An embodiment apparatus for preventing a collision at an intersection includes a communication device configured to receive map information, location information, an image around a vehicle, ultrasonic sensor data, or traffic light information, a right turn prediction device configured to predict whether the vehicle will make a right turn at the intersection, based on the map information, the location information, or the image around the vehicle, a right turn performance determination device configured to determine whether the vehicle is able to make the right turn safely, based on the image around the vehicle, the ultrasonic sensor data, or the traffic light information, in response to a prediction that the vehicle will make the right turn at the intersection, and a controller configured to control the vehicle according to the determination of whether the vehicle is able to make the right turn safely.

Among other things, a command is received expressing an objective for operation of a vehicle within a denominated travel segment of a planned travel route. The objective spans a time series of (for example, is expressed at a higher or more abstract level than) control inputs that are to be delivered to one or more of the brake, accelerator, steering, or other operational actuator of the vehicle. The command is expressed to cause operation of the vehicle along a selected man-made travel structure of the denominated travel segment. A feasible manner of operation of the vehicle is determined to effect the command. A succession of control inputs is generated to one or more of the brake, accelerator, steering or other operational actuator of the vehicle in accordance with the determined feasible manner of operation.

When a collision avoidance target is a pedestrian or a bicycle, a driving assistance ECU performs automatic braking control. In this case, accelerator override cannot be performed. When the collision avoidance target is an automobile and when an accelerator operation amount is equal to or larger than a first operation amount threshold, the driving assistance ECU prohibits the automatic braking control. In this case, the accelerator override can be performed. When the accelerator operation amount is smaller than the first operation amount threshold, the driving assistance ECU performs the automatic braking control.

A vehicle controller of a subject vehicle includes a processor that: recognizes a surrounding state of the subject vehicle traveling in a lane on a road; detects a specific target object in a specific area; provides control such that the subject vehicle follows a vehicle traveling ahead thereof; and makes the subject vehicle operate in at least one of a first support status and a second support status having an automated degree higher than the first and realized only when the subject vehicle is traveling in the specific area. When the subject vehicle is traveling in the specific area in the first support status and the specific target object has been detected therein, the processor keeps the support status of the subject vehicle unchanged at the first support status; and, in the second support status, shifts the support status of the subject vehicle to the first support status.

A driving support device performs steering control and deceleration control for avoiding an object which is detected in front of a host vehicle. The driving support device performs: calculating a target lateral distance which is a target of the steering control and which is a lateral distance between the host vehicle and the object when the host vehicle passes by the object; and increasing target deceleration which is a target of the deceleration control and which is deceleration of the host vehicle when the host vehicle passes by the object as a lateral distance restraint value which is obtained by subtracting the target lateral distance from a threshold value increases when the target lateral distance is less than the threshold value.

According to one aspect, an overall airbag system of an autonomous vehicle uses a combination of sensors to deploy one or more external airbags in advance of a collision or as a collision occurs, for the purpose of protecting vulnerable persons. By using sensor data, combined with perception and prediction algorithms, an autonomous driving system may deploy a substantially optimal combination of external airbags for a given the size of a vulnerable person, vehicle speed, and/or collision timing. In addition to cushioning impact during a collision, the deployment of multiple external airbags may also control kinematics of vulnerable persons, as for example by addressing brain injuries in pedestrians due to rotational kinematics.

A system comprises an autonomous vehicle (AV) and a control device operably coupled with the AV. The control device detects a series of events within a threshold period of time, where a number of series of events in the series of events is above a threshold number. The series of events taken in the aggregate within the threshold period of time deviates from a normalcy mode. The normalcy mode comprises events that are expected to the encountered by the AV. The control device determines whether the series of events corresponds to a malicious event, where the malicious event indicates tampering with the AV. In response to determining that the series of events corresponds to the malicious event, the series of events are escalated to be addressed.

A driving assistance method includes: detecting a first other vehicle entering an intersection on a first route where a host vehicle is traveling from a second route; predicting whether or not the first other vehicle will stop in the intersection, and predicting a stop position of the first other vehicle; calculating a minimum distance of a first gap between a vehicle body of the first other vehicle and a surrounding object around the first other vehicle or between the vehicle body of the first other vehicle and a road edge of a travel lane of the first other vehicle when the first other vehicle stops at the predicted stop position; and predicting according to the calculated minimum distance whether or not a second other vehicle, which is a following vehicle behind the first other vehicle, may slip through the first gap from behind the first other vehicle.

Systems and methods for operating a vehicle are disclosed. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle while the vehicle is in motion; detecting an object within a given distance from the vehicle; generating at least one possible object trajectory for the object which was detected; performing a collision check to determine whether a collision between the vehicle and the object can be avoided based on the vehicle trajectory and the at least one possible object trajectory; performing a plausibility check to determine whether the collision is plausible based on content of a map, when a determination is made in the collision check that a collision between the vehicle and the object cannot be avoided; and performing operations to selectively cause the vehicle to perform an emergency maneuver based on results of the plausibility check.

A system may receive point cloud data that includes one or more data points associated with an object that was detected by sensors of an autonomous vehicle. The system may identify a subset of the point cloud data having data points that are associated with a likelihood of a pedestrian entering a scene with the object, determine a current probability value using a logistic function that is associated with the subset of the point cloud data, determine, based at least in part on the current probability value, a probability value representing a likelihood of the pedestrian actually being present for the subset of the point cloud data, determine whether the probability value exceeds a false alarm threshold value, and in response to the probability value exceeding the false alarm threshold value, assign data points of the subset an attribute value indicative of the pedestrian being present.