Simulating realistic movement of an object, such as a vehicle or pedestrian, that accounts for unusual behavior may comprise generating an agent behavior model based at least in part on output of a perception component of an autonomous vehicle and determining a difference between the output and log data that includes indications of an actual maneuver of location of an object. Simulating movement of an object may comprise determining predicted motion of the object using the perception component and modifying the predicted motion based at least in part on the agent behavior model.

An example operation includes one or more of determining, by a transport, that an issue will soon occur, determining, by the transport, a time the issue will occur, and displaying, by the transport, the time the issue will occur. The issue is based on sensor data approaching a threshold within a period of time that is faster than an average period of time.

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.

In one embodiment, a computer-implemented method for calibrating autonomous driving vehicles at a cloud-based server includes receiving, at the cloud-based server, one or more vehicle calibration requests from at least one user, each vehicle calibration request including calibration data for one or more vehicles and processing in parallel, by the cloud-based server, the one or more vehicle calibration requests for the at least one user to generate a calibration result for each vehicle. The method further includes sending, by the cloud-based server, the calibration result for each vehicle to the at least one user.

An apparatus and method performed by a perception comparing system of a vehicle for perception performance evaluation of an ADAS or ADS. The perception comparing system establishes communication with a secondary vehicle determined and/or estimated to be positioned within a potential range of surrounding detecting sensors on-board the vehicle. The system derives perception data from a perception system of the ADAS or ADS. The system receives secondary perception data from a secondary perception system of a secondary ADAS or ADS of the secondary vehicle and determines a discrepancy output based on comparison of at least a portion of the both of perception data and the secondary perception data. The system communicates acknowledgement data when at least a portion of the discrepancy output fulfils discrepancy exceedance criteria and/or when the vehicle is perceivable in the secondary perception data but the secondary vehicle not is locatable in the perception data.

Simulating realistic movement of an object, such as a vehicle or pedestrian, that accounts for unusual behavior may comprise generating an agent behavior model based at least in part on output of a perception component of an autonomous vehicle and determining a difference between the output and log data that includes indications of an actual maneuver of location of an object. Simulating movement of an object may comprise determining predicted motion of the object using the perception component and modifying the predicted motion based at least in part on the agent behavior model.

An apparatus can have a processor configured to determine a length of time that a vehicle is in a region and to determine whether the vehicle needs to be configured for the region based on the determined length of time.

Systems and methods for determining the location of a vehicle are disclosed. In one embodiment, a method for localizing a vehicle includes driving over a first road segment, identifying by a first localization system a set of candidate road segments, obtaining vertical motion data while driving over the first road segment, comparing the obtained vertical motion data to reference vertical motion data associated with at least one candidate road segment, and identifying, based on the comparison, a location of the vehicle. The use of such localization methods and systems in coordination with various advanced vehicle systems such as, for example, active suspension systems or autonomous driving features, is contemplated.

An electronic control device comprises an electronically rewritable nonvolatile memory which has first storage area and second storage area. The first storage area stores a control program in which control data is embedded, and the second storage area stores a plurality of control data usable for the control program and a rewrite program for rewriting the control data of the control program to one piece of control data selected from the plurality of control data.

The subject disclosure relates to ways to resolve autonomous vehicle (AV) routes based on verbal descriptions of landmark features. In some aspects, a process of the disclosed technology includes steps for receiving speech instructions, wherein the speech instructions indicate an autonomous vehicle (AV) destination, analyzing the speech instructions to identify one or more landmarks associated with the AV destination, and determining location information corresponding with the one or more landmarks. In some aspects, the process further includes calculating a route based on the location information corresponding with the one or more landmarks. Systems and machine-readable media are also provided.