900b of FIG. 9B, alternatively, between frequencies 920b and 922b By applying a frequency offset of 910b, waveforms 910b and 912b can be distinguished. Similar to scenario 900a, for example, such a frequency offset allows a sensor such as sensor 700 to distinguish between the two waveforms (e.g., based on the IF filter bandwidth).

[0111]

[0120] In scenario 900c of FIG. 9C, modulation pattern 910c and / or 912c can be adjusted to have a different shape. For example, FIG. 9C shows modulated pattern 910c (e.g., of a first sensor) to have a different slope than modulated pattern 912c (e.g., of a second sensor). Alternatively, in some examples, other modifications to modulated patterns 910c and 912c can be applied. For example, a different shape (e.g., triangular, sawtooth, sinusoidal, etc.) can be used by one of the two sensors.

[0112]

[0121] In scenario 900d of FIG. 9D, the frequencies of modulation patterns 910d and 912d The bandwidths can be adjusted. For example, a first sensor can be adjusted to output modulated pattern 910d having a minimum frequency of 76 GHz and a maximum frequency of 76.45 GHz, and a second sensor can be adjusted to output modulated pattern 912d having a minimum frequency of 76.5 GHz and a maximum frequency of 77 GHz. Thus, a filter, such as IF filter 710, can be configured to filter the signal for frequencies within the corresponding bandwidth.

[0113]

[0122] In scenario 900e of FIG. 9E, the first sensor and the second sensor detect EM radiation. The EM radiation of the first sensor (e.g., modulation pattern 910e) can be intermittently stopped by the first vehicle, and the modulation pattern 912e of the second sensor can be started after a time offset, shown in FIG. 9E as the time offset between times 920e and 922e. Thus, the receivers of the first sensor and the second sensor can avoid receiving signals from each other's transmitters.

[0114]

[0123] Scenarios 900a-900e in FIGS. 9A-9E are shown for illustrative purposes only. Other scenarios for adjusting the modulation patterns of the sensors to reduce interference are also possible with the methods 400-500 of the present invention.

[0115]

[0124] FIG. 10 depicts an example of a computer-readable medium configured in accordance with an example embodiment. In example embodiments, the example system may include one or more processors, one or more types of memory, one or more input devices / interfaces, one or more output devices / interfaces, and machine-readable instructions that, when executed by the one or more processors, cause the system to perform the various functional tasks, capabilities, etc. described above.

[0116]

[0125] As noted above, in some embodiments, the disclosed techniques (e.g., Method 4 00, 500, etc.) may be embodied by computer program instructions (e.g., instructions 216 of vehicle 200, instructions 312 of computing device 304, etc.) encoded in a machine-readable format on a computer-readable storage medium or other medium or apparatus. Figure 10 is a schematic diagram illustrating a conceptual partial view of an example computer program product including a computer program for executing a computer process on a computing device arranged in accordance with at least some embodiments disclosed herein.

[0117]

[0126] In one embodiment, the example computer program product 1000 is a signal transmission medium 1 1-9. The signal-bearing medium 1002 may include one or more programming instructions 1004 that, when executed by one or more processors, can provide the functionality described above with respect to FIGS. 1-9, or a portion thereof. In some examples, the signal-bearing medium 1002 may be a computer-readable medium 1006, such as, but not limited to, a hard disk drive, a compact disc (CD), a digital video disc (DVD), digital tape, a memory, or the like. In some implementations, the signal-bearing medium 1002 may be a computer-recordable medium 1008, such as, but not limited to, a memory, a read / write (R / W) CD, a R / W DVD, or the like. In some implementations, the signal-bearing medium 1002 may be a communications medium 1010 (e.g., fiber optic cable, a waveguide, a wired communications link, etc.). Thus, for example, the signal-bearing medium 1002 may be conveyed via a wireless form of communications medium 1010.

[0118]

[0127] The one or more programming instructions 1004 may be, for example, computer-executable instructions. The programming instructions 1004 may be instructions and / or logic-embodied instructions. In some examples, a computing device may be configured to provide various operations, functions, or actions in response to programming instructions 1004 communicated to the computing device by one or more of computer-readable medium 1006, computer-recordable medium 1008, and / or communication medium 1010.

[0119]

[0128] The computer readable medium 1006 may include multiple The stored instructions may also be distributed among data storage elements. The computing device that executes some or all of the stored instructions may be an external computer or mobile computing platform, such as a smartphone, tablet device, personal computer, wearable device, etc. Alternatively, the computing device that executes some or all of the stored instructions may be a remotely located computer system, such as a server or a distributed cloud computing network.

[0120]

[0129] It is understood that the arrangements described herein are for illustrative purposes only. Therefore, those skilled in the art will appreciate that other arrangements and other elements (e.g., machines, interfaces) may be used. It will be recognized that various elements (e.g., resources, functions, instructions, and groupings of functions) may be used instead, and some elements may be omitted entirely, depending on the results desired. Furthermore, many of the elements described are functional entities that can be implemented as separate or distributed components, or with other structural elements described such that they can be combined with other components or independent structures in any suitable combination and location.

[0121]

[0130] While various aspects and embodiments are disclosed herein, other aspects and embodiments may be used. Implementations will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and not limitation, with the true scope being indicated by the following claims, along with the full scope of equivalents to which such claims are entitled. Also, the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

Claims

1. a sensor configured to detect an environment of the vehicle based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment; a controller configured to (i) receive data from an external computing device indicative of at least one other vehicle in the environment of the vehicle, the data including at least one sensor; (ii) determine a likelihood of interference between the at least one sensor of the at least one other vehicle and the sensor of the vehicle based on the data; and (iii) responsively initiate adjustments of the sensor to reduce the likelihood of interference between the sensor of the vehicle and the at least one sensor of the at least one other vehicle; Vehicles including.

