A collision avoidance assistance device for a vehicle is provided. The collision avoidance assistance device includes a camera configured to acquire an image of an area around the vehicle and a controller. The controller is configured to: detect an image of an animal in the image of the area around the vehicle; determine a type of the animal detected in the image; retrieve behavior characteristics index values representing behavior characteristics of the determined type of the animal; calculate a future presence area of the animal based on the behavior characteristics index values; determine a probability of a collision between the animal and the vehicle based on the calculated future presence area of the animal; and perform a collision avoidance assistance function based on the determined probability of the collision between the animal and the vehicle.

A driver assistance system for a motor vehicle for automated driving with automated longitudinal guidance, wherein when automated longitudinal guidance is active in an automatic mode, automated longitudinal guidance is brought about taking into account a predefinable setpoint speed. The system includes a first detection unit, configured to detect a defined stationary state situation which is set on the basis of a preceding automated braking process of the motor vehicle to the stationary state, a second detection unit, configured to detect accelerator pedal activation, and an evaluation and control unit, configured to actuate a manual mode when actuator pedal activation is detected during a defined stationary state situation.

Embodiments of the present disclosure relate to the technical field of autonomous driving, and in particular to methods for updating an autonomous driving system, autonomous driving systems, and on-board apparatuses. In the embodiments of the present disclosure, the autonomous driving system, in a manual driving mode, senses the surrounding environment of a vehicle, performs vehicle positioning, and plans a path for autonomous driving for the vehicle. However, the autonomous driving system does not issue an instruction to control the driving of the vehicle. Instead, it compares the path with a path along which a driver drives the vehicle in the manual driving mode to update a planning and control algorithm of the autonomous driving system. As such, the updated autonomous driving system better caters to the driving habits of the driver and improves the driving experience for the driver without compromising the reliability of planning and decision-making of autonomous driving.

An apparatus for controlling turning of a vehicle, a system having the same, and a method thereof are provided. The vehicle turning control apparatus include a processor to perform a control operation to determine whether a present situation is a normal turning situation based on steering angle information and wheel speed information of the vehicle, and operate an electronic limited slip differential (eLSD) by making an inner wheel slip based on a turning direction when an operation of the eLSD is failed in the normal turning situation; and a storage to store data obtained by the processor and an algorithm executed by the processor.

A vehicle assistive system includes a plurality of context information generating devices, each configured to output context information relating to a mobile vehicle, a processor, and a non-transitory computer-readable medium comprising instructions for performing acts. The acts include: generating one or more object representations based on corresponding context information; predicting one or more future states, each relating to a state of the object representation at a future time; eliminating the future states having a probability that does not meet a corresponding threshold; detecting a future event for one or more of the future states; providing one or more action items for each detected future event; performing one or more actions associated with the action items including an action selected from the group consisting of generating a notification using a notification device, and controlling the mobile vehicle using a control device.

A computer-implemented method is provided that involves determining, based on map data, an approaching merge region comprising an on-ramp merging with a road comprising one or more lanes, wherein a truck is traveling on an initial lane of the road according to a navigation plan. The method involves an indication of movement of a vehicle on the on-ramp, wherein the indication of movement is based on data collected by one or more sensors configured to capture sensor data from an environment surrounding the truck. The method involves determining, for the on-ramp and the one or more lanes, respective avoidance scores indicative of a likelihood of an interaction between the truck and the vehicle based on the approaching merge region. The method involves updating the navigation plan based on the respective avoidance scores. The method also involves controlling the truck to execute a driving strategy based on the updated navigation plan.

A vehicle engine start/stop control method includes shifting an automatic transmission to a park or neutral position and auto-stopping the engine in response the automatic transmission being in the park or neutral position for a predetermined period of time that begins with a shift of the automatic transmission to the park or neutral position.

A vehicle positioning method via data fusion and a system using the same are disclosed. The method is performed in a processor electrically connected to a self-driving-vehicle controller and multiple electronic systems. The method is to perform a delay correction according to a first real-time coordinate, a second real-time coordinate, real-time lane recognition data, multiple vehicle dynamic parameters, and multiple vehicle information received from the multiple electronic systems with their weigh values, to generate a fusion positioning coordinate, and to determine confidence indexes. Then, the method is to output the first real-time coordinate, the second real-time coordinate, and the real-time lane recognition data that are processed by the delay correction, the fusion positioning coordinate, and the confidence indexes to the self-driving-vehicle controller for a self-driving operation.

Techniques are described herein for generating trajectories for autonomous vehicles using velocity-based steering limits. A planning component of an autonomous vehicle can receive steering limits determined based on safety requirements and/or kinematic models of the vehicle. Discontinuous and discrete steering limit values may be converted into a continuous steering limit function for use during on-vehicle trajectory generation and/or optimization operations. When the vehicle is traversing a driving environment, the planning component may use steering limit functions to determine a set of situation-specific steering limits associated with the particular vehicle state and/or driving conditions. The planning component may execute loss functions, including steering angle and/or steering rate costs, to determine a vehicle trajectory based on the steering limits applicable to the current vehicle state.

Apparatus and methods of the present disclosure provide a solution to quickly sort through and identify relevant data sets from large amounts of data collected by numerous vehicles. This process is a form of data mining where a processor executes instructions out of a memory to evaluate sensor data collected by vehicles over time. These vehicles may be driven by person's such that data collected by those sensors would be representative of how a person drives. After data has been acquired, it may be evaluated to identify portions of data where one vehicle encounters another vehicle along a roadway. Data may be classified as being associated with particular types of driving maneuvers and organized into data sets with labels consistent with the classification or driving maneuver. Classifications could correspond to different typed of driving maneuvers, “turning left across traffic,” “all way stop,” “merging onto a highway,” or “lane change.”