In non-limiting examples of the present disclosure, systems, methods and devices for surfacing drive safety notifications are provided. A personal driving pattern library comprising first data associated with a first user for a plurality of road sections included in a first route may be maintained. A global driving pattern library comprising second data associated with a plurality of users for the plurality of road sections included in the first route may be maintained. A determination may be made that the first user is going to travel the first route. A first drive safety score for the first user driving the first route may be calculated. A determination may be made that the first drive safety score is below a threshold value. A drive safety notification may be caused to be surfaced.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Systems, apparatuses and methods may provide for technology that generates, via a first neural network such as a grid network, a first vector representing a prediction of future behavior of an autonomous vehicle based on a current vehicle position and a vehicle velocity. The technology may also generate, via a second neural network such as an obstacle network, a second vector representing a prediction of future behavior of an external obstacle based on a current obstacle position and an obstacle velocity, and determine, via a third neural network such as a place network, a future trajectory for the vehicle based on the first vector and the second vector, the future trajectory representing a sequence of planned future behaviors for the vehicle. The technology may also issue actuation commands to navigate the autonomous vehicle based on the future trajectory for the vehicle.

A vehicle control device controls travel of a vehicle by performing state transition for a plurality of control states having different driving assistance levels based on vehicle surrounding information. The vehicle control device comprises: an acquisition unit configured to acquire the vehicle surrounding information; and a control unit configured to control the state transition and braking operation of the vehicle based on the information acquired by the acquisition unit, wherein, based on the information, the control unit is configured to transition from a first control state set for travel of the vehicle to a second control state with a lower driving assistance level in a case where it is determined that another vehicle is crossing a lane line in front of the vehicle in a lane where the vehicle is traveling.

The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwritable state or taking measures for preventing the transmission of the image to a cloud server.

Techniques for controlling a protection apparatus are provided. An example method includes detecting an offset collision or diagonal collision, and activating a suitable protection apparatus for protecting the side or head of a passenger at a timing in accordance with the degree of collision. An example controller may include a level calculation part for calculating a level of a front face collision, a ΔV.sub.offset calculation part for making an offset adjustment of a speed (ΔV), and a determination part for determining an offset collision or diagonal collision based on the level of the front face collision and the ΔV.sub.offset.

Techniques for controlling a protection apparatus are provided. An example method includes detecting an offset collision or diagonal collision, and activating a suitable protection apparatus for protecting the side or head of a passenger at a timing in accordance with the degree of collision. An example controller may include a level calculation part for calculating a level of a front face collision, a ΔV.sub.offset calculation part for making an offset adjustment of a speed (ΔV), and a determination part for determining an offset collision or diagonal collision based on the level of the front face collision and the ΔV.sub.offset.

The control apparatus (200) is an apparatus that controls the travel of a target vehicle (10). The control apparatus (200) detects a partial object (20) using a sensor. The partial object (20) is a part of an object riding on the target vehicle (10) and is jutting outside the target vehicle (10). Furthermore, the control apparatus (200) outputs information (travel information) relating to travel of the target vehicle (10) based on the detected partial object (20). For example, the travel information is control information for travel control of the target vehicle (10) and notification information indicating information relating to the partial object (20).

The control apparatus (200) is an apparatus that controls the travel of a target vehicle (10). The control apparatus (200) detects a partial object (20) using a sensor. The partial object (20) is a part of an object riding on the target vehicle (10) and is jutting outside the target vehicle (10). Furthermore, the control apparatus (200) outputs information (travel information) relating to travel of the target vehicle (10) based on the detected partial object (20). For example, the travel information is control information for travel control of the target vehicle (10) and notification information indicating information relating to the partial object (20).