An autonomous driving computing system may include an on-board computing system that is configured to perform first operations that include obtaining sensor data relating to an autonomous vehicle (AV). The first operations may include sending the obtained sensor data to an off-board cloud computing system. The autonomous driving computing system may include the off-board cloud computing system, which may be configured to perform second operations that include receiving the sensor data and performing computations relating to the driving operation of the AV based on the obtained sensor data. The second operations may include determining a control signal corresponding to a driving operation and sending the control signal to the on-board computing system. The first operations may involve the on-board computing system receiving, from the off-board cloud computing system, the control signal corresponding to the driving operation of the AV and performing the driving operation by implementing the control signal.

An autonomous driving validation system may include a primary advanced autonomy system located on board an autonomous vehicle (AV) that includes sensors, computing subsystems, and a drive-by-wire system. The primary advanced autonomy system may be configured to process first computations relating to a driving operation of the AV. The autonomous driving validation system may also include an off-board autonomous cloud computing system that includes cloud computing subsystems. The off-board autonomous cloud computing system may be configured to process second computations that are similar to the first computations processed by the primary advanced autonomy system. The autonomous driving validation system may include processors and non-transitory computer-readable storage media configured to store instructions that, in response to being executed, cause a system to perform operations relating to whether a likelihood of a problem arising during driving operation of the AV is above a threshold and generating a notification message regarding the problem.

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.

The subject disclosure relates to techniques for positioning an autonomous vehicle for sensor calibration. A process of the disclosed technology can include steps for positioning an autonomous vehicle along a first axis on a platform in a predetermined environment using guide rails, positioning the autonomous vehicle along a second axis on the platform using one or more elevated platform features, inserting one or more lifting alignment pins of a lifting mechanism into one or more sockets located on an underbody of the autonomous vehicle, and positioning the autonomous vehicle along a third axis using the lifting mechanism. Systems and machine-readable media are also provided.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for generating or updating usage-based insurance policies for autonomous or semi-autonomous vehicles may be provided. A request to generate an insurance quote may be received via wireless communication, and with the customer's permission, risk levels associated with intended usage by the customer of an autonomous or semi-autonomous vehicle may be determined. An insurance policy may be adjusted based upon the risk levels and the intended vehicle usage. The insurance policy may then be presented on the customer's mobile device for review and approval. In some aspects, the vehicle may be rented, and the intended vehicle usage is measured in distance or duration of vehicle operation. Insurance discounts may be provided to risk averse vehicle owners based upon low risk levels.

A platooning control apparatus may include: a navigation unit configured to guide an ego vehicle to a destination set by a driver; a driving module configured to drive the ego vehicle; and a control unit configured to primarily select platooning groups based on the destination set in the navigation unit, analyze platooning information of the primarily selected platooning groups, finally decide any one of the primarily selected platooning groups, and then control the driving module to join the finally decided platooning group.

A platooning control apparatus may include: a navigation unit configured to guide an ego vehicle to a destination set by a driver; a driving module configured to drive the ego vehicle; and a control unit configured to primarily select platooning groups based on the destination set in the navigation unit, analyze platooning information of the primarily selected platooning groups, finally decide any one of the primarily selected platooning groups, and then control the driving module to join the finally decided platooning group.

In one aspect, a computer system for vehicle configuration verification, and/or detecting unauthorized vehicle modification may be provided. In some exemplary embodiments, the computer system may include a processor and a non-transitory, tangible, computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations including: (1) receiving a vehicle image, including a vehicle identifier and at least one software module; (2) calculating a configuration hash value of the at least one software module; generating a first data block including the configuration hash value, a first index value, the vehicle identifier, and a digital signature; (3) storing the first data block in a memory; and/or (4) transmitting the first data block to any number of network participants using a distributed network to facilitate vehicle software configuration verification.

When a traveling state of a vehicle is switched, the vehicle requests delivery of an update program from an OTA server. For example, when the vehicle travels with an occupant on board, the vehicle requests delivery of an update program for manned vehicle traveling from the OTA server. When the vehicle travels with an occupant not on board, the vehicle requests delivery of an update program for unmanned vehicle traveling from the OTA server. When the OTA server receives the request for delivery of the update program for manned vehicle traveling/unmanned vehicle traveling, the OTA server delivers the requested update program for manned vehicle traveling/unmanned vehicle traveling to the vehicle. The vehicle updates a diagnosis program using the received update program for manned vehicle traveling/unmanned vehicle traveling.

Embodiments include methods performed by a processor of a vehicle control unit for managing a driving condition anomaly. In some embodiments, the vehicle may receive a first driving condition based on data from a first vehicle sensor, receive a second driving condition based on data from another data source, determine a driving condition anomaly based on the first driving condition and the second driving condition, send a request for information to a driving condition database remote from the vehicle, receive the requested information from the driving condition database, and resolve the driving condition anomaly based on the requested information from the driving condition database.