The disclosure includes embodiments that provide a switching decision for vehicle computational offloading to a roadside edge server. A method includes causing a sensor set of a connected vehicle to determine a current driving context of the connected vehicle. The method includes comparing the current driving context to a set of historical data to determine a predicted latency for using offboard computing resources of an edge server. The method includes determining that the predicted latency for using the offboard computing resources satisfies a threshold for the predicted latency. The method includes executing a switching decision that includes deciding to use the offboard computing resources of the edge server. The method includes causing the edge server to wirelessly provide digital data generated by the edge server responsive to a calculation. The method includes modifying an operation of the onboard vehicle computer based on the digital data.

Aspects of the disclosure relate to controlling a vehicle using a simplified model of an object. In one example, sensor data including a plurality of data points corresponding to surfaces of the object in the vehicle's environment may be received from one or more sensors of the vehicle. A first model may be determined using a subset of the plurality of data points. A set of secondary data points may be identified from the plurality of data points using a point on the vehicle. The set of secondary data points may be filtered from the subset of the plurality data points to determine a second model, wherein the second model is a simplified version of the first model. The vehicle may be controlled in an autonomous driving mode based on the second model.

A receding horizon state estimator estimates state of a vehicle such as to reduce total communication cost of acquiring external measurements over a prediction horizon, in which state estimation accuracy for a time step is a function of state estimation accuracy for a previous time step. For each time step of the prediction horizon, estimator selects a subset of external sensors with external measurements sufficient to estimate the state with accuracy satisfying the constraint on state estimation accuracy for the corresponding time step while reducing a total communication cost of acquiring the external measurements over the prediction horizon. The estimator requests the external measurements from the subset of external sensors determined for a current time step and estimates the state of the vehicle using the internal and the requested external measurements.

Aspects of the disclosure relate to controlling a vehicle using a simplified model of an object. In one example, sensor data including a plurality of data points corresponding to surfaces of the object in the vehicle's environment may be received from one or more sensors of the vehicle. A first model may be determined using a subset of the plurality of data points. A set of secondary data points may be identified from the plurality of data points using a point on the vehicle. The set of secondary data points may be filtered from the subset of the plurality data points to determine a second model, wherein the second model is a simplified version of the first model. The vehicle may be controlled in an autonomous driving mode based on the second model.

A plurality of candidate estimated paths (301) for a vehicle (100) to travel to an intermediate destination (300) while avoiding a moving object present by estimation time is generated depending on cost information of lanes (200, 201), and an estimated path selected from the plurality of candidate estimated paths (301) is set as a path of the vehicle (100) for each estimation time.

The disclosure relates to a control apparatus for enabling functions, comprising an integrated circuit. The control apparatus has a function register unit for storing at least one entry relating to an enabled state of a respective circuit function and/or of a respective circuit area of the integrated circuit. The integrated circuit is configured to enable the respective circuit function and/or the respective circuit area for use in accordance with the at least one entry in the function register unit. The control apparatus has a function control unit configured to respond to a predetermined actuation signal by changing the at least one entry in the function register unit, wherein the change is made only if a predetermined authenticity check based on a cryptographic method confirms a source of the actuation signal is authorized, so that the function control unit is actuatable only by a trusted source.

Disclosed herein are methods and systems for motion planning in an autonomous vehicle (AV) that separate path planning and velocity planning and may use reference lines in combination with motion planners to determine paths. The method may include reference lines to project planning data into a S-L coordinate system. A motion planner algorithm uses the reference lines and previous path planning history to generate a path in the S-L coordinate system. A velocity is determined for the path. An AV controller is updated with the path and the velocity. Motion planning computations use a dynamic vehicle look-up table to determine possible vehicle motions based on an initial state and control input.

To provide an electronic control device generating low heat due to a simplified configuration and a reduced verification arithmetic load without multiplexing of sensors and calculations.

A sensor fusion processing unit 4 that integrates a plurality of pieces of sensor information having been input from a plurality of first sensors 11 and second sensors 12, a behavior prediction processing unit 5 that obtains a surrounding object prediction map 8 in which a future behavior of a target object is predicted based on an own vehicle surrounding map 9 integrated by the sensor fusion processing unit 4, and a first comparison unit 102 that compares the surrounding object prediction map 8 predicted by the behavior prediction processing unit 5 with output information of each of the first sensors 11 and the second sensors 12 of the sensor fusion processing unit 4 at a predicted time are included.

A motion planning system includes: a processor; and memory to store instructions that when executed by the processor, cause the processor to: identify a reference path between a departure point and a destination point in an environment including one or more obstacles; generate decomposition segments of a space surrounding the reference path, the decomposition segments including a first free-space segment and a second free-space segment that are devoid of the obstacles; generating a first path segment relative to the reference path for traversing the first free-space segment, and a second path segment relative to the reference path for traversing the second free-space segment; and connecting the first and second path segments to each other to generate a navigational path to traverse the environment.

A drive control system is provided, which is mounted on a vehicle configured to travel by operation of a driver. The drive control system includes an actuator configured to output a driving force for the vehicle to travel, an output sensor configured to detect a driving force requested by the operation of the driver, and a control device configured to control operation of the actuator based on the requested driving force detected by the output sensor. The control device sets a target output value by adding a given delay time to a requested output value set corresponding to the requested driving force, and controls the actuator so as to output the target output value based on a response characteristic of the actuator.