Abstract: A driving assistance device is the driving assistance device used in a vehicle capable of switching between autonomous driving and driving that requires operation by the driver, and includes a different vehicle information acquisition unit that acquires autonomous driving information on different vehicles on a traveling road of the vehicle, an autonomous driving ratio acquisition unit that acquires a ratio of autonomous driving in the different vehicles from the autonomous driving information on the different vehicles acquired by the different vehicle information acquisition unit, and a notification control unit that provides information for supporting determination on switching between autonomous driving and driving that requires operation by a driver if the ratio of autonomous driving in the different vehicles is equal to or larger than a predetermined ratio.

Abstract: Provided is an autonomous wheeled device. A first sensor obtains first data indicative of distances to objects within an environment of the autonomous wheeled device and a second sensor obtains second data indicative of movement of the autonomous wheeled device. A processor generates at least a portion of a map of the environment using at least one of the first data and the second data and a first path of the autonomous wheeled device. The processor transmits first information to an application of a communication device paired with the autonomous wheeled device and receives second information from the application.

Abstract: Spin controller that can enable an autonomous vehicle (AV) to spin in place. A model predictive controller (MPC) can trigger the spin controller any time the MPC determines that a spin in place is required. In some configurations, the spin controller can move the AV to within 5° of the destination point. Spin controller can determine spin method based on the configuration of the AV, calculate an optimum turning path based at least on device mode and obstacles, and can enable the AV to spin in place.

Abstract: In one embodiment, a computer-controlled method for adjusting a height of a header reel, the method comprising: measuring a rotational speed of the reel; measuring a force opposing rotation of the reel; determining a target load for the reel based on the measured rotational speed and the measured force and a first input; and causing movement of the reel according to the target load based on a change in load on the reel.

Abstract: Embodiments of the present invention provide a navigation system which, on the one hand, is arranged on sides of the underwater vehicle/AUV and, on the other hand, includes a surface transmitter as a counterpart. The two units communicate with each other such that the surface transmitter emits its signal directed to the position of the underwater vehicle and/or that the surface transmitter follows the underwater vehicle to improve the position determination capability.

Abstract: A system includes one or more components within an internal cabin of a vehicle. An imaging device is configured to obtain an image of the one or more components. A state determination control unit includes a processor. The state determination control unit is in communication with the imaging device. The state determination control unit receives image data including the image from the imaging device. Further, the state determination control unit determines a state of the one or more components based on the image data.

Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.

Abstract: A vehicle platoon following deciding system based on cloud computing is configured to decide a plurality of vehicle platoon accelerations of a leading vehicle and at least one following vehicle. A cloud processing unit receives a leading vehicle parameter group and at least one following vehicle parameter group. The cloud processing unit is configured to implement a cloud deciding step. The cloud deciding step includes judging whether the leading vehicle is manually driven according to the leading vehicle parameter group to generate a driving mode judging result, calculating a driving acceleration range according to a leading vehicle acceleration range and at least one following vehicle acceleration range, estimating a compensated acceleration according to the leading vehicle parameter group, and calculating the vehicle platoon accelerations according to the driving mode judging result and at least one of the driving acceleration range and the compensated acceleration.

Abstract: A vehicle communication system includes: a communication server and a vehicle control device. The vehicle control device includes at least one electronic control unit configured to: recognize a position of the host vehicle; acquire section information on the communication established section and the communication interrupted section; determine in which section, either the communication established section or the communication interrupted section, the host vehicle is traveling or is to travel; perform system driven control of the host vehicle based on the road condition information when the host vehicle travels in the communication established section; and perform driver driven control of the host vehicle when the host vehicle travels in the communication interrupted section.

Abstract: A vehicle communication system includes: a communication server and a vehicle control device. The vehicle control device includes at least one electronic control unit configured to: recognize a position of the host vehicle; acquire section information on the communication established section and the communication interrupted section; determine in which section, either the communication established section or the communication interrupted section, the host vehicle is traveling or is to travel; perform system driven control of the host vehicle based on the road condition information when the host vehicle travels in the communication established section; and perform driver driven control of the host vehicle when the host vehicle travels in the communication interrupted section.

