An autonomous vehicle includes a control system, an array of sensors, processing logic, and a switch. The processing logic generates operation instructions based on sensor data and the control system controls the autonomous vehicle based on the operation instructions. The array of sensors generate the sensor data that is related to objects in an external environment. The switch is coupled between the sensors and the processing logic to buffer the processing logic from the sensor data. The switch is further coupled between the processing logic and the control system to provide the operation instructions from the processing logic to the control system. The switch includes a prioritization engine that prioritizes an order of transmission, from the switch to the processing logic, of the first sensor data over the second sensor data based on received vehicle operation data.

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.

A remote control apparatus performs: calculating a path and a moving speed to reach a desired destination from a current position of the control target apparatus; measuring a communication delay time between the remote control apparatus and the control target apparatus; estimating an overshoot region based on the communication delay time, a stored size of the control target apparatus, and the moving speed; predicting whether the control target apparatus will contact with a peripheral object(s), based on the path, the overshoot region, and stored peripheral object information of the control target apparatus; calculating the moving speed information to be given to the control target apparatus so that a moving direction of the control target apparatus changes by a predetermined value or more when predicted that the control target apparatus will contact with a peripheral object(s); and transmitting a control signal including the moving speed information to the control target apparatus.

A mobile robot is configured to navigate on a sidewalk and deliver a delivery to a predetermined location. The robot has a body and an enclosed space within the body for storing the delivery during transit. At least two cameras are mounted on the robot body and are adapted to take visual images of an operating area. A processing component is adapted to extract straight lines from the visual images taken by the cameras and generate map data based at least partially on the images. A communication component is adapted to send and receive image and/or map data. A mapping system includes at least two such mobile robots, with the communication component of each robot adapted to send and receive image data and/or map data to the other robot. A method involves operating such a mobile robot in an area of interest in which deliveries are to be made.

Provided are an in-vehicle wireless communication apparatus, a wireless communication system, a wireless communication apparatus, and a vehicle control method configured to realize prompt external control of a vehicle. An in-vehicle wireless communication apparatus according to the present embodiment includes a wireless communication unit configured to perform wireless communication with an out-of-vehicle apparatus installed outside the vehicle, and a processing unit configured to perform processing related to communication, and the processing unit transmits information regarding a data format of control data to be output to an in-vehicle network by an in-vehicle control apparatus that controls the vehicle, to the out-of-vehicle apparatus using the wireless communication unit, receives data transmitted from the out-of-vehicle apparatus using the wireless communication unit, the data including control data having the data format, and outputs the control data included in the received data to the in-vehicle network.

Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

An apparatus for controlling a lane change of a vehicle includes: a sensor to sense an external vehicle, an input device to receive a lane change command from a driver of the vehicle, and a control circuit to be electrically connected with the sensor and the input device. The control circuit may receive the lane change command using the input device, calculate a minimum operation speed for lane change control, and determine whether to accelerate the vehicle based on a distance between a preceding vehicle which is traveling on the same lane as the vehicle and the vehicle, when a driving speed of the vehicle is lower than the minimum operation speed when receiving the lane change command.

Aspects of the disclosure relate to determining perceptive range of a vehicle in real time. For instance, a static object defined in pre-stored map information may be identified. Sensor data generated by a sensor of the vehicle may be received. The sensor data may be processed to determine when the static object is first detected in an environment of the vehicle. A distance between the object and a location of the vehicle when the static object was first detected may be determined. This distance may correspond to a perceptive range of the vehicle with respect to the sensor. The vehicle may be controlled in an autonomous driving mode based on the distance.

Aspects of the disclosure provide for a method for identifying speed limit signs and controlling an autonomous vehicle in response to detected speed limit signs. The autonomous vehicle's computing devices identifies a speed limit sign in a vehicle's environment and a location and orientation corresponding to the speed limit sign. Then, the and orientation location of the speed limit sign is determined to not correspond to a pre-stored location and a pre-stored orientation of a speed limit sign that is pre-stored in map information. An effect zone of the speed limit sign is determined based on the location and orientation of the speed limit sign and characteristics of surrounding areas or other detected object before or after the speed limit sign. The autonomous vehicle's computing devices determines a response of the vehicle based on the determined effect zone, and controls the autonomous vehicle based on the determined response.

A trajectory for a vehicle can be generated using a lateral offset bias. The vehicle, such as an autonomous vehicle (AV), may be directed to follow reference trajectory for through an environment. The AV may determine a segment associated with the reference trajectory based on curvatures of the reference trajectory, determine a lateral offset bias associated with the segment based at least in part on, for example, one or more of a speed or acceleration of the vehicle, and determine a candidate trajectory for the autonomous vehicle based at least in part on the lateral offset bias. The candidate trajectory may then be used to control the autonomous vehicle.