2. a position sensor configured to identify a position of the vehicle within the environment, the controller configured to determine, based on the position sensor and the data, that the at least one other vehicle is within a critical distance to the vehicle, and the controller configured to determine, based on the determination, the likelihood of interference; an orientation sensor configured to identify an orientation of the vehicle, wherein the controller is configured to compare the orientation of the vehicle with at least one orientation of the at least one other vehicle indicated by the data, and wherein the controller is configured to determine the likelihood of interference based on the comparison; The vehicle of claim 1 further comprising:

3. The vehicle of claim 1 , wherein the sensor comprises an electromagnetic detection (RADAR) sensor.

4. 1. A steering device configured to adjust the orientation of the sensor, wherein the adjustment of the sensor comprises adjusting the orientation of the sensor. The vehicle of claim 1 further comprising:

5. The vehicle of claim 1 , wherein the adjustment of the sensor comprises adjusting the power of the EM radiation transmitted by the sensor.

6. a speed sensor configured to detect a direction of travel and a speed of the vehicle, wherein the controller is configured to determine that the direction of travel is away from the at least one other vehicle, and wherein the controller is configured to reduce the power of the EM radiation based on the determination. The vehicle of claim 5 further comprising:

7. The vehicle of claim 6 , wherein the controller is configured to reduce the power of the EM radiation by an amount based on the speed of the vehicle.

8. The vehicle of claim 1 , wherein the EM radiation has a modulation pattern, and the adjusting of the sensor comprises adjusting the modulation pattern of the EM radiation.

9. The vehicle of claim 8 , wherein the adjustment of the modulation pattern includes a time offset applied to the modulation pattern.

10. The vehicle of claim 8 , wherein the adjustment of the modulation pattern comprises a frequency offset applied to the modulation pattern.

11. The vehicle of claim 8 , wherein the adjusting of the modulation pattern comprises adjusting a frequency bandwidth of the modulation pattern.

12. The vehicle of claim 8 , wherein the adjusting the modulation pattern comprises adjusting a shape of the modulation pattern.

13. 9. The vehicle of claim 8, wherein said adjusting said modulation pattern comprises adjusting a binary phase shift keying (BPSK) format associated with said modulation pattern.

14. receiving, by a vehicle including a sensor configured to detect an environment of the vehicle based on a comparison of electromagnetic (EM) radiation transmitted by the sensor and reflections of the EM radiation from one or more objects in the vehicle's environment, data from an external computing device indicative of at least one other vehicle in the vehicle's environment, the other vehicle including at least one sensor; determining a likelihood of interference between the at least one sensor of the at least one other vehicle and the sensor of the vehicle based on the data; Initiating an adjustment of the sensor based on the likelihood being greater than a threshold likelihood to reduce the likelihood of interference between the sensor of the vehicle and the at least one sensor of the at least one other vehicle; A method comprising:

15. modifying a direction of the EM radiation transmitted by the sensor, wherein the adjustment of the sensor includes modifying the direction.

15. The method of claim 14, further comprising:

16. modifying a modulation pattern of the EM radiation, wherein the adjusting of the sensor includes modifying the modulation pattern.

15. The method of claim 14, further comprising:

17. 17. The method of claim 16, wherein modifying the modulation pattern of the EM radiation comprises one or more of: (i) applying a time offset to the modulation pattern; (ii) applying a frequency offset to the modulation pattern; (iii) adjusting a frequency bandwidth of the modulation pattern; (iv) adjusting a shape of the modulation pattern; or (v) adjusting a phase shift keying (PSK) scheme of the modulation pattern.

18. identifying a position of the vehicle within the environment based on a position sensor within the vehicle; identifying an orientation of the vehicle within the environment based on an orientation sensor within the vehicle; determining at least one position and at least one orientation of the at least one other vehicle based on the data from the external computing device, wherein determining the likelihood of interference is based on the position of the vehicle, the orientation of the vehicle, the at least one position of the at least one other vehicle, and the at least one orientation of the at least one other vehicle.

15. The method of claim 14, further comprising:

19. receiving, by a computing device including one or more processors, data from a plurality of vehicles indicative of configuration parameters of sensors in the plurality of vehicles, the data also indicative of locations of the plurality of vehicles, and a given sensor in a given vehicle detecting electromagnetic (EM) emissions transmitted by the given sensor and forward-facing emissions from one or more objects in an environment of the given vehicle; configured to detect the environment of the given vehicle based on a comparison of the EM radiation with a reflection; determining, based on the data, that the given vehicle is within a critical distance to at least one other vehicle; responsively determining a likelihood of interference between at least one sensor of the at least one other vehicle and the given sensor of the given vehicle based on the configuration parameters; providing a request to the given vehicle to adjust a given configuration parameter of the given sensor to reduce the likelihood of interference between the given sensor of the given vehicle and the at least one sensor of the at least one other vehicle based on the likelihood being greater than a marginal likelihood; A method comprising:

20. 20. The method of claim 19, wherein the given configuration parameter comprises one or more of an orientation of the given sensor, an output of the given sensor, or a modulation pattern of the EM radiation transmitted by the given sensor.

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