Methods and systems are disclosed for vehicles configured for performing a self-parking operation without a human operator. The vehicle includes an on-board computer for receiving a wireless signal from a portable device. The wireless signal is configured to instruct the on-board computer to perform the self-parking operation. The on-board computer of the vehicle is configured for processing instructions to communicate with sensors of the vehicle, and the sensors are located along a front and a rear of the vehicle, and the sensors along the front and the rear include a combination of one or more cameras and ultrasonic sensors. The on-board computer is configured for receiving data from the combination of said one or more cameras and said ultrasonic sensors. The on-board computer is configured for determining that a space in front of said vehicle is clear to enable movement of the vehicle using said data from the combination of said camera and said ultrasonic sensors from said front of the vehicle. The on-board computer enabling the vehicle for movement forward toward a parking space, and while said vehicle is moving, continuing to determine that the space in front of said vehicle remains clear as the vehicle continues to move toward the parking space and stopping said movement while the space is determined to not be clear by way of a detected obstacle along a path of said movement. The on-board computer stops said vehicle upon detecting that the vehicle has arrived at a destination location for parking of said vehicle.

In a host vehicle a threat number is determined for a target vehicle based on respective dimensions of the target and host vehicles, and a heading angle of the host vehicle. A host vehicle subsystem is actuated based on the threat number.

A system for navigating a vehicle automatically from a current location to a destination location without a human operator is provided. The system of the vehicle includes a global positioning system (GPS) for identifying a vehicle location and a communications system for communicating with a server of a cloud system. The server is configured to identify that the vehicle location is near or at a parking location. The communications system is configured to receive mapping data for the parking location from the server, and the mapping data is at least in part used to find a path at the parking location to avoid a collision of the vehicle with at least one physical object when the vehicle is automatically moved at the parking location. The mapping data is processed by electronics of the vehicle so that when the vehicle is automatically moved collision with the at least one physical object is avoided and the electronics of the vehicle is configured to process a combination of sensor data obtained by sensors of the vehicle. The processing of the sensor data uses image data obtained from one or more cameras and light data obtained from one or more optical sensors.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

A collision avoidance control method for a vehicle, through which a collision avoidance control apparatus controls a vehicle to avoid a collision. The collision avoidance control method includes: calculating a TTC (Time To Collision) between the vehicle and a rearward vehicle, when the rearward vehicle approaching the rear of the vehicle is sensed; determining whether the vehicle and the rearward vehicle are likely to collide with each other, by comparing the TTC to a preset reference TTC; and performing a collision avoidance function when it is determined that the vehicle and the rearward vehicle are likely to collide with each other, the collision avoidance function including one or more of a collision risk warning signal output function, a forward acceleration control function and a lane change control function.

Various technologies described herein pertain to generating an occupancy grid movie for utilization in motion planning for the autonomous vehicle. The occupancy grid movie can be generated for a given time and can include time-stepped occupancy grids for future times that are at predefined time intervals from the given time. The time-stepped occupancy grids include cells corresponding to regions in an environment surrounding the autonomous vehicle. Probabilities can be assigned to the cells specifying likelihoods that the regions corresponding to the cells are occupied at the future times. Moreover, cached query objects that respectively specify indices of cells of a grid occupied by a representation of an autonomous vehicle at corresponding orientations are described herein. An occupancy grid for the environment surrounding the autonomous vehicle can be queried to determine whether cells of the occupancy grid are occupied utilizing a cached query object from the cache query objects.

A travelling track prediction method and device for a vehicle are provided. The method includes that: calculating a plurality of potential positions to which is to be reached by a target vehicle within a preset time within a sensible range of a main vehicle; selecting at least two positions from the plurality of potential positions as target positions; predicting a plurality of travelling tracks to each target position for the target vehicle based on travelling state information of the target vehicle; and selecting at least one travelling track from the plurality of travelling tracks as a prediction result of the target vehicle based on environment information around the target vehicle. According to the embodiments, the travelling track of the target vehicle around the main vehicle may be accurately predicted based on travelling state information and the environment information.

A collision avoidance system for a subject vehicle. The system includes a secondary vehicle detection module that, based on at least one of inputs from sensors of the subject vehicle or a message transmitted by a secondary vehicle, detects the following: location, speed, and heading of the secondary vehicle, and whether the secondary vehicle intends to turn or change lanes. A warning module warns an operator of the subject vehicle of the secondary vehicle and the identified intention of the secondary vehicle, and modifies warning intensity based on the detected intention of the secondary vehicle to turn or change lanes. An adaptive cruise control module modifies at least one of speed and heading of the subject vehicle based on the detected intention of the secondary vehicle to turn or change lanes.

A vehicle driving control apparatus includes a communication interface configured to receive, from a sound sensor, a signal corresponding to sound that is generated in an external environment, and a processor configured to identify a sound object generating the sound, by obtaining a type of the sound object and either one or both of a direction of the sound object and a distance from the sound object to a vehicle including the vehicle driving control apparatus, based on the received signal, and control driving of the vehicle, based on the identified sound object.

Disclosed are a driver assistance system for a vehicle, the driver assistance system comprising: a camera disposed on the vehicle to have a field of view of an outside of the vehicle, and configured to acquire external image data; a radar disposed on the vehicle to have a field of sensing of an outside of the vehicle, and configured to acquire radar data; and a controller including a processor configured to process the image data and the radar data, determine a cut-in area of a nearby vehicle on the basis of the image data acquired by the camera, determine a target vehicle on the basis of the determined cut-in area, and control at least one of a braking device or a steering device of the vehicle to avoid a collision with the target vehicle.