An information processing apparatus includes a processor. The processor is configured to estimate whether a fellow passenger is included in occupants of a vehicle, when the fellow passenger is included in the occupants, acquire information relating to a driver of the vehicle and information relating to the fellow passenger, estimate a relationship between the driver and the fellow passenger based on the acquired information, and select a control relating to traveling of the vehicle according to the relationship.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for communicating information regarding a smart infrastructure component to an autonomous or semi-autonomous vehicle may be provided. Sensors may be communicatively connected to an infrastructure communication device, and the infrastructure communication device may generate a message based upon information from the sensors and/or regarding the infrastructure component. The message may be transmitted, and, with the vehicle operator's permission, all or part of the determined message may be presented to the operator of the autonomous or semi-autonomous vehicle. The message may include weather, traffic, ice, or road condition or construction information and facilitate safer vehicle travel. Insurance discounts for customers may be generated based upon their vehicle being equipped with this safety and vehicle damage prevention functionality.

An automated driving system includes a determiner, a driving switch controller, and a notification controller. The determiner determines each of a plurality of determination items that is a condition for switching from an automated driving to a manual driving. The driving switch controller switches from the automated driving to the manual driving when all of the plurality of determination items are determined as positive. The notification controller notifies a driver of notification information for urging a reaction of the driver when at least one of the plurality of determination items is determined as negative. The determiner determines the at least one or all of the plurality of determination items before a vehicle passes through a switch determination point. The determiner determines the at least one or all of the plurality of determination items when or after the vehicle passes through the switch determination point.

A system includes an acquisition unit that acquires an operation amount or a duration count, and a switching unit that switches a driving state. The switching unit switches the driving state to the cooperative driving state when the operation amount is equal to or greater than an intervention threshold and less than a start threshold or the duration count is equal to or greater than a first threshold and less than a second threshold during the autonomous driving state, switches the driving state to the autonomous driving state when the operation amount is less than the intervention threshold or the duration count is less than the first threshold during the cooperative driving state, and switches the driving state to the manual driving state when the operation amount is equal to or greater than the start threshold or the duration count is equal to or greater than the second threshold.

Systems and methods are provided for controlling operation of a vehicle. An example system for controlling operation of a vehicle includes one or more data collection components and one or more processors. The one or more data collection components are configured to collect data representative of a physical configuration of an interior vehicle component. The one or more processors are configured to access the collected data, determine, by processing the collected data, the physical configuration of the interior vehicle component, select a manner of operation based upon the determined physical configuration of the interior vehicle component, and cause the vehicle to operate according to the manner of operation.

A system for detecting a vehicular crash (i) receives data from the at least one sensor; (ii) determines that a potential vehicular crash is imminent based upon the received data; and (iii) performs at least one action to reduce a severity of the potential vehicular crash prior to impact. As a result, at least one of the potential injuries to passengers and the potential damage to a vehicle involved in the potential vehicular crash is reduced.

A system for analyzing the environment of a vehicle (i) receives a plurality of data from at least one sensor associated with a vehicle, such that the plurality of data includes at least one environmental condition; (ii) analyzes the plurality of data to determine the at least one environmental condition; (iii) determines at least one actionable item based upon the at least one environmental condition; (iv) determines at least one provider based upon the actionable item; and (v) transmits a message to the at least one provider, such that the message includes the at least one actionable item. As a result, the speed and accuracy of providers learning about potential actionable items is increased.

A stability control system identifies an actionable condition, such as instability, in an off-road mobile machine, based upon an in-rubber tire sensor. A remedial action is identified, and a control signal is generated to control the mobile machine to take the remedial action.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The system can determine a collision avoidance path by: 1) predicting the behavior/trajectory of other moving objects (and identifying stationary objects); 2) given the driving trajectory (issued by autonomous driving system) or predicted driving trajectory (human), establishing the probability for a collision that can be calculated between the vehicle and one or more objects; and 3) finding a path to minimize the collision probability.