An adaptive cruise control system includes an information acquisition unit having a main detector and a secondary detector, a control unit, and an execution unit. The main detector detects an object located ahead of the vehicle. The control unit determines whether control of the vehicle is required depending on an actual value determined by the main detector and the threshold value of a system property characterizing the driving environment. The execution unit controls the vehicle. The secondary detector is arranged such that its field of view for detecting an object located at an angle ahead of the vehicle covers the boundary of the main detector's field of view, and which is oriented outwards in relation to the forward direction of the vehicle. The secondary detector sends an indication signal to adjust the threshold value of the system property when an object is detected.

The present disclosure relates to a vehicle and control method thereof, to a vehicle having a driver assistance system for assisting a driver. When a lane change is requested even though it does not meet the predetermined lane change condition, present disclosure provides a vehicle driver assistance system (ADAS) that can actively indicate a lane change intention to an adjacent vehicle through ‘deflected driving in a lane’ and perform lane change safely after confirming the yield/overtake intention of the adjacent vehicle. It is an aspect of the present disclosure to provide a control method of a vehicle, including: confirming whether the surrounding situation of the vehicle satisfies a lane change condition when a lane change command occurs while the vehicle is driving autonomously; performing deflected driving in the lane of the vehicle to indicate a lane change intention when the surrounding situation of the vehicle does not satisfy the lane change condition; and performing a lane change corresponding to the lane change command when the yield intention for the lane change intention is confirmed from another vehicle around the traveling lane after indicating the lane change intention through the deflected driving.

The present invention is to obtain a control device and a control method capable of appropriately assisting driving of a straddle-type vehicle by a rider.

In a control device (12) and a control method of the present invention, an acquisition section of the control device (12) configured to control an operation of a straddle-type vehicle (10) acquires prediction information about a future lane change by a preceding vehicle that travels ahead of the straddle-type vehicle (10), and a control section of the control device (12) causes the straddle-type vehicle (10) to execute a safety operation (for example, causes a notification device (15) to issue a warning of the lane change to the rider), when the prediction information satisfies a determination criterion during a slipping-through traveling of the straddle-type vehicle (10).

Methods and systems for controlling navigation of a vehicle are disclosed. The system will first detect a URU within a threshold distance of a drivable area that a vehicle is traversing or will traverse. The system will then receive perception information relating to the URU, and use a plurality of features associated with each of a plurality of entry points on a drivable area boundary that the URU can use to enter the drivable area to determine a likelihood that the URU will enter the drivable area from that entry point. The system will then generate a trajectory of the URU using the plurality of entry points and the corresponding likelihoods, and control navigation of the vehicle while traversing the drivable area to avoid collision with the URU.

A method for monitoring the environment of a vehicle includes evaluating physical measurement data obtained from the environment of the vehicle to determine whether at least one person is approaching the vehicle, how many people approach the vehicle may also be recorded. The method includes evaluating physical measurement data obtained from the environment of the vehicle to determine whether at least one person is moving away from the vehicle and, if appropriate, the number of people that are moving away from the vehicle is also recorded. The method further includes carrying out a check as to whether the number of people that have moved away from the vehicle corresponds to the number of people that have previously approached the vehicle. In response to the check resulting in a difference, it is determined that the vehicle is in an unsafe state.

The present disclosure relates to an apparatus and method for controlling a brake system based on a driver's forward gaze.

Trajectory generation for controlling motion or other behavior of an autonomous vehicle may include alternately determining a candidate action and predicting a future state based on that candidate action. The technique may include determining a cost associated with the candidate action that may include an estimation of a transition cost from a current or former state to a next state of the vehicle. This cost estimate may be a lower bound cost or an upper bound cost and the tree search may alternately apply the lower bound cost or upper bound cost exclusively or according to a ratio or changing ratio. The prediction of the future state may be based at least in part on a machine-learned model's classification of a dynamic object as being a reactive object or a passive object, which may change how the dynamic object is modeled for the prediction.

While operating a host vehicle in a lane, a target vehicle is detected entering the lane in front of the vehicle. A trajectory of the target vehicle is predicted based on sensor data. Upon determining that the target vehicle will pass through the lane based on the predicted trajectory, the host vehicle is operated based on determining a presence or an absence of a lead vehicle. Upon determining that the target vehicle will remain in the lane based on the predicted trajectory, the host vehicle is operated with the target vehicle as the lead vehicle.

Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling monitoring analysis and reaction to subtle sources of information that aid in prediction and response of vehicle control systems across a range of automation levels. Such systems, components, and methodologies include wheel-turn detection equipment for detecting a wheel angle of another vehicle to trigger a vehicle control system to perform an operation based on the detected wheel angle of the other vehicle.

A driver assistance method for an ego vehicle (EGO) travelling in a traffic lane, includes: identifying traffic surrounding the ego vehicle in the same traffic lane as the ego vehicle and in adjacent parallel lanes travelling in the same direction; determining a virtual barycentric target, including calculating a position of the virtual barycentric target, a speed of the virtual barycentric target, and an acceleration of the virtual barycentric target; calculating a longitudinal speed setpoint of the ego vehicle, an acceleration setpoint, and a torque setpoint, the longitudinal speed setpoint being a function of the position of the virtual barycentric target, the speed of the virtual barycentric target, and the acceleration of the virtual barycentric target.