According to various embodiments, systems, methods, and media for evaluating an open space planner in an autonomous vehicle are disclosed. In one embodiment, an exemplary method includes receiving, at a profiling application, a record file recorded by the ADV while driving in an open space using the open space planner, and a configuration file specifying parameters of the ADV; extracting planning messages and prediction messages from the record file, each extracted message being associated with the open space planner. The method further includes generating features from the planning message and the prediction messages in view of the specified parameters of the ADV; and calculating statistical metrics from the features. The statistical metrics are then provided to an automatic tuning framework for tuning the open space planner.

A vehicle may include a primary system for generating data to control the vehicle and a secondary system that validates the data and/or other data to avoid collisions. For example, the primary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and generate a trajectory for the vehicle. The secondary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and determine a likelihood of a collision of the vehicle with the object. A simulation system may generate simulation scenarios that test aspects of the primary system and the secondary system. Simulation scenarios may include simulated vehicle control data that causes the primary system to generate a driving trajectory and simulated object data that causes the secondary system to determine a collision.

Methods and systems of enabling a transportation mode on a telematics device coupled to a vehicle are provided. One method includes detecting a first event or receiving a command for enabling a transportation mode, running a transportation mode power-saving scheme in response to receiving the first event or the command, and exiting the transportation mode power-saving scheme in response to detecting a second event.

A method for ascertaining a highly accurate piece of yaw rate information for controlling a vehicle is provided. The method includes ascertaining a first yaw rate estimated value of the vehicle based on a fusion of sensor data of an inertial sensor, a GNSS sensor, a wheel velocity sensor and/or a steering angle sensor; ascertaining a second yaw rate estimated value of the vehicle by an evaluation of sensor data of a camera assigned to the vehicle, which optically detects the surroundings of the vehicle; carrying out a correction of the first yaw rate estimated value with the aid of the second yaw rate estimated value to ascertain a corrected yaw rate estimated value; and outputting the corrected yaw rate estimated value as a piece of yaw rate information to generate a control signal for controlling the vehicle.

A vehicle control system uses reliability of an input signal of an autonomous vehicle to safely travel through an intersection or a crossroad. The system includes a first calculating unit that calculates reliability for behavior information of a front vehicle and a second calculating unit calculates reliability for state information of a traffic light in the crossroad or the intersection based on a surrounding vehicle. A third calculating unit calculates reliability for brake light information of the front vehicle and a fourth calculating unit calculates reliability for flow information of the surrounding vehicle passing the crossroad or the intersection. A determining unit generates a vehicle control signal according to the calculated reliability.

System, methods, and other embodiments described herein relate to improving automated driving by testing for inputs during driving. In one embodiment, a method includes testing an input from a driver in a manual driving mode of a vehicle. The method also includes adapting a fixed time interval on a condition that a test result of the input satisfies criteria used to validate driver inputs. The method also includes monitoring, via an input system of the vehicle, for driver feedback according to the fixed time interval in an automated driving mode.

A system for recording event data of an autonomous vehicle is disclosed. The present disclosure suggests an EDR system operation scheme suitable for properly investigating the cause of a vehicle accident. Subsystems of an autonomous driving control system may determine whether an event satisfying a preconfigured condition has occurred, and send to an EDR system a trigger signal to trigger recording of data elements related to the event when the occurrence of the event is detected. The EDR system may record data elements that are useful to reconstruct a map of an external environment surrounding an autonomous vehicle at the time of the occurrence of the event or to reconstruct an internal environment of the vehicle.

In one embodiment, an exemplary method includes the operations of receiving, at a profiling application, a record file recorded by the ADV for a driving scenario in an area, and a high definition map matching the area; extracting planning messages and perception messages from the record file; and aligning the planning message and the perception messages based on their timestamps. The method further includes calculating an individual performance score for each planning cycle of the ADV for the driving scenario based on the planning messages; calculating a weight for each planning cycle based on the perception messages and the high definition map; and then calculating a weighted score for the driving scenario based on individual performance scores and their corresponding weights.

Provided are systems, methods and computer program code for transmitting vehicle data to remote monitoring systems using a low bandwidth protocol.

Provided are systems, methods and computer program code for transmitting vehicle data to remote monitoring systems using a low bandwidth protocol.