A system includes a vehicle control module, a vehicle gateway module, and a wired vehicle communications network communicatively coupling the vehicle gateway module to the vehicle control module. The vehicle control module is programmed to receive sensor data from at least one sensor, execute a machine-learning program trained to determine whether the sensor data satisfies at least one criterion, and transmit the sensor data satisfying the at least one criterion to the vehicle gateway module. The vehicle gateway module is programmed to transmit the machine-learning program to the vehicle control module; upon receiving the sensor data from the vehicle control module, store the sensor data; and upon establishing a connection with a remote server, transmit the sensor data to the remote server.

Techniques for determining an object contour are discussed. Depth data associated with an object may be received. The depth data, such as lidar data, can be projected onto a two-dimensional plane. A first convex hull may be determined based on the projected lidar data. The first convex hull may include a plurality of boundary edges. A longest boundary edge, having a first endpoint and a second endpoint, can be determined. An angle can be determined based on the first endpoint, the second endpoint, and an interior point in the interior of the first convex hull. The longest boundary edge may be replaced with a first segment based on the first endpoint and the interior point, and a second segment based on the interior point and the second endpoint. An updated convex hull can be determined based on the first segment and the second segment.

The present disclosure relates to navigational systems for vehicles. In one implementation, such a navigational system may receive a first output from a first sensor and a second output from a second sensor; identify a target object in the first output; determine whether the target object is included in the second output; and determine a detected driving condition associated with the target object and whether the condition triggers a navigational constraint. If the navigational constraint is not triggered, the system may cause a first navigational adjustment if the target object is included in both the first output and the second output, and may forego any navigational adjustments if the target object is included in the first output but not in the second output. If the navigational constraint is triggered and the target object is included either in the first or second output, the system may cause a second navigational adjustment.

A vehicle control apparatus includes an electric control unit that performs a preceding vehicle trailing control which makes an own vehicle trail a preceding vehicle as an adaptive cruise control, and performs a first brake control which automatically applies a first braking control to the own vehicle when a time-to-collision to a target object is less than a first threshold. In a case where a performing condition for the first brake control has been determined to be satisfied during a performance of the adaptive cruise control, the electric control unit continues performing the adaptive cruise control without performing the first brake control when a deceleration control by the adaptive cruise control is being performed, whereas stops performing the adaptive cruise control when the deceleration control by the adaptive cruise control is not being performed.

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.

System and methods are provided that allow users of shared vehicles to benefit from an enhanced user experience that seamlessly unlocks and/or provides access to features for autonomous vehicles by proactively computing an interest index based on detected contextual behavioral patterns of the pedestrians such as the trajectory a candidate passenger is walking given a locational context.

System and methods are provided that contextually define interest index requirements for shared and autonomous vehicles. An interest index is computed based on detected contextual behavioral patterns of pedestrians such as the trajectory a candidate passenger is walking given a locational context. The use of the interest index allows users of shared vehicles to benefit from an enhanced user experience that seamlessly unlocks and/or provides access to features for autonomous vehicles based on the interest index.

A vehicle control system includes an automatic driving control device that generates a target trajectory used for automatic driving, and a vehicle travel control device that executes vehicle travel control such that a vehicle follows the target trajectory. The vehicle travel control device determines whether an operating condition of travel support control for reducing a risk when the vehicle travels is satisfied based on driving environment information, acquired from a plurality of sensor devices, and executes the travel support control in a case where the operating condition is satisfied. The vehicle travel control device generates risk information based on the driving environment information, and transmits the risk information to the automatic driving control device before the operating condition is satisfied. The automatic driving control device generates or corrects the target trajectory based on the received risk information.

Aspects and implementations of the present disclosure relate to autonomous vehicle (AV) trajectories computed using a box-based probabilistic overlap model. An example method includes: receiving, by a data processing system of an AV, data descriptive of an agent state of an object relative to the AV; computing an initial overlap region between a first box representative of the AV and a second box representative of the agent state; updating dimensions of the second box; and computing an updated overlap region by interpolating the initial overlap region based on the updated dimensions of the second box.

A driving support apparatus according to the invention estimates the position of a moving body by controlling a position estimation unit when the tracking-target moving body leaves a first area or a second area to enter a blind spot area and detects the position of the moving body by controlling a position detection unit when the moving body leaves the blind spot area to enter the first area or the second area. In this manner, the trajectory of the tracking-target moving body is calculated so that the trajectory of the moving body detected in the first area or the second area and the trajectory of the moving body estimated in the blind spot area are continuous to each other and driving support is executed based on the calculated trajectory of the tracking-target moving body.