Abstract: An automated signal compliance monitoring and alerting system (ASCMAS) that automatically monitors and provides historical and real-time alerting for mobile assets in violation of a signal aspect, such as a stop light, traffic light, and/or speed limit signal, and/or operating the mobile asset unsafely in an attempt to maintain compliance to a signal. ASCMAS works in conjunction with a data acquisition and recording system (DARS) for mobile assets that includes a data center onboard the mobile asset and a data center remote from the mobile asset. A first artificial intelligence model of at least one of the data centers determines whether the mobile asset is a leading and/or controlling mobile asset. From video content obtained from one of the data centers, a second artificial intelligence model determines an episode involving the mobile asset.

Abstract: A driving control method comprises: acquiring a destination of a vehicle; referring to a first map that includes identification information of a travel lane and a second map that does not include the identification information of the travel lane; calculating a route from a current position of the vehicle to the destination; when traveling along a first route included in the route and belonging to the first map, setting first driving control, while when traveling along a second route included in the route and belonging to the second map, setting second driving control with a lower level of autonomous driving than that of the first driving control; and creating a driving plan for the vehicle to travel along the route with contents of the set driving control. A driving control apparatus is based on the method.

Abstract: An unmanned following vehicle includes a controller that controls the unmanned following vehicle to move in parallel with a moving object by following the moving object on a left side or a right side of the moving object. For example, the controller adjusts a moving speed of the unmanned following vehicle according to a Y-axis coordinate difference value, which is a difference value between a position of the moving object and a position of the unmanned following vehicle in a forward direction. The controller also adjusts a steering direction and a steering angle of the unmanned following vehicle according to an X-axis coordinate difference value, which is a difference value between the position of the moving object and the position of the unmanned following vehicle in a lateral direction.

Abstract: Example embodiments relate to gradually adjusting a vehicle sensor perspective using remote assistance. A computing device may receive a request for assistance from a vehicle operating in an environment. The request indicates that the vehicle is stopped at a location with a sensor perspective of the environment that is at least partially occluded. Responsive to receiving the request for assistance, the computing device may display a graphical user interface (GUI) that represents a current state of the vehicle and includes a selectable option configured to enable the vehicle to gradually move forward a predefined distance. The computing device may detect a selection of the selectable option and transmit instructions that enable the vehicle to gradually move forward the predefined distance. The vehicle can then gradually move forward the predefined distance while also monitoring for one or more changes in the environment responsive to receiving the instructions.

Abstract: Systems and methods for using transmission sensor(s) in localization of an autonomous vehicle (“AV”) are described herein. Some implementations receive instance(s) of transmission sensor data generated by transmission sensor(s) of the AV, generate pose instance(s) of a pose of the AV based on the instance(s) of the transmission sensor data, and cause the AV to be controlled based on the pose instance(s). In some of those implementations, the pose instance(s) can be generated based on steering data the AV that indicates steering angle(s) of the autonomous, and that temporally correspond to the instance(s) of the transmission sensor data. In various implementations, the pose instance(s) may only be generated or utilized based on the instance(s) of the transmission sensor data (and optionally the steering data) in response to detecting an adverse event at the AV.

Abstract: Disclosed are methods and devices related to autonomous driving. In one aspect, a method is disclosed. The method includes determining three-dimensional bounding indicators for one or more first objects in road target information captured by a light detection and ranging (LIDAR) sensor; determining camera bounding indicators for one or more second objects in road image information captured by a camera sensor; processing the road image information to generate a camera matrix; determining projected bounding indicators from the camera matrix and the three-dimensional bounding indicators; determining, from the projected bounding indicators and the camera bounding indicators, associations between the one or more first objects and the one or more second objects to generate combined target information; and applying, by the autonomous driving system, the combined target information to produce a vehicle control signal.

Abstract: Methods, systems, and apparatus for recommending alternative destinations in ride-sharing services are provided. A computing device implementing the method may start with receiving a trip request from a user device. The trip request may include an origin and a destination. Then the computing device classifies the trip request into one of a plurality of trip purpose categories based at least on the origin and the destination of the trip request, the rider's information, and a machine-learning classifier trained to predict the one trip purpose category of the trip request. In response to the one trip purpose category belonging to a preset group of trip purpose categories, the computing device determines one or more alternative destinations for the trip request, and sends to the user device, the one or more alternative destinations.

Abstract: An autonomous mobile device (AMD) may move around while performing tasks. If the AMD is lifted, the AMD responds to ensure safety of the user, modify ongoing operation, and so forth. For example, the AMD may stop the wheels, retract a mast, or suspend navigation tasks. To accurately determine whether or not the AMD has been lifted, the AMD uses one or more sensors to determine a vertical lift distance and rotation of the AMD with respect to one or more axes. For example, while the AMD is stationary, the sensors used may include an accelerometer or a gyrometer. While the AMD is moving, data from time-of-flight sensors or one or more cameras may also be used. If the AMD is stationary low-level sensor thresholds are used. If the AMD is moving steadily, medium-level sensor thresholds are used. If the AMD is suddenly decelerating, high-level sensor thresholds are used.

Abstract: A method, apparatus and computer program product are provided for generating a transition variability index related to autonomous driving. In this regard, a first transition variability index is calculated. The first transition variability index is indicative of a first degree of variability in relation to transition of vehicles from respective autonomous levels while traveling proximate a first spatial reference point. Furthermore, a second transition variability index is generated. The second transition variability index is indicative of a second degree of variability in relation to transition of vehicles from respective autonomous levels while traveling along proximate a second spatial reference point. Updating of transition data associated with one of the first and second spatial reference points relative to another one of the first and second spatial reference points is then prioritized based on a comparison between the first transition variability index and the second transition variability index.

Abstract: A method for controlling switching of steering control rights of an autonomous vehicle, may include: performing a control to synchronize a steering angle of a steering wheel and a steering angle of a road wheel, when switching of the steering control rights from an automated driving mode to a manual driving mode is requested. The method further includes: detecting an error value between the steering angle of the steering wheel and the steering angle of the road wheel, when a hands-on state in which the steering wheel is gripped is detected in the synchronization process. In addition, the method further includes: performing a control to switch the mode of the autonomous vehicle to the manual driving mode, when the error value is less than a preset value.

Abstract: Disclosed is a method of providing a safe navigation route for travelling. The method comprises receiving, at a graphical user interface of a processor-based user device, a query for a navigation route from a user, comprising a source station and a destination station, determining, at an application server, a plurality of navigation routes between the source station and the destination station, analyzing, at the application server, each of the plurality of navigation routes to compute a safety index associated with each of the plurality of navigation routes, identifying, at the application server, at least one safe navigation route between the source station and the destination station, and rendering, at the graphical user interface, the at least one safe navigation route between the source station and the destination station in response to the query from the user.

Abstract: While operating a host vehicle in a lane, a target vehicle is detected entering the lane in front of the vehicle. A trajectory of the target vehicle is predicted based on sensor data. Upon determining that the target vehicle will pass through the lane based on the predicted trajectory, the host vehicle is operated based on determining a presence or an absence of a lead vehicle. Upon determining that the target vehicle will remain in the lane based on the predicted trajectory, the host vehicle is operated with the target vehicle as the lead vehicle.

Abstract: A device and a method are provided. The device includes a communication module, a memory, and a processor. The processor is configured to acquire position information of a vehicle via the communication module, determine whether high definition (HD) map information corresponding to the position information is acquired, display three-dimensional (3D) navigation information in augmented reality by using the HD map information when the HD map information is acquired, and display two-dimensional (2D) navigation information in augmented reality when the HD map information is not acquired. The 3D navigation information is information in which virtual 3D graphic information for driving guidance is spatially matched to and displayed on an actual object in the real world by using the HD map information, and the 2D navigation information is information in which virtual 2D graphic information for driving guidance is planarly matched to and displayed on an actual object in the real world.

