Systems, methods, and computer program products to enhance the situational competency and/or the safe operation of a vehicle, when operating at least partially in an autonomous mode, as a support vehicle for one or more on-road persons engaged in a training or competitive cycling, running, and/or walking activity on a predetermined travel route at a predetermined pace.

An example operation includes one or more of determining a characteristic of an occupant in a transport and a current driving environment of the transport, wherein the characteristic includes a position of the occupant, determining that the current driving environment will lead to a collision of the transport, and based on a predicted result of the collision, sending a predicted state of the occupant based on the position, to an emergency service node.

Methods, systems, apparatus, and non-transitory computer readable media are described for using a vehicle as a payment device. Various aspects may include receiving a selection of a stored financial card or financial account at a vehicle head unit. The selected financial card or financial account may be transmitted to a point-of-sale (POS) terminal for making a payment by transmitting a tokenized card number to the POS terminal. The tokenized card number may be transmitted over a very short-range communication link to ensure that the transmission is secure. For example, electronic circuitry may be attached to the exterior of the vehicle, where the electronic circuitry may be within a threshold distance (e.g. one inch, three inches, six inches, one foot, three feet, etc.) of the POS terminal. The tokenized card number may be transmitted from the vehicle head unit to the electronic circuitry and then to the POS terminal.

Systems and methods for providing product samples to users in autonomous vehicles, thereby allowing businesses to advertise their products via the rideshare platform. A physical advertising platform is provided leveraging existing rideshare and delivery infrastructure to allow businesses to advertise their products by providing samples in rideshare vehicles and/or with rideshare vehicle deliveries. Consumers have the opportunity to try new products from local businesses that they may otherwise not be exposed to. In some implementations, a rideshare application interface can allow users to see what new local product samples are available. In some examples, a user can select one or more product samples to try.

A small-object perception system, for use in a vehicle, includes a stereo vision system that captures stereo images and outputs information identifying an object having a dimension in a range of ˜20 cm to about ˜100 cm in a perception range of ˜3 meters to ˜150 meters from the vehicle, and a system controller configured to receive output signals from the stereo vision system and to provide control signals to control a path of movement of the vehicle. The stereo vision system includes cameras separated by a baseline of ˜1 meter to ˜4 meters. The stereo vision system includes a stereo matching module configured to perform stereo matching on left and right initial images and to output a final disparity map based on a plurality of preliminary disparity maps generated from the left and right initial images, with the preliminary disparity maps having different resolutions from each other.

A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Systems and methods for monitoring the lane of an object in an environment of an autonomous vehicle are disclosed. The methods include receiving sensor data corresponding to the object, and assigning an instantaneous probability to each of a plurality of lanes based on the sensor data as a measure of likelihood that the object is in that lane at a current time. The methods also include generating a transition matrix for each of the plurality of lanes that encode one or more probabilities that the object transitioned to that lane from another lane in the environment or from that lane to another lane in the environment at the current time. The methods then include determining an assigned probability associated with each of the plurality of lanes based on the instantaneous probability and the transition matrix as a measure of likelihood of the object occupying that lane at the current time.

A system and method operate an autonomous vehicle. A sensor senses a road and an object. A processor determines, in a Cartesian reference frame, a representation of the road and a source point representative of the object, samples a first waypoint and a second waypoint from the representation of the road, determines a linear projection of the source point to a line connecting the first waypoint and the second waypoint, determines a first estimate of a longitudinal component of the source point in a road-based reference frame based on the linear projection, the first estimate being on a curve representing the road between the first waypoint and the second waypoint, determines a second estimate of the longitudinal component from the first estimate, determines a coordinate of the source point in the road-based reference frame from the second estimate and operates the vehicle with respect to the object using the coordinate.

Systems and methods are provided for influential control over a driver's hand(s) that grip a vehicle's steering wheel. Upon issuing an autonomous control signal to control motive operation of the vehicle, an autonomous control system of the vehicle may further reinforce the application of the autonomous control signal by inducing the driver's hand(s) to grip/increase grip strength on the vehicle's steering wheel or by releasing the grip/decreasing grip strength on the vehicle's steering wheel. Moreover, the increasing/decreasing of the driver's grip may alternatively, or in addition to the reinforcement aspect, induce augmentative or intervening action(s)/behavior(s) by the driver.

A method for ascertaining a depth information image for an input image. The input image is processed using a convolutional neural network, which includes multiple layers that sequentially process the input image, and each converts an input feature map into an output feature map. At least one of the layers is a depth map layer, the depth information image being ascertained as a function of a depth map layer. In the depth map layer, an input feature map of the depth map layer is convoluted with multiple scaling filters to obtain respective scaling maps, the multiple scaling maps are compared pixel by pixel to generate a respective output feature map in which each pixel corresponds to a corresponding pixel from a selected one of the scaling maps.