Systems and methods may coordinate and provide bidirectional energy transfer events between electrified vehicles and other vehicles, devices, and/or structures. A power outage map can automatically be generated in response to a power outage condition of a grid power source. Both a power outage zone and a predicted power outage zone may be identified within the power outage map. A notification, alternative drive route recommendation, etc. may be sent to users of the bidirectional energy transfer system who are operating their vehicles near the power outage zone or the predicted power outage zone.

Methods and systems for distributed detection of road conditions and damage are described. In one embodiment, a method for distributed detection of road conditions and damage is provided. The method includes receiving, from one or more mobile devices, a plurality of reports of anomalies associated with roads in a geographic area. The method also includes storing the received reports of anomalies in a database and comparing each report of an anomaly to stored reports of previous anomalies in the database. The method further includes determining whether each report of an anomaly indicates road damage or a temporary problem. The method includes generating a prioritized list of locations of anomalies associated with one or more roads that have been determined to have road damage that needs maintenance and/or repair.

According to an aspect of an embodiment, operations may comprise receiving a plurality of frame sets generated while navigating a local environment, receiving an occupancy map (OMap) representation of the local environment, for each of the plurality of frame sets, generating, using the OMap representation, one or more instances each comprising a spatial cluster of neighborhood 3D points generated from a 3D sensor scan of the local environment, and classifying each of the instances as dynamic or static, tracking instances classified as dynamic across the plurality of frame sets using a tracking algorithm, assigning a single instance ID to tracked instances classified as dynamic across the plurality of frame sets, estimating a bounding box for each of the instances in each of the plurality of frame sets, and employing the instances as ground truth data in a training of one or more deep learning classifiers.

A method of manufacturing a semiconductor nanowire semiconductor device is described. The method includes forming an amorphous channel material layer on a substrate, patterning the channel material layer to form semiconductor nanowires extending in a lateral direction on the substrate, and forming a cover layer covering an upper of the semiconductor nanowire. The cover layer and the nanowire are patterned to form a trench exposing a side section of an one end of the semiconductor nanowire and a catalyst material layer is formed in contact with a side surface of the semiconductor nanowire, and metal induced crystallization (MIC) by heat treatment is performed to crystallize the semiconductor nanowire in a length direction of the nanowire from the one end of the semiconductor nanowire in contact with the catalyst material.

A system for determining and executing an autonomous-vehicle vehicle travel route, including a hardware-based processing unit and a non-transitory computer-readable storage medium. The storage medium includes an input-interface module that, when executed by the hardware-based processing unit, obtains factor data indicating factors relevant to determining a vehicle travel route. The storage medium also includes a route-generation module comprising a route-complexity sub-module. The route-complexity sub-module determines, based on the factor data, route-complexity indexes corresponding to respective optional routes. The route-generation module determines the vehicle travel route based on the route-complexity indexes. The storage in various embodiments includes other sub-modules associated with other elements, such as autonomous-driving safety, comfort, stress, pollution, scenery, or infrastructure-accessibility, for determining and executing an autonomous-driving travel route. In some embodiments, the storage includes an autonomous-driving perceptions module and an autonomous-driving control module for modifying vehicle functions in executing the autonomous-driving travel route.

Navigation devices and methods of operation are provided. The navigation device includes a communication unit; a display; an input unit for receiving an input of data; a communication unit; and a controller for controlling operation of the display and the input unit. The controller connects to a data server through the communication unit, requests path setting information to the data server, receives the path setting information from the data server, acquires present position information of the navigation device, acquires a user moving path by reflecting the acquired position information and the received path setting information, and sets the user moving path as a guidance path. In this case, the path setting information is generated in another electronic device or the data server based on user input information input from the another electronic device.

Aspects of the disclosure provide for controlling an autonomous vehicle using no block costs in space and time. For instance, a trajectory for the autonomous vehicle to traverse in order to follow a route to a destination may be generated. A set of no-block zones through which the trajectory traverses may be identified. A no-block zone may be region where the autonomous vehicle should not stop but can drive through in an autonomous driving mode. For each given no-block zone of the set, a penetration cost that increases towards a center of the no-block zone and decreases towards edges of the no-block zone may be determined. Whether the autonomous vehicle should follow the trajectory may be determined based on the penetration cost. An autonomous vehicle may be controlled in the autonomous driving mode according to the trajectory based on the determination of whether the autonomous vehicle should follow the trajectory.

A process for displaying crime deterrent effects includes first receiving patrol route information indicating a patrol route taken by a law enforcement patrol and determining a type of the law enforcement patrol. Subsequently, a deterrent effect parameter associated with the law enforcement patrol is determined as a function of the determined type of the law enforcement patrol. Finally, an electronic display is caused to display a cartographic map of a geographic area at least partially including the patrol route taken by the law enforcement patrol and, along the patrol route taken, to display a deterrent effect indicator having a radius, width, size, and/or fade time that varies as a function of the type of the determined deterrent effect parameter.

An information processing device (20) includes a route acquisition unit (202) and an automatic driving section determination unit (204). The route acquisition unit (202) acquires route information indicating a moving route of a mobile body. The automatic driving section determination unit (204) acquires adaptation coefficients for a plurality of sections included in the moving route indicated by the route information, with reference to an adaptation coefficient storage unit (206) that stores automatic driving adaptation coefficients set for the respective sections. Further, the automatic driving section determination unit (204) determines the automatic driving sections of the mobile body in the moving route, based on the acquired adaptation coefficients.

A vehicle traveling control system according to the example in the present disclosure communicates with an automatic operation control system which drafts a traveling plan of the vehicle, and performs an automatic traveling control for automatically running the vehicle along the traveling plan received from the automatic operation control system. The vehicle traveling control system predicts a risk based on information about surrounding environment of the vehicle, and performs, when the risk is predicted, a risk avoidance control to intervene in the automatic traveling control in order to avoid the risk. When the risk avoidance control is executed, the vehicle traveling control system transmits information on the risk avoidance control to the automatic operation control system.