A method, a computer program with instructions, and an apparatus for configuring a control system for an at least partially autonomous transportation vehicle. Data relating to the driving situation are captured, selection criteria are then determined from the available data, two or more AI modules are selected from a library of AI modules during driving based on selection criteria, and combined execution of the selected two or more AI modules by the control system is initiated.

A precipitation index estimation apparatus includes a data collection unit and an estimation processing unit. The data collection unit is configured to collect rainfall amount data detected by a rainfall amount sensor in one or more vehicles positioned on a predetermined road link within a predetermined period. The estimation processing unit is configured to estimate a precipitation index indicating an intensity of precipitation on the predetermined road link within the predetermined period, based on the collected rainfall amount data.

A stopping position control device according to an embodiment includes a sitting position specifying unit configured to specify a sitting position of a user who gets off a vehicle next, the vehicle being subjected to automatic driving control, and a stopping position determination unit configured to determine a stopping position of the vehicle, at which the user gets off the vehicle, corresponding to the sitting position of the user.

A vehicle-mounted equipment control device includes a controller configured to cause equipment of any of a headlight, a wiper, and an air-conditioning device to continue a visual securing operation for securing visibility of a driver of a vehicle even after driving control of the vehicle is switched from automated driving control to manual driving control regardless of an operation mode of the equipment specified by an operation switch for setting an operation of the equipment when an operation mode executed by the equipment immediately before driving control of the vehicle is switched from automated driving control to manual driving control is an operation mode corresponding to the visual securing operation.

A server includes a processor, programmed to receive a vehicle location from a vehicle, receive a weather condition of the vehicle location from a cloud server, responsive to receiving a calendar of a user including an event, calculate a departure time based on the vehicle location and a location of the event, responsive to receiving a desired cabin temperature of the user from a mobile device, calculate a minimum time for the vehicle to reach the desired cabin temperature based on the weather condition, calculate a vehicle start time using the departure time and the minimum time, and send an instruction to the vehicle to start at the vehicle start time.

Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

A vehicle includes a control system, a sensing system that senses an environment of the vehicle, and a propulsion system, a braking system, and a steering system that are operated by the control system to navigate the vehicle according to the sensing system and without direct human control. The propulsion system and the braking system are operated by the control system to cooperatively decelerate the vehicle. The braking system includes an inboard friction brake that is associated with one or more wheels of the vehicle and does not form unsprung mass of the vehicle.

A method for trajectory planning of a vehicle includes storing a desired driving path of the vehicle. The method then includes observing external interference factors (2) on the vehicle. The method proceeds by using the driving path and the interference factors (2) to calculate tracking errors (3) and secondary conditions (4). The method then includes optimizing a trajectory (5) in such a way that the tracking errors (3) are reduced within the secondary conditions (4). A corresponding device, a corresponding computer program, and a corresponding storage medium also are provided.

Aspects of the disclosure provide for enabling autonomous vehicles to pull over into driveways when picking up or dropping off passengers or goods. For instance, a request for a trip identifying a first location and a second location may be received. The first location may be a location of a client computing device, and the second location may be a starting location or a destination for the trip. A user preference for the trip indicating that a pickup for the trip be in a driveway may be identified. That the first location corresponds with the second location may be identified. Based on the determination that the first location corresponds with the second location, dispatch instructions may be to an autonomous vehicle. The dispatch instructions may identify a polygon for a driveway at the second location in order to cause the autonomous vehicle to pull over into the driveway.

A plurality of thermal areas (11a, 11b, 11c, and 11d) of different thermal environments are formed in a room (11). When it is determined that a person (13) riding on a movable object (20) is feeling uncomfortable in the thermal area (11d), the movable object (20) is remotely operated to move toward the thermal area (11a) where the person (13) feels comfortable.