A method for cleaning up vehicle driving data includes receiving vehicle driving data of a vehicle within a predetermined time period, the vehicle driving data comprising vehicle mileage data and vehicle status data; determining a first mileage of the vehicle within the predetermined time period based on the vehicle mileage data; determining a second mileage of the vehicle within the predetermined time period based on the vehicle status data; and judging whether the first mileage is abnormal data based on the second mileage.

A method for cleaning up vehicle driving data includes receiving vehicle driving data of a vehicle within a predetermined time period, the vehicle driving data comprising vehicle mileage data and vehicle status data; determining a first mileage of the vehicle within the predetermined time period based on the vehicle mileage data; determining a second mileage of the vehicle within the predetermined time period based on the vehicle status data; and judging whether the first mileage is abnormal data based on the second mileage.

A method for controlling the actuation of an actuatable restraint to help protect a vehicle occupant in response to a rollover event is implemented in a controller of a vehicle safety system that includes the actuatable restraint. To implement the method, the controller is configured to execute a roll discrimination metric that discriminates the occurrence of a ramp rollover event or an embankment rollover event in response to a vehicle roll rate (R_RATE) having a magnitude that exceeds a predetermined threshold roll rate (R_RATE). The controller is also configured to execute a switching metric that is operative to reduce the predetermined threshold roll rate (R_RATE) in response to a vehicle pitch rate (P_RATE) having a magnitude that exceeds a predetermined threshold pitch rate (P_RATE).

Systems providing a comparison of results of simulations of operation of a simulated autonomous vehicle may include a processor to: perform a first simulation of operation of a simulated autonomous vehicle based on first autonomous vehicle control code, receive second autonomous vehicle control code that includes a second version of software code associated with controlling operations of the simulated autonomous vehicle, the second version including a modification of a first version of software code associated with controlling operations of the simulated autonomous vehicle, perform a second simulation of operation of the simulated autonomous vehicle based on the second autonomous vehicle control code, and display an indication that second values of one or more metrics that resulted from the second simulation are different from one or more first values of the one or more metrics that resulted from the first simulation. Methods, computer program products, and autonomous vehicles are also disclosed.

Systems providing a comparison of results of simulations of operation of a simulated autonomous vehicle may include a processor to: perform a first simulation of operation of a simulated autonomous vehicle based on first autonomous vehicle control code, receive second autonomous vehicle control code that includes a second version of software code associated with controlling operations of the simulated autonomous vehicle, the second version including a modification of a first version of software code associated with controlling operations of the simulated autonomous vehicle, perform a second simulation of operation of the simulated autonomous vehicle based on the second autonomous vehicle control code, and display an indication that second values of one or more metrics that resulted from the second simulation are different from one or more first values of the one or more metrics that resulted from the first simulation. Methods, computer program products, and autonomous vehicles are also disclosed.

Operation data from one or more vehicle subsystems are input to a vehicle dynamics model. Predicted operation data of the one or more vehicle subsystems are output from the vehicle dynamics model. The operation data and the predicted operation data are input to an optimization program that is programmed to output control directives for the one or more vehicle subsystems. One or more vehicle subsystems are operated according to the output control directives.

Operation data from one or more vehicle subsystems are input to a vehicle dynamics model. Predicted operation data of the one or more vehicle subsystems are output from the vehicle dynamics model. The operation data and the predicted operation data are input to an optimization program that is programmed to output control directives for the one or more vehicle subsystems. One or more vehicle subsystems are operated according to the output control directives.

In an abnormality detection method for detecting an abnormality in vehicle behaviors based on an abnormality degree indicating a degree of difference between first driving information representing a vehicle behavior undergoing abnormality detection and second driving information obtained when no abnormality is found in a travel environment, an abnormality threshold is estimated using an abnormality degree distribution generated from a set of preaccumulated abnormality degrees. The abnormality threshold is an abnormality degree allowing a probability of erroneous determination as to presence or absence of an abnormality to be a predefined probability. Further, in the abnormality detection method, it is detected whether an abnormality is found in the vehicle behavior by comparing the abnormality degree for the first driving information and the estimated abnormality threshold.

A method for calculating running resistance of a vehicle includes: calculating, by a controller, an integrated value obtained by integrating a torque of a driving source of the vehicle before the vehicle reaches a reference speed after the vehicle starts; and calculating, by the controller, the running resistance of the vehicle including rolling resistance based on the integrated value of the torque of the driving source.

Techniques to provide guidance to a vehicle operating in an environment are discussed herein. For example, such techniques may include sending a request for assistance, receiving a reference trajectory, and causing the vehicle to determine a trajectory based on the reference trajectory. Data such as sensor data and vehicle state data may be sent from the vehicle to a remote computing device. The computing device outputs a user interface using the data and determines the reference trajectory based on receiving an input in the user interface. The techniques can send an indication of the reference trajectory to the vehicle for use in planning a trajectory for the vehicle. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory.