Systems and methods can improve passenger safety for an Autonomous Vehicle (AV) based on the integration of sensor data captured by the AV's interior and exterior sensors. The AV can determine passenger occupancy data corresponding to where each passenger is detected within the AV by the interior sensors. The AV can determine multiple sets of one or more driving actions that the AV can perform at a future time. The AV can generate crash impact data corresponding to where each passenger is detected from one or more simulated collisions between the AV and one or more objected detected by the exterior sensors when the AV performs one or more sets of driving actions from among the multiple sets. The AV can determine ranked sets of driving actions based on the passenger occupancy data and the crash impact data.

Methods and systems for tracking driver behavior across a variety of vehicles are described herein. One or more first performance metrics which indicate performance of a first vehicle when driven by a user may be determined. One or more second performance metrics indicating performance of a second vehicle when driven by the user may be determined. The first vehicle and the second vehicle may be compared to determine a vehicle difference. The performance metrics may be compared. One or more third performance metrics that predict performance of a third vehicle, different from the first vehicle and the second vehicle, when driven by the user may be determined based on the vehicle difference and the comparison. Whether to provide the user access to the third vehicle may be determined based on the one or more third performance metrics.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. A first autonomous vehicle may receive a communication from a second autonomous vehicle travelling on the same road as the first autonomous vehicle, where the communication includes an indication of a maneuver which will be performed by the second autonomous vehicle. The first autonomous vehicle may then analyze the communication to identify a first maneuver for the first autonomous vehicle in response to the second maneuver performed by the second autonomous vehicle. Thus, the first autonomous vehicle may move in accordance with the first maneuver.

A travel instruction information generation device has a vehicle information acquisition unit, a travel instruction information generator, and a correction information generator. The vehicle information acquisition unit acquires vehicle information representing a specific state of a vehicle. The travel instruction information generator generates travel instruction information with which the vehicle performs self-driving by using three-dimensional map information. The correction information generator generates, on the basis of the vehicle information, correction information for correcting the travel instruction information.

Example systems and methods enable an autonomous vehicle to request assistance from a remote operator in certain predetermined situations. One example method includes determining a representation of an environment of an autonomous vehicle based on sensor data of the environment. Based on the representation, the method may also include identifying a situation from a predetermined set of situations for which the autonomous vehicle will request remote assistance. The method may further include sending a request for assistance to a remote assistor, the request including the representation of the environment and the identified situation. The method may additionally include receiving a response from the remote assistor indicating an autonomous operation. The method may also include causing the autonomous vehicle to perform the autonomous operation.

A vehicle is a vehicle on which an ADK is mountable. The vehicle includes: a VP that controls the vehicle in accordance with an instruction from the ADK; and a VCIB that serves as an interface between the ADK and the VP. The VP outputs an accelerator pedal position signal in accordance with an amount of depression of an accelerator pedal by a driver, and outputs an accelerator pedal intervention signal, to the ADK through the VCIB. The accelerator pedal intervention signal indicates that the accelerator pedal is depressed, when the accelerator pedal position signal indicates that the amount of depression is larger than a threshold value, and indicates beyond autonomy acceleration of the vehicle, when an acceleration request in accordance with the amount of depression is higher than a system acceleration request.

An information processing device includes a control unit. The control unit determines a service content fit for an occupant by acquiring first information from a first sensor installed in a vehicle cabin of a vehicle for detecting the occupant and second information from a second sensor for detecting opening and closing of a door of the vehicle, estimating composition information of the occupant based on the first information that is acquired, estimating mood information of the occupant based on the second information that is acquired, and comparing the composition information and the mood information that are estimated with past data for another occupant in which the composition information and the mood information are associated with a service content received at a service facility.

Systems and methods for selecting among different driving modes for autonomous driving of a vehicle may: generate output signals; determine the vehicle proximity information that indicates whether one or more vehicles are within the particular proximity of the vehicle; determine the internal passenger presence information that indicates whether one or more passengers are present in the vehicle; select a first driving mode or a second driving mode based on one or more determinations; and control the vehicle autonomously in accordance with the selection of either the first driving mode or the second driving mode.

Systems and methods for controlling a failover response of an autonomous vehicle are provided. In one example embodiment, a method includes determining, by one or more computing devices on-board an autonomous vehicle, an operational mode of the autonomous vehicle. The autonomous vehicle is configured to operate in at least a first operational mode in which a human driver is present in the autonomous vehicle and a second operational mode in which the human driver is not present in the autonomous vehicle. The method includes detecting a triggering event associated with the autonomous vehicle. The method includes determining actions to be performed by the autonomous vehicle in response to the triggering event based at least in part on the operational mode. The method includes providing one or more control signals to one or more of the systems on-board the autonomous vehicle to perform the one or more actions in response to the triggering event.

A device for determining amass of a vehicle includes vehicle height sensors respectively mounted on left front and rear wheels or respectively mounted on right front and rear wheels to sense a vehicle height of the vehicle, a passenger detecting sensor for sensing the number of passengers boarded the vehicle and boarded locations of the passengers, and a controller that calculates a load based on the vehicle height, calculates a load conversion factor based on each offset set based on a boarded location of each passenger and the number of passengers, and calculates a mass change amount based on the load and the load conversion factor. The device may determine an accurate mass of the vehicle when the vehicle height sensors are not mounted on all four wheels, improve a performance of the vehicle by reflecting the determined mass to vehicle control, and reduce tuning parameters for vehicle control.