Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

A vehicle control device includes a detecting unit that detects a towing state of a subject vehicle, a recognizing unit that recognizes surrounding situations of the subject vehicle, a control unit that performs automatic control in which at least one of acceleration-and-deceleration and steering of the subject vehicle is automatically controlled on the basis of the surrounding situations of the subject vehicle recognized by the recognizing unit, and a changing unit that changes, if the detecting unit has detected that the subject vehicle is in a state of towing an object, details of control performed by the control unit in such a manner that it is less likely to perform the automatic control than in the case where the detecting unit has not detected that the subject vehicle is in a state of towing an object

Vehicle control system, vehicle control method, and vehicle control program

Harnessing big data, deep data, and smart data from state-of-the-art imaging might accelerate the design and realization of advanced functional materials. Here we discuss new opportunities in materials design enabled by the availability of big data in imaging and data analytics approaches, including their limitations, in material systems of practical interest. We specifically focus on how these tools might help realize new discoveries in a timely manner. Such methodologies are particularly appropriate to explore in light of continued improvements in atomistic imaging, modelling and data analytics methods.

Big-deep-smart data in imaging for guiding materials design.

Various examples are described for an artificial intelligence valet system. In one example, among others, a distributed information sharing system can obtain route information associated with a geographic area and provide the route information to a user vehicle in response to a request. In another example, an autonomous user vehicle can receive a request to autonomously proceed to a user defined location; obtain route information; and determine a route to the user defined location using the route information. In another example, a collision avoidance system can determine if an object is in a path of travel of a vehicle based at least in part upon sensory data and maneuver the vehicle based at least in part upon an object determination. In another example, an accident reporting system can determine an occurrence of a violation of a vehicle; obtain recordings of the environment surrounding the vehicle; and report the violation.

Artificial intelligence valet systems and methods

Technology is described for operating a fleet of autonomous vehicles. A request for a taxi service may be received from a mobile device. The request may include a current location of the mobile device. They request may indicate that the taxi service is to be performed at a current time. An autonomous vehicle may be selected from the fleet of autonomous vehicles to perform the taxi service based in part on an availability of the autonomous vehicle and a proximity between the autonomous vehicle and the current location of the mobile device. Instructions may be provided to the autonomous vehicle to perform the taxi service according to the request. The autonomous vehicle may be configured to provide commands to drive the autonomous vehicle to the current location of the mobile device in order to perform the taxi service.

Using Autonomous Vehicles in a Taxi Service

Aspects of the invention relate generally to autonomous vehicles. Specifically, the features described may be used alone or in combination in order to improve the safety, use, driver experience, and performance of these vehicles.

System and method for predicting behaviors of detected objects

A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.

Wide-View LIDAR With Areas of Special Attention

A computing device may be configured to receive sensor information indicative of respective characteristics of vehicles on a road of travel of a first vehicle. The computing device may be configured to identify, based on the respective characteristics, a second vehicle that exhibits an aggressive driving behavior manifested as an unsafe or unlawful driving action. Also, based on the respective characteristics, the computing device may be configured to determine a type of the second vehicle. The computing device may be configured to estimate a distance between the first vehicle and the second vehicle. The computing device may be configured to modify a control strategy of tire first vehicle, based on the aggressive driving behavior of the second vehicle, the type of the second vehicle, and the distance between the first vehicle and the second vehicle; and control the first vehicle based on the modified control strategy.

A method to detect nearby aggressive drivers and adjust driving modes

Aspects of the invention relate generally to autonomous vehicles. The features described improve the safety, use, driver experience, and performance of these vehicles by performing a behavior analysis on mobile objects in the vicinity of an autonomous vehicle. Specifically, the autonomous vehicle is capable of detecting nearby objects, such as vehicles and pedestrians, and is able to determine how the detected vehicles and pedestrians perceive their surroundings. The autonomous vehicle may then use this information to safely maneuver around all nearby objects.

System and method for predicting behaviors of detected objects through environment representation

Aspects of the disclosure relate generally to detecting discrete actions by traveling vehicles. The features described improve the safety, use, driver experience, and performance of autonomously controlled vehicles by performing a behavior analysis on mobile objects in the vicinity of an autonomous vehicle. Specifically, an autonomous vehicle is capable of detecting and tracking nearby vehicles and is able to determine when these nearby vehicles have performed actions of interest by comparing their tracked movements with map data.

Jiajun Zhu

Papers

System and method for predicting behaviors of detected objects

Wide-View LIDAR With Areas of Special Attention

A method to detect nearby aggressive drivers and adjust driving modes

System and method for predicting behaviors of detected objects through environment representation

System and method for automatically detecting key behaviors by vehicles