A vehicle driving assist device comprises: an oncoming moving body recognizer configured to recognize an oncoming moving body; a risk determination region setting unit configured to set a risk determination region for calculating a risk degree that decreases as a distance outward from a center of the oncoming moving body in a width direction of the oncoming moving body increases; a risk degree calculator configured to calculate the risk degree for the oncoming moving body in accordance with an overlap state between the target traveling path of the vehicle and the risk determination region; and a preliminary collision avoidance controller configured to recognize the oncoming moving body as the obstacle in accordance with the risk degree, and perform preliminary collision avoidance control in response to the oncoming moving body recognized as the obstacle prior to the emergency collision avoidance control.

A vehicle driving assist device includes an oncoming moving body recognizer configured to recognize an oncoming moving body; a lateral position distribution characteristics acquisition unit configured to acquire distribution characteristics of a lateral position of the oncoming moving body; a risk determination region setting unit configured to set, based on the distribution characteristics, a risk determination region for calculating a risk degree; a risk degree calculator configured to calculate the risk degree for the oncoming moving body; and a preliminary collision avoidance controller configured to recognize the oncoming moving body as the obstacle in accordance with the risk degree, and perform preliminary collision avoidance control in response to the oncoming moving body prior to the emergency collision avoidance control. The risk determination region setting unit is further configured to variably set the risk determination region so that the risk degree relatively increases as the distribution characteristics tend to disperse.

A mobile object control device according to an embodiment includes a recognizer configured to recognize a surroundings situation of a mobile object, a contact likelihood determiner configured to change a condition for determining that there is a likelihood that the mobile object and the object will come into contact with each other in the future on the basis of a state of an object around the mobile object recognized by the recognizer, and determine the likelihood that the mobile object and the object will come into contact with each other in the future on the basis of the changed condition.

A vehicle driving assist device includes a processor that functions as a receiver, an emergency collision avoidance controller, and a preliminary collision avoidance controller. The receiver receives, in relation to an oncoming moving body moving in an oncoming lane adjacent to a traveling lane of a vehicle and having a velocity component in a direction opposite to a traveling direction of the vehicle, a risk degree calculated based on a history of a distance from a lane marker defining the oncoming lane to the oncoming moving body, by communication with a device outside the vehicle. Upon determination that the vehicle is highly likely to collide with an obstacle, the emergency collision avoidance controller performs emergency collision avoidance control. The preliminary collision avoidance controller recognizes the oncoming moving body as the obstacle in accordance with the risk degree, and performs preliminary control prior to the emergency collision avoidance control.

Provided is a method for evaluating a performance of an autonomous driving algorithm performed by one or more processors, including determining a first parameter set and a second parameter set which are associated with a driving of an ego vehicle in which the autonomous driving algorithm is applied and a driving of a surrounding vehicle, based on a collision scenario between the ego vehicle and the surrounding vehicle, generating a plurality of cases associated with the collision scenario based on the first parameter set and the second parameter set, and performing a simulation for each of the plurality of cases using the autonomous driving algorithm, in which each parameter of the first parameter set has a fixed value, and each parameter of the second parameter set has a predetermined sweeping range.

A driving assistance apparatus of a vehicle includes a processor configured to calculate a risk sensitivity index on risk avoidance of a driver of the vehicle with respect to a target existing around the vehicle, diagnose a change in the calculated risk sensitivity index, and notify the driver of information on the diagnosed change in the risk sensitivity index.

A mobile object control device according to an embodiment includes a recognizer that recognizes a surroundings situation of a mobile object, and an unavoidable contact determiner that determines whether or not contact between the mobile object and an object likely to come into contact with the mobile object is unavoidable on the basis of a recognition result of the recognizer when there is the object around the mobile object, and the unavoidable contact determiner limits a recognition range of the recognizer to a predetermined range including the object when the recognition result of the recognizer satisfies a predetermined condition, and determines whether or not the contact between the mobile object and the object is unavoidable.

Disclosed herein are system, method, and computer program product embodiments for determining objects that are kinematically capable, even if non-compliant with rules-of-the-road, of affecting a trajectory of a vehicle. The computing system (e.g., perception system, etc.) of a vehicle may generate a trajectory for the vehicle and a respective trajectory for each object of a plurality of objects within a field of view (FOV) of the sensing device associated with the vehicle. The computing system may identify objects of the plurality of objects with trajectories that intersect the trajectory for the vehicle and remove from such objects, objects with trajectories that at least one of exit the FOV or intersect with other objects of the plurality of objects within the FOV. The computing system may select, from remaining objects with trajectories that intersect the trajectory for the vehicle, objects with trajectories that indicate a respective collision between the object and the vehicle and assign a severity of the respective collision.

A mobile object control method including: recognizing physical objects near a mobile object and a route shape; generating a target trajectory based on a result of the recognition and cause the mobile object to travel autonomously along the target trajectory; and determining that an abnormality has occurred in a control system for causing the mobile object to travel autonomously by performing the recognition when a time period from a timing when a degree of deviation between a reference target trajectory determined by the route shape and serving as a reference for generating the target trajectory and a position of the mobile object is greater than or equal to a predetermined degree to a timing when the degree of deviation is less than the predetermined degree is greater than or equal to a first predetermined time period and output a determination result.

An Autonomous Vehicle (AV) system, including: a tracking subsystem configured to detect and track relative positioning of another vehicle that is behind or lateral to an AV configured to comply with a safety driving model, and to check a safety driving model compliance status of the other vehicle; and a risk reduction subsystem configured to plan, based on the safety driving model compliance status of the other vehicle, an AV action, wherein if the safety driving model compliance status of the other vehicle is unknown or is known to be non-compliant, the AV action is administration of a safety driving model compliance test to the other vehicle, or is a maneuver by the AV to reduce risk of collision with a leading vehicle positioned in front of the AV.