The disclosure describes various embodiments for detecting an unexpected control state of an autonomous driving system. According to an embodiment, an exemplary method of detecting an unexpected control state of an autonomous driving system include the operations of generating environmental data of a vehicle; determining, by the autonomous driving system, a first control state based on the environmental data of the vehicle; determining, by a reference model, a second control state based on the environmental data, wherein the reference model defines at least one scenario each corresponding to a plurality of expected control states and a state switching condition, and in each of the expected control states corresponding to the scenario, an action of the vehicle in the scenario obeys a traffic rule; and determining the unexpected control state of the autonomous driving system by comparing the first control state with the second control state.

Systems and methods for driving trajectory planning of an automated vehicle. The system includes an electronic processor configured to determine a lane segment graph indicating allowable transitions between a plurality of lane segments. The electronic processor is also configured to determine a current type of traffic flow situation. The electronic processor is further configured to determine weighting factors for each of the allowable transitions based on aggregate observations of previous real-world traffic flow transitions for the current type of traffic flow situation. Each of the weighting factors indicate a likelihood of transition for a respective one of the allowable transitions. The electronic processor is also configured to determine a weighted lane segment graph based at least in part on the weighting factors. The electronic processor is further configured to determine a driving trajectory of the automated vehicle based at least in part on the weighted lane segment graph.

A driving system for a motor vehicle includes a first driving function for automated driving with automated longitudinal and transverse guidance and a second driving function for automated driving with at least automated longitudinal guidance, or with at least automated transverse guidance. The second driving function has a lower degree of automation than the first driving function. The first driving function is available in a tolerance range. Starting from a driving state with an active second driving function and a value of the driving parameter outside the tolerance range, the driving system changes, when the second driving function is active, the value of the driving parameter in the direction of the tolerance range via automated longitudinal guidance or automated transverse guidance. The driving system then determines that the driving parameter satisfies a criterion with respect to the tolerance range.

A current lane of vehicle operation is determined to be branched at a location into a through lane and a deceleration lane based on first sensor data indicating an increased width of the current lane exceeds a predetermined width at the location. Then the vehicle is determined to be operating in one of (a) the deceleration lane, or (b) the through lane, based on second sensor data. Then one of (a) an assist feature of the vehicle is activated to a disabled state based on determining the vehicle is in the deceleration lane, or (b) the assist feature is maintained in an enabled state based on determining the vehicle is in the through lane.

A sensor calibration system for a vehicle includes one or more processors. The system also includes a memory communicably coupled to the one or more processors and storing a sensor calibration module including instructions that when executed by the one or more processors cause the one or more processors to, for an environment sensor of the vehicle, determine if the sensor can detect at least a predetermined number of viable reference features in an environment of the vehicle. The module also includes processor-executable instructions to, if the sensor cannot not detect at least a predetermined number of viable reference features, determine at least one suggested positional arrangement of viable reference features with respect to a current position the sensor. The module also includes processor-executable instructions to generate instructions to arrange viable reference features in the at least one suggested positional arrangement.

A method of maintaining vehicle formation includes receiving a desired cross track offset distance and a desired along track offset distance between a lead vehicle and a follower vehicle; receiving a current position, a current yaw rate, and a current speed of the lead vehicle; determining a current turn radius of the lead vehicle based on the current yaw rate and the current speed of the lead vehicle; determining a projected turn radius of the follower vehicle based on the current turn radius of the lead vehicle, the desired cross track offset distance, and the desired along track offset distance; determining a commanded curvature and a next speed of the follower vehicle based on a current position of the follower vehicle and the projected turn radius of the follower vehicle; and outputting the next speed and the commanded curvature to a control system of the follower vehicle.

A driving support apparatus according to the invention estimates the position of a moving body by controlling a position estimation unit when the tracking-target moving body leaves a first area or a second area to enter a blind spot area and detects the position of the moving body by controlling a position detection unit when the moving body leaves the blind spot area to enter the first area or the second area. In this manner, the trajectory of the tracking-target moving body is calculated so that the trajectory of the moving body detected in the first area or the second area and the trajectory of the moving body estimated in the blind spot area are continuous to each other and driving support is executed based on the calculated trajectory of the tracking-target moving body.

A method or system for controlling safety of both an ego vehicle and social objects in an environment of the ego vehicle, comprising: receiving data representative of at least one social object and determining a current state of the ego vehicle based on sensor data; predicting an ego safety value corresponding to the ego vehicle, for each possible behavior action in a set of possible behavior actions, based on the current state; predicting a social safety value corresponding to the at least one social object in the environment of the ego vehicle, based on the current state, for each possible behavior action; and selecting a next behavior action for the ego vehicle, based on the ego safety values, the social safety values, and one or more target objectives for the ego vehicle.

A method for controlling a driving dynamics function of a working machine with at least two vehicle axles. A current actual wheel rotational speed of at least one wheel is detected and sent to a control unit for comparison with an acceptable wheel rotational speed of the same wheel and wheel slip is calculated from that comparison. The control unit emits a control signal to lock at least one differential gear system if the wheel slip has an unacceptable value. For the differential gear system (4, 5, 6, 7, 8) concerned, an unlocking control signal is periodically emitted and the wheel rotational speeds are compared afresh. A control signal to lock the differential gear system concerned is emitted again if the value of the wheel slip is still unacceptable, and a trajectory is detected with reference to detection elements, along which the value of the wheel slip of the at least one wheel has been unacceptable.

Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.