Lighting control systems may be commissioned for programming and/or control with the aid of a mobile device. Design software may be used to create a floor plan of how the lighting control system may be designed. The design software may generate floor plan identifiers for each lighting fixture, or group of lighting fixtures. During commissioning of the lighting control system, the mobile device may be used to help identify the lighting devices that have been installed in the physical space. The mobile device may receive a communication from each lighting control device that indicates a unique identifier of the lighting control device. The unique identifier may be communicated by visible light communication (VLC) or RF communication. The unique identifier may be associated with the floor plan identifier for communication of digital messages to lighting fixtures installed in the locations indicated in the floor plan identifier.

A self-learning method for an obstacle and a self-learning method for a new obstacle are provided. With the self-learning method, in step 1, data of a grid map in a movement region is acquired, and each of grids of the grid map is marked as not being traversed. In step 2, a starting grid of the grid map is set, data of the starting grid is pushed into a stack, a movement unit is controlled to move to the starting grid, and the starting grid is remarked as being traversed. In step 3, the movement unit is controlled to traverse the grid map, and boundary data of the obstacle is acquired based on marks of the grids in the grid map. In step 4, boundary data of the obstacle is stored.

Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.

Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.

A method for transferring control of a vehicle from automated vehicle control by a control unit to manual vehicle control by a driver by a control lever, wherein the control lever is used at least to accelerate, brake, and steer the vehicle, wherein there is also at least one first display screen for displaying driving information, including at least an actual speed and an actual trajectory of the vehicle and a speed and a trajectory based on the actual position of the control lever, and wherein automated vehicle control is transferred to manual vehicle control when the actual speed of the vehicle corresponds graphically to the speed based on the actual position of the control lever and the actual trajectory of the vehicle corresponds graphically to the trajectory based on the actual position of the control lever on the first display screen.

A vehicle communication system includes: a communication server and a vehicle control device. The vehicle control device includes at least one electronic control unit configured to: recognize a position of the host vehicle; acquire section information on the communication established section and the communication interrupted section; determine in which section, either the communication established section or the communication interrupted section, the host vehicle is traveling or is to travel; perform system driven control of the host vehicle based on the road condition information when the host vehicle travels in the communication established section; and perform driver driven control of the host vehicle when the host vehicle travels in the communication interrupted section.

A vehicle communication system includes: a communication server and a vehicle control device. The vehicle control device includes at least one electronic control unit configured to: recognize a position of the host vehicle; acquire section information on the communication established section and the communication interrupted section; determine in which section, either the communication established section or the communication interrupted section, the host vehicle is traveling or is to travel; perform system driven control of the host vehicle based on the road condition information when the host vehicle travels in the communication established section; and perform driver driven control of the host vehicle when the host vehicle travels in the communication interrupted section.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

An avoidance route calculation part calculates an avoidance route for avoiding a collision between an own vehicle and an obstacle through a collision avoidance assist control (an automatic brake control and an automatic steering control). A post-avoidance route calculation part calculates a post-avoidance route. A post-avoidance route collision determination part determinates whether a secondary obstacle is present on the post-avoidance route. When the secondary obstacle is determined to be present, the automatic steering control is prohibited from being performed.

An avoidance route calculation part calculates an avoidance route for avoiding a collision between an own vehicle and an obstacle through a collision avoidance assist control (an automatic brake control and an automatic steering control). A post-avoidance route calculation part calculates a post-avoidance route. A post-avoidance route collision determination part determinates whether a secondary obstacle is present on the post-avoidance route. When the secondary obstacle is determined to be present, the automatic steering control is prohibited from being performed.