A device for controlling platooning includes a communication device configured to support wireless communication between a vehicle and a preceding vehicle, and a processor connected to the communication device, wherein the processor is configured to monitor a communication performance between the vehicle and the preceding vehicle during the platooning and to control a behavior of the vehicle by selectively applying first longitudinal direction control logic or second longitudinal direction control logic based on the communication performance.

A vehicle controller and a headway distance control method are provided. The vehicle controller includes an object information obtaining device that obtains information about an object around a vehicle, a forward gazing detecting device that detects whether a driver in the vehicle keeps his or her eyes on the road, and a headway distance controller that controls a headway distance between the vehicle and a forward vehicle which is traveling in front of the vehicle depending on whether the driver keeps his or her eyes on the road.

A system and a method for adjusting a yielding space of a platoon are provided. The system can include camera modules, sensors, interface circuitry, processing circuitry, and memory. The sensors can detect one or more behaviors of one or more vehicles adjacent to the platoon. The processing circuitry can determine one or more triggering events between the one or more vehicles and the platoon based on the one or more behaviors. The processing circuitry can adjust the yielding space of the platoon.

A system and method are provided for Bayesian updating of distributions of factors that affect tire wear. Information is accumulated in data storage regarding probability distributions corresponding to each of a respective plurality of tire wear factors. Vehicle data comprising movement data and location data collected in association with a vehicle is transmitted from the vehicle to a centralized (e.g., cloud) computing device or network. At least one observation corresponding to one or more of the plurality of factors is generated based on the transmitted vehicle data. A Bayesian estimation is then generated of a tire wear status at a given time for at least one tire associated with the vehicle, based at least on the at least one generated observation and the stored information regarding probability distributions. The predictions accordingly carry a measure of uncertainty, and Bayesian inference can be used to update distributions based on the observations.

A system and method are provided for predicting the non-linear progression in vehicle tire wear. The system determines an original tread depth for a tire associated with a vehicle, and further determines an initial wear rate for the tire based at least partially on the original tread depth. One or more tire conditions are measured as time-series inputs to a predictive tire wear model, for example utilizing “brush-type” tire wear models for a contact interface between a base material of the tire and road surfaces, wherein the interface is represented as a plurality of independently deformable elements, wherein a current wear rate is normalized based at least partially on said inputs to the initial wear rate for the tire. The system can then predict a tire wear status of the tire for specified future parameters, such as for example a specified future distance traveled or a time traveled.

A system and method are provided for estimating progression in vehicle tire wear. A tread depth is stored at a first (e.g., initial or unworn) stage for a given tire, along with a first set of modal frequencies for the tire. At a later (e.g., worn) stage, for example in concert with a controlled excitation of tire structural modes, a second set of corresponding modal frequencies are sensed for the tire, and a tire wear status of the tire is determined at the second stage based on a calculated frequency shift between at least one corresponding modal frequency from each of the first and second sets. In one example, an initial mass of the tire is stored, and a change in mass is calculated based on the calculated frequency shift. Alternatively, a correlation of modal frequency shift may be performed with respect to tread depth for a given tire.

A vehicle control device aims to ensure more appropriate self-driving based on circumstances around its own vehicle. The vehicle control device controls an engine and a motor such as to drive the vehicle with changing over between motor drive without operation of the engine and hybrid drive with operation of the engine. In the motor drive in a self-driving mode where the vehicle is driven independently of a driver's accelerating or decelerating operation, the vehicle control device maintains the motor drive when an other vehicle condition is not met, where the other vehicle condition is a condition that any other vehicle is present in a predetermined distance at least either ahead of the own vehicle or behind the own vehicle, while allowing for a shift to the hybrid drive when the other vehicle condition is met.

A device, method, and processor readable storage medium for controlling travel of a vehicle. The device includes a processor and a controller; the processor is configured to set a speed curve of the vehicle according to a relative speed and distance between the vehicle and the front subject, and the controller is configured to control the vehicle to travel according to the set speed curve.

The present invention relates to a vehicle control apparatus least a partial automatic control over the travel of the host vehicle. A following variable generating unit (96) calculates a predicted position of an other vehicle at a predicted time point ahead of the present time point, sets a target position which is short of the predicted position by a target intervehicle distance, and determines a first following variable for causing the host vehicle to reach the target position at the predicted time point.

Provided herein is a system and method for fleet coordination in a vehicle. The system comprises one or more sensors, one or more processors, and a memory storing instructions that, when executed by the one or more processors, cause the system to perform, capturing current data associated with the vehicle, planning a route of the vehicle based on the captured current data, navigating the vehicle in accordance with the planned route, detecting an instant position of the vehicle while navigating the vehicle, and coordinating a movement of another vehicle with the vehicle based on the detected instant position of the vehicle.