Various applications for use of mass estimations of a vehicle, including to control operation of the vehicle, sharing the mass estimation with other vehicles and/or a Network Operations Center (NOC), organizing vehicles operating in a platoon and/or partially controlling the operation of one or more vehicles operating in a platoon based on the relative mass estimations between the platooning vehicles. When vehicles are operating in a platoon, the relative mass between a lead and a following vehicle may be used to scale torque and/or brake commands generated by the lead vehicle and sent to the following vehicle.

A vehicle control system includes an output unit configured to output information to the outside of a vehicle, an in-vehicle status acquisition unit configured to acquire a status inside the vehicle, and a control unit configured to cause the output unit to output information as to whether or not it is possible to ride in the vehicle on the basis of in-vehicle information acquired by the in-vehicle status acquisition unit.

Systems and methods for coordinating and controlling vehicles, for example heavy trucks, to follow closely behind each other, or linking to form a platoon. In one aspect, on-board controllers in each vehicle interact with vehicular sensors to monitor and control, for example, relative distance, relative acceleration or deceleration, and speed. In some aspects, vehicle onboard systems supply various data (breadcrumbs) to a Network Operations Center (NOC), which in turn provides data (authorization data) to the vehicles to facilitate platooning. The NOC suggests vehicles for platooning based on, for example, travel forecasts and analysis of relevant roadways to identify platoonable roadway segments. The NOC also can provide traffic, roadway, weather, or system updates, as well as various instructions. In some aspects, a mesh network ensures improved communication among vehicles and with the NOC. In some aspects, a vehicle onboard system may provide the authorization data.

Systems and methods navigate a vehicle on a road at least partially covered with snow. In one implementation, a system may include at least one processor programmed to receive from an image capture device, a plurality of images captured of an environment forward of the vehicle, including an area where snow covers a road on which the vehicle travels, analyze at least one of the plurality of images to identify a first free space boundary on a first side of the vehicle and extending forward of the vehicle, a second free space boundary on a passenger side of the vehicle and extending forward of the vehicle, and a forward free space boundary forward of the vehicle and extending between the first free space boundary and the second free space boundary.

The present disclosure relates to an automated driving control device, a system including the automated driving control device, and a method of automated driving control. The automated driving control device may include: a high-precision lane-level road map storage storing a high-precision lane-level road map; a position recognition controller recognizing a current position of a vehicle based on the high-precision lane-level road map, position recognition information, and vehicle control information; and a vehicle controller generating a path for driving to a destination based on the position of the vehicle recognized by the position recognition controller and obstacle recognition information, and controlling driving of the vehicle.

The present technology relates to an information processing device, an information processing method, and an information processing system which enable reduction in a capacity of a transmission path required for transmission of sensor data.

The information processing device extracts a part of sensor data of a distance measurement sensor to generate extracted data on the basis of a spectrum of a specific component of the sensor data. The present technology can be applied to a vehicle control system that performs processing related to vehicle travel assistance and automated driving.

A system for sparse map autonomous navigation of a vehicle along a road segment may include at least one processor. The at least one processor may be programmed to receive a sparse map of the road segment. The sparse map may have a data density of no more than 1 megabyte per kilometer. The at least one processor may be programmed to receive from a camera, at least one image representative of an environment of the vehicle, and determine an autonomous navigational response for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

The present invention relates to an emergency control device for a vehicle. The emergency control device for a vehicle according to the present invention includes a sensor configured to measure an area inside or outside the vehicle, a processor configured to process data collected by the sensor, and a controller configured to control the vehicle by reflecting the data processed by the processor, wherein the sensor detects whether a driver is inattentive, the processor determines the level of inattentiveness of the driver according to the detected state of the driver, and the controller controls the vehicle according to the level of inattentiveness of the driver.

Systems and methods navigate a vehicle on a road with snow covering at least some lane markings and road edges. In one implementation, a system may include at least one processor programmed to receive from an image capture device, at least one environmental image forward of the vehicle, including areas where snow covers at least some lane markings and road edges, identify, based on an analysis of the at least one image, at least a portion of the road that is covered with snow and probable locations for road edges bounding the at least a portion of the road that is covered with snow, and cause the vehicle to navigate a navigational path that includes the identified portion of the road and falls within the determined probable locations for the road edges.

A system for a vehicle, which drives in an at least in-part-automated manner is configured to determine a control signal for a control system. The system includes a sensor, a planning module, and a monitoring module. The sensor is configured to detect an object in a surrounding area of the vehicle and store a corresponding object representation. The planning module is configured to determine, based to the stored object representation, a first trajectory and a first probability of collision of the first trajectory for the vehicle. The monitoring module is configured to perform one of following actions when the first probability of collision exceeds a predefined probability of collision: determine, using the planning module and based on the stored object representation, a further trajectory having a further probability of collision and a maximum deceleration of the further trajectory; or assess the stored object representation of the object using the sensor.