Abstract: Provided herein is a system and method implemented on a vehicle. The system comprises one or more sensors, one or more processors, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: obtaining data from the one or more sensors; comparing the obtained data from the one or more sensors with reference data; determining whether one or more characteristics of the obtained data deviate from corresponding characteristics of the reference data by more than a respective threshold; in response to determining that one or more characteristics of the data obtained deviate from corresponding characteristics of the reference data by more than a respective threshold, determining an action of the vehicle based on amounts of the one or more deviations; and performing the determined action.

Abstract: Systems and methods of analyzing a target vehicle based on other vehicles are disclosed. One or more computing devices may receive monitoring vehicle driving data collected from vehicle operation sensors within at least one monitoring vehicle by a telematics device. The one or more computing devices may further receive target vehicle driving data from the telematics device of the at least one monitoring vehicle. The one or more computing devices may determine a driving behavior associated with the target vehicle based on an analysis of the monitoring vehicle driving data and the target vehicle driving data. The one or more computing devices may calculate one or more driver scores based on the driving behavior.

Abstract: A vehicle determines whether or not a passage permit condition of the vehicle according to an instruction content of a traffic light in front of the vehicle is satisfied. If it is determined that the passage permit condition is not satisfied, the vehicle temporally stops in front of the traffic light and transmits an assist requiring signal to a remote facility. A display device of the remote facility displays reference image information indicating shot image information of the vehicle that temporally stops in front of the traffic light. An operator of the remote facility inputs positional information of pixels that make up the traffic light contained in the reference image information. The remote facility transmits assist information including the positional information to the vehicle. Based on the positional information, the vehicle determines again whether or not the passage permit condition is satisfied.

Abstract: A method, apparatus, and system for collecting and evaluating powered vehicle operation utilizing on-board diagnostic components and location determining components or systems. The invention creates one or more databases whereby identifiable behavior or evaluative characteristics can be analyzed or categorized. The evaluation can include predicting likely future events. The database can be correlated or evaluated with other databases for a wide variety of uses.

Abstract: Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode using trajectories. For instance, a trajectory may be received by one or more first computing devices from one or more second computing devices. While the first computing devices are controlling the vehicle in the autonomous driving mode based on the trajectory, an error may be generated by second computing devices. Whether the error is a recoverable error may be determined, and if so, the second computing devices attempt to generate a new trajectory. When the second computing devices generate the new trajectory, the vehicle may be controlled by the first computing devices according to the new trajectory.

Abstract: Disclosed herein are system, method, and computer program product embodiments for switching between local and remote guidance instructions for autonomous vehicles. For example, the method includes, in response to monitoring one or more actions of objects detected in a scene in which the autonomous robotic system is moving, causing the autonomous robotic system to slow or cease movement in the scene. The method includes detecting a trigger condition based on movement of the autonomous robotic system in the scene. In response to the one or more monitored actions and detecting the trigger condition, the method includes transmitting a remote guidance request to a remote server. After transmitting the remote guidance request, the method includes receiving remote guidance instructions from the remote server and causing the autonomous robotic system to begin operating according to the remote guidance instructions.

Abstract: In accordance with one embodiment of the present disclosure, method includes obtaining multi-level environment data corresponding to a plurality of driving environment levels, encoding the multi-level environment data at each level, extracting features from the multi-level environment data at each encoded level, fusing the extracted features from each encoded level with a spatial-temporal attention framework to generate a fused information embedding, and decoding the fused information embedding to predict driving environment information at one or more driving environment levels.

Abstract: According to one embodiment, a travel control device includes a passing order determiner configured to determine passing order of a plurality of mobile objects in a first area through which the plurality of mobile objects pass on a basis of a conflict condition at which conflict among the mobile objects occurs; and a controller configured to control traveling of the plurality of mobile objects on a basis of the passing order.

Abstract: Disclosed herein are system, method, and computer program product embodiments for automated autonomous vehicle pose validation. An embodiment operates by generating a range image from a point cloud solution comprising a pose estimate for an autonomous vehicle. The embodiment queries the range image for predicted ranges and predicted class labels corresponding to lidar beams projected into the range image. The embodiment generates a vector of features from the range image. The embodiment compares a plurality of values to the vector of features using a binary classifier. The embodiment validates the autonomous vehicle pose based on the comparison of the plurality of values to the vector of features using the binary classifier.

Abstract: Disclosed are power machines and systems configured to provide autonomous or augmented control of the machines in a localized positioning environment in which GPS navigation is not available. Also disclosed are methods of providing augmented control of a power machine in such an environment.