Abstract: A boarding/deboarding point providing system includes a probe vehicle group, a data server, and an on-board unit or a mobile terminal. When vehicle data transmitted from the probe vehicle group are input, the data server extracts a boarding/deboarding point suitable for boarding a vehicle or deboarding a vehicle from the vehicle data, and stores the point while updating the boarding/deboarding point information database. When a request for boarding/deboarding point information is received from the on-board unit or the mobile terminal, the boarding/deboarding point information stored in the boarding/deboarding point information database is searched for a boarding/deboarding point that meets the request conditions, and the search result that includes the boarding/deboarding point is transmitted to the on-board unit or the mobile terminal.

Abstract: A vehicle and control method thereof are intended to promote safe driving of a driver by securing a map of surroundings around the vehicle and displaying a guide line for safe driving when the driver needs to display a guide line for safe driving while the vehicle is driving. The control method of the vehicle includes: checking whether a preset condition for generating a map and displaying a guide line is satisfied while the vehicle is driving; and generating a new map of the surroundings around a place where the vehicle is located and displaying the guide line for safe driving on the map when the preset condition for generating the map and displaying the guide line is satisfied.

Abstract: A method is disclosed for evaluating a classifier used to determine a traffic light signal state in images. The method includes, by a computer vision system of a vehicle, receiving at least one image of a traffic signal device of an imminent intersection. The traffic signal device includes a traffic signal face including one or more traffic signal elements. The method includes classifying, by a traffic light classifier (TLC), a classification state of the traffic signal face using labeled images correlated to the received at least one image. The classification state controls an operation of the vehicle at the intersection. The method includes evaluating a performance of the classifying of the classification state generated by the TLC. The evaluation is a label-free performance evaluation based on unlabeled images. The method includes training the TLC based on the evaluated performance.

Abstract: A method for collecting information required for Bode plot creation of a UAV (Unmanned Aerial Vehicle) autopilot system is provided. The method comprises: creating a Bode plot generation input signal: adding the Bode plot generation input signal to control inputs; collecting data from multiple points within the control system; calculating magnitude and phase at the multiple points using the data collected; recording the magnitude and phase for the multiple points in a datalog; comparing the magnitude and phase for the multiple points to calculate the gain and phase margins for open loop responses in the control system; creating a Bode plot for at least one of the following: i) a closed loop response of the attitude and/or rate loops, ii) an open loop response of the attitude and/or rate loops and iii) a response of the UAV; and outputting the Bode plot.

Abstract: An apparatus for updating map information for a vehicle includes a vehicle information detecting device that detects information of a surrounding vehicle which accompanies a vehicle, when the vehicle travels through an intersection, a line analyzing device that analyzes line information based on information of the surrounding vehicle which accompanies the vehicle, a reliability determining device that determines reliability of the line information, and a controller that extracts a change point on a map based on the reliability and update map information based on the change point.

Abstract: A method, apparatus and computer program product are provided for improving user experiences for autonomous driving. In context of a method, the method determines one or more autonomous transition region parameters for a respective autonomous transition region along a route. The method also, based on the one or more autonomous transition region parameters, determines whether an action is to be performed by a vehicle in accordance with user preference data associated with a user. The method also causes the vehicle to perform the action in accordance with a determination that the action is to be performed by the vehicle.

Abstract: A method and an apparatus are disclosed for providing navigation instructions. The method may include receiving, from a user apparatus, a first location and a destination location; calculating a first route from the first location to the destination location; generating, for a predetermined time period, a first set of maneuvering data corresponding to the first route, the first set of maneuvering data comprising playback cues based on a predicted user apparatus location; transmitting the first set of maneuvering data to the user apparatus; receiving, from the user apparatus, a second location; generating, for a subsequent predetermined time period, a second set of maneuvering data, the second set of maneuvering data comprising playback cues based on a further predicted user apparatus location; calculating an update set of maneuvering data based on the first and second set of maneuvering data; and transmitting the update set of maneuvering data to the user apparatus.