A method for providing assistance in driving includes capturing an image of a second moving vehicle when a first moving vehicle is moving and obtaining basic information of the second moving vehicle according to the image thereof, the basic information of the second moving vehicle comprising weight information of the second moving vehicle. Driving information of the first moving vehicle is obtained, and a safe distance between the first moving vehicle and the second moving vehicle is determined according to the driving information of the first moving vehicle and the basic information of the second moving vehicle. The current distance between the first moving vehicle and the second moving vehicle is detected, and a warning is output if the distance between the first moving vehicle and the second moving vehicle is less than the safe distance.

A method for providing assistance in driving includes capturing an image of a second moving vehicle when a first moving vehicle is moving and obtaining basic information of the second moving vehicle according to the image thereof, the basic information of the second moving vehicle comprising weight information of the second moving vehicle. Driving information of the first moving vehicle is obtained, and a safe distance between the first moving vehicle and the second moving vehicle is determined according to the driving information of the first moving vehicle and the basic information of the second moving vehicle. The current distance between the first moving vehicle and the second moving vehicle is detected, and a warning is output if the distance between the first moving vehicle and the second moving vehicle is less than the safe distance.

To provide a technology that makes it possible to recognize a target object quickly and accurately. An information processing apparatus according to the present technology includes a controller. The controller recognizes a target object on the basis of event information that is detected by an event-based sensor, and transmits a result of the recognition to a sensor apparatus that includes a sensor section that is capable of acquiring information regarding the target object.

To provide a technology that makes it possible to recognize a target object quickly and accurately. An information processing apparatus according to the present technology includes a controller. The controller recognizes a target object on the basis of event information that is detected by an event-based sensor, and transmits a result of the recognition to a sensor apparatus that includes a sensor section that is capable of acquiring information regarding the target object.

Provided is an object recognition device including a prediction processing unit, a temporary setting unit, and a association processing unit. The prediction processing unit predicts, as a prediction position on an object model obtained by modeling a tracking target, a position of a movement destination of the tracking target based on a trajectory formed by movement of at least one object of a plurality of objects as the tracking target. The temporary setting unit sets, based on specifications of a sensor that has detected the tracking target, a position of at least one candidate point on the object model. The association processing unit sets, based on the position of the candidate point and the prediction position, a reference position on the object model. The association processing unit determines whether the position of the detection point and the prediction position associate with each other based on a positional relationship between a association range which is set so that the association range has a reference position on the object model as a reference and a detection point at a time when the sensor has detected the at least one object of the plurality of objects.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a surfel map to generate a prediction for a state of an environment. One of the methods includes obtaining surfel data comprising a plurality of surfels, wherein each surfel corresponds to a respective different location in an environment, and each surfel has associated data that comprises an uncertainty measure; obtaining sensor data for one or more locations in the environment, the sensor data having been captured by one or more sensors of a first vehicle; determining one or more particular surfels corresponding to respective locations of the obtained sensor data; and combining the surfel data and the sensor data to generate a respective object prediction for each of the one or more locations of the obtained sensor data.

Systems and methods for operating a mobile platform. The methods comprise, by a computing device: obtaining a LiDAR point cloud; using the LiDAR point cloud to generate a track for a given object in accordance with a particle filter algorithm by generating states of a given object over time (each state has a score indicating a likelihood that a cuboid would be created given an acceleration value and an angular velocity value); using the track to train a machine learning algorithm to detect and classify objects based on sensor data; and/or causing the machine learning algorithm to be used for controlling movement of the mobile platform.

Aspects of the disclosure relate to an autonomous vehicle that may detected other nearby vehicles and identify them as parked or unparked. This identification may be based on visual indicia displayed by the detected vehicles as well as traffic control factors relating to the detected vehicles. Detected vehicles that are in a known parking spot may automatically be identified as parked. In addition, detected vehicles that satisfy conditions that are indications of being parked may also be identified as parked. The autonomous vehicle may then base its control strategy on whether or not a vehicle has been identified as parked or not.

A system for identifying autonomous vehicles includes at least one sensor that may be configured to provide sensor data associated with at least two vehicles. A pre-processing module may be coupled to the at least one sensor and may be configured to determine a set of data including at least car following data based on the sensor data. An autonomous vehicle (AV)/human-driven vehicle (HV) identification neural network may be coupled to the pre-processing module and configured to generate an AV/HV identifier for at least one of the at least two vehicles based on at least the car following data during a predetermined time period.

A system for identifying autonomous vehicles includes at least one sensor that may be configured to provide sensor data associated with at least two vehicles. A pre-processing module may be coupled to the at least one sensor and may be configured to determine a set of data including at least car following data based on the sensor data. An autonomous vehicle (AV)/human-driven vehicle (HV) identification neural network may be coupled to the pre-processing module and configured to generate an AV/HV identifier for at least one of the at least two vehicles based on at least the car following data during a predetermined time period.