A surround multi-object tracking and surround vehicle motion prediction framework is provided. A full-surround camera array and LiDAR sensor based approach provides for multi-object tracking for autonomous vehicles. The multi-object tracking incorporates a fusion scheme to handle object proposals from the different sensors within the calibrated camera array. A motion prediction framework leverages the instantaneous motion of vehicles, an understanding of motion patterns of freeway traffic, and the effect of inter-vehicle interactions. The motion prediction framework incorporates probabilistic modeling of surround vehicle trajectories. Additionally, subcategorizing trajectories based on maneuver classes leads to better modeling of motion patterns. A model takes into account interactions between surround vehicles for simultaneously predicting each of their motion.

Controllers, control architectures, systems and methods are described for controlling a host vehicle's participation in a platoon. Described vehicle platooning control systems may include a platoon controller and a vehicle interface controller. The platoon controller is configured to determine torque and braking requests for at least partially automatically controlling the host vehicle to platoon with a platoon partner. The vehicle interface controller manages communications between the platoon controller and one or more host vehicle control units. The vehicle interface controller may also include a safety monitor including one or more safety monitoring algorithms In some embodiments, the vehicle interface controller is at least ASIL-C compliant, whereas the platoon controller and an optional gateway processor may be QM rated under ISO 26262. The platoon controller may be configured as a listener capable of receiving but not transmitting messages on the host vehicle's control related communication bus(es).

A path providing device configured to provide a path information to a vehicle includes: a communication unit configured to receive, from a server, map information including a plurality of layers of data, an interface unit configured to receive sensing information from one or more sensors disposed at the vehicle, a processor, and an event data recorder (EDR) configured to store vehicle status information including first sensor data sensed by a first sensor associated with an operation of the vehicle, and second sensor data sensed by a second sensor associated with surrounding information of the vehicle. The processor is configured to determine an optimal path for guiding the vehicle from an identified lane, generate autonomous driving visibility information, update the optimal path based on dynamic information and the autonomous driving visibility information, and include the vehicle status information stored in the EDR in the autonomous driving visibility information.

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.

A path providing device configured to provide a path information to a vehicle includes a communication unit configured to receive, from a server, map information including a plurality of layers of data, an interface unit configured to receive sensing information from one or more sensors disposed at the vehicle, and a processor. The processor is configured to determine an optimal path for guiding the vehicle from an identified lane, generate autonomous driving visibility information based on the sensing information and the determined optimal path, update the optimal path based on dynamic information related to a movable object located on the optimal path and the autonomous driving visibility information, receive different types of sensor data from a plurality of sensors, and update at least one of the autonomous driving visibility information or the optimal path based on information generated by combining at least two types of sensor data.

A path providing device is configured to provide a path to a vehicle. The path providing device includes an image sensor, and the image sensor and a processor are provided on one printed circuit board. The path providing device further includes a data fusion unit configured to extract a portion to be updated from the map information using an image received from the image sensor.

A trajectory planning system can be used to select a trajectory for an autonomous vehicle. The trajectory planning system may generate multiple trajectories and extract features from the generated trajectories. The trajectory planning system may evaluate the trajectories based on the extracted features and select a trajectory for the vehicle based on the evaluation. The selected trajectory may be used to control the vehicle.

A reliability correction device is provided in which a target-matter is detected by means of a camera and/or a radar, and a reliability modification unit included in the device modifies the degree of reliability with respect to target-matter information being detected, on the basis of an irradiation range(s) being an irradiation region(s) of a light(s).

A system for autonomously navigating a vehicle along a road segment may include at least one processor. The at least one processor may be programmed to receive from at least one sensor information relating to one or more aspects of the road segment. The processor may also be programmed to determine a local feature of the road segment based on the received information. Further the processor may be programmed to compare the local feature to a predetermined signature feature for the road segment. The processor may be programmed to determine a current location of the vehicle along a predetermined road model trajectory associated with the road segment based on the comparison of the received information and the predetermined signature feature. The processor may also be programmed to determine an autonomous steering action for the vehicle based on a direction of the predetermined road model trajectory at the determined location.

A system for autonomously navigating a vehicle through a road junction may include at least one processor programmed to receive from an image capture device at least one image representative of an environment of the vehicle. The processor may also be configured to analyze the image to identify two or more landmarks located in the environment of the vehicle and to determine, for each of the two or more landmarks, a directional indicator relative to the vehicle. The processor may be configured to determine a current location of the vehicle relative to the road junction based on an intersection of the directional indicators a heading for the vehicle based on the directional indicators for the two or more landmarks. The processor may be configured to determine a steering angle for the vehicle by comparing the vehicle heading with a predetermined road model trajectory at the current location of the vehicle.