A computer-implemented method of evaluating the performance of a full or partial autonomous vehicle (AV) stack in simulation, the method comprising: applying an optimization algorithm to a numerical performance function defined over a scenario space, wherein the numerical performance function quantifies the extent of success or failure of the AV stack as a numerical score, and the optimization algorithm searches the scenario space for a driving scenario in which the extent of failure of the AV stack is substantially maximized, wherein the optimization algorithm evaluates multiple driving scenarios in the search space over multiple iterations, by running a simulation of each driving scenario in a simulator, in order to provide perception inputs to the AV stack, and thereby generate at least one simulated agent trace and a simulated ego trace reflecting autonomous decisions taken in the AV stack in response to the simulated perception inputs, wherein later iterations of the multiple iterations are guided by the results of previous iterations of the multiple iterations, with the objective of finding the driving scenario for which the extent of failure of the AV stack is maximized.

A control unit is presented for controlling a driving unit arranged for adjustment of one or more first air guiding flaps of a motorised vehicle between a first outer position and a second outer position. The control unit comprises a communication module for communicating with a vehicle control network for receiving first adjustment instructions for adjusting the first flap, a power supply module comprising an input power terminal for receiving power from a vehicle power network and a first output power terminal for supplying a first current to the driving unit. The control unit further comprises a current sensor module for sensing variations in the first supply current and a control module arranged to control the first supply current in accordance with the adjustment instructions and the sensed variations. By separating the control module from the driving unit, functionality of the control module may be shared over multiple driving units.

Example aspects of the present disclosure are directed to improved systems and methods for testing autonomous vehicle operation through the use of mobile test devices that are controlled at least in part in response to predictive motion planning associated with autonomous vehicles. More particularly, the motion of a mobile test device can be controlled based on the motion plan of an autonomous vehicle to cause desired interactions between the mobile test device and the autonomous vehicle. Motion planning data associated with the autonomous vehicle can be obtained by an autonomous vehicle (AV) test system prior to the autonomous vehicle implementing or completely implementing a motion plan. In this manner, the AV test system can proactively control the mobile test device based on predictive motion planning data to facilitate interactions between the mobile test device and the autonomous vehicle that may not otherwise be achievable.

A system is provided generating a context-dependent experience for a vehicle driver, e.g., to relax or enhance the driver's mental state. A system controller is configured to receive driving context data regarding a driving situation from various driving context data sources. The driving context data may include vehicle operation data, e.g., generated by vehicle-based sensors, and environmental data regarding an environment external to the vehicle, e.g., received wirelessly from a remote server. The system controller may identify content triggering events based on (a) the received driver context data and (b) a set of content triggering rules. For each content triggering event, the system controller may select one or more human-perceivable contents elements (e.g., audio clips, seat massage settings, or air conditioner settings), and control one or more content output devices (e.g., speakers, seat massage system, or vehicle HVAC system) to output the selected content element(s) to the driver.

A system and method of augmenting a delivery route. The method comprises receiving first location information from a first position device and receiving second location information from a second position device. The method further comprises storing the first and second location information in a memory structure and determining, based on at least one of the first and second information, a time and a location for each of a plurality of stops. The method also comprises reconciling the determined time and location of each of the plurality of stops with a stored route comprising a plurality of stored stops, the stored stops having a stored location and a stored time associated therewith and estimating a plurality of transition times between pairs of the plurality of stops. The method further also comprises constructing an updated timeline based on the plurality of stored stops, the plurality of determined stops, and the plurality of transition times and updating the delivery route based on the constructed timeline.

Systems and methods are provided for generating data for sensor system validation. A representative vehicle is equipped with a set of sensors positioned to provide a collective field of view defining a set of sensor locations as a set of master data and encompassing a field of view of a sensor positioned at any of the set of sensor locations. The set of sensor locations includes a sensor location at which no sensor of the set of sensors is placed. The representative vehicle is driven for a distance required for validation of a sensor system to provide master data representing the entire distance required for validation.

A method and an apparatus for controlling an autonomous driving vehicle are provided. The method includes: receiving environment information sent by an autonomous driving vehicle, the environment information including vehicle exterior environment information; determining whether the autonomous driving vehicle is in an abnormal operation status, based on the vehicle exterior environment information and operation information of an operation executed by the autonomous driving vehicle; and sending a braking control instruction and a data acquisition instruction to the autonomous driving vehicle, in response to determining that the autonomous driving vehicle is in the abnormal operation status, the braking control instruction being used for controlling braking of the autonomous driving vehicle, and the data acquisition instruction being used for acquiring data of a driving recorder in the autonomous driving vehicle.

The present application relates to providing alert notifications of high-risk driving areas in a connected vehicle by calculating a first navigational route between a host vehicle location and a destination, transmitting the first navigational route via a wireless network, receiving via a wireless network an indication of a high-risk area in response to the first navigational route, generating a second navigational route in response to the high-risk area, presenting the second navigational route to a vehicle occupant via a user interface and prompting user action.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

A control unit is presented for controlling a driving unit arranged for adjustment of one or more first air guiding flaps of a motorised vehicle between a first outer position and a second outer position. The control unit comprises a communication module for communicating with a vehicle control network for receiving first adjustment instructions for adjusting the first flap, a power supply module comprising an input power terminal for receiving power from a vehicle power network and a first output power terminal for supplying a first current to the driving unit. The control unit further comprises a current sensor module for sensing variations in the first supply current and a control module arranged to control the first supply current in accordance with the adjustment instructions and the sensed variations. By separating the control module from the driving unit, functionality of the control module may be shared over multiple driving units.