Systems and methods are provided and include a communication gateway of a control module. The communication gateway establishes wireless communication connections with a plurality of user devices. A plurality of sensors are configured to, in response to the plurality of user devices being connected to the communication gateway, communicate signal information about the wireless communication connections to the control module. The signal information indicates characteristics of the wireless communication connections. The control module (i) determines a location of each user device of the plurality of user devices based on the signal information and (ii) generates a plurality of entries based on the signal information. Each entry of the plurality of entries corresponds to each of the plurality of user devices. A user settings activation module (i) determines user profiles corresponding to each entry of the plurality of entries and (ii) activates at least one vehicle function based on the user profiles.

Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

A vehicle, system and method for operating the vehicle is disclose. The system includes a radar system and a processor. The radar system locates a gap between targets in a second lane adjoining a first lane, with the host vehicle residing in the first lane. The processor is configured to determine a viability value of the gap for a lane change, select the gap based on the viability value, align the host vehicle with the selected gap, and merge the host vehicle from the first lane into the selected gap in the second lane.

In one embodiment, a method by a computing system of a vehicle includes determining an environment of the vehicle. The method includes generating, based on the environment, multiple proposed vehicle actions with associated operational data. The method includes determining a comfort level for each proposed vehicle action by processing the environment and operational data using a model for predicting comfort levels of vehicle actions. The model is trained using records of performed vehicle actions. The record for each performed vehicle action includes environment data, operational data, and a perceived passenger comfort level for the performed vehicle action. The method includes selecting a vehicle action from the proposed vehicle actions based on the determined comfort level. The method includes causing the vehicle to perform the selected vehicle action.

Implementations described herein relate to leveraging corresponding streams of speed readings of a vehicle generated by different speed sensors of different computing devices to automatically determine an updated tire size of tires of the vehicle. For example, while a user of the vehicle is driving, a first stream of speed readings can be generated by a vehicle speed sensor of an in-vehicle computing device of the vehicle and a second stream of speed readings can be generated by a mobile speed sensor of a mobile computing device of the user of the vehicle. Processor(s) can obtain the different streams of speed readings from the different computing devices and process the different streams using various operations to determine the update tire size of the tires of the vehicle. The updated tire size can be subsequently utilized to update operational parameter(s) of the vehicle that influence how the vehicle operates.

A vehicle travel control device executes vehicle travel control such that a vehicle follows a target trajectory. An automated driving control device generates a first target trajectory that is the target trajectory for automated driving of the vehicle. The vehicle travel control device further determines whether or not an activation condition of travel assist control is satisfied. When the activation condition is satisfied, the vehicle travel control device generates a second target trajectory that is the target trajectory for the travel assist control. When the second target trajectory is generated during the automated driving, the vehicle travel control device determines whether or not a cancellation condition is satisfied. When the cancellation condition is satisfied, the vehicle travel control device cancels both the first target trajectory and the second target trajectory, and decelerates the vehicle.

A parking assist system includes: a control device configured to execute a driving process for autonomously moving a vehicle to a target position; a steering operation member configured to receive a steering operation performed by an occupant; a vehicle state detecting device; and a notification device configured to make a notification to the occupant. In the driving process, the control device executes vehicle speed control and steering control. When, during execution of the driving process, the control device determines that the vehicle is a suspension state in which the driving process should be temporarily suspended, the control device causes the notification device to output a prescribed notification and executes a suspension process. In the suspension process, the control device executes the vehicle speed control to stop the vehicle and stops the steering control.

A database of high risk locations is formed and high risk causal factors for the high risk locations determined. Driver behavior is monitored at the sites in the database using data collection devices such as electronic logging devices or mobile phones to see if the drivers exhibit the same specific behaviors that are considered contributing factors to specific accident types at risk of occurrence at those sites. Warnings are provided to drivers approaching the specific sites to prompt behavioral changes which may further be monitored by the data collection devices.

A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.