An electric power steering device includes: a steering torque sensor that detects a steering torque; a current command value calculation unit that calculates a current command value based on the steering torque; an electric motor that generates a steering assist torque; a motor control unit that controls and drives the electric motor based on the current command value; a navigation controller and a GPS receiver that detects position information of a vehicle; and an operation assist unit that stores, in a map database, the steering torque detected by the steering torque sensor and the position information of the vehicle upon detection of the steering torque in association with each other and executes operation assist processing for assisting the driver in operating the steering wheel based on a past steering torque corresponding to current position information.

An electric power steering device includes: a steering torque sensor that detects a steering torque; a current command value calculation unit that calculates a current command value based on the steering torque; an electric motor that generates a steering assist torque; a motor control unit that controls and drives the electric motor based on the current command value; a navigation controller and a GPS receiver that detects position information of a vehicle; and an operation assist unit that stores, in a map database, the steering torque detected by the steering torque sensor and the position information of the vehicle upon detection of the steering torque in association with each other and executes operation assist processing for assisting the driver in operating the steering wheel based on a past steering torque corresponding to current position information.

Systems and methods for crash determination in accordance with embodiments of the invention are disclosed. In one embodiment, a vehicle telematics device includes a processor and a memory storing a crash determination application, wherein the processor, on reading the crash determination application, is directed to obtain sensor data from at least one sensor installed in a vehicle, calculate peak resultant data based on the sensor data, where the peak resultant data describes the acceleration of the vehicle over a first time period, generate crash score data based on the peak resultant data and a set of crash curve data for the vehicle, where the crash score data describes the likelihood that the vehicle was involved in a crash based on the characteristics of the vehicle and the sensor data, and provide the obtained sensor data when the crash score data exceeds a crash threshold to a remote server system.

At least one processor of an electronic device in a vehicle may be configured to: receive broadcast information which is broadcast from a beacon and includes reference data indicating the relative positional relationship between a designated object positioned in a designated place and the position of the beacon and the data of the designated place; in response to reception of the broadcast information, acquire sensed data indicating the relative positional relationship between the designated object and the vehicle through at least one sensor of the electronic device on the basis of the data of the designated place; in response to acquiring the sensed data, identify the difference between the sensed data and the reference data; identify whether the difference lies outside of a reference range; and determine correction of the at least one sensor to be required, on the basis of identification that the difference lies outside of the reference range.

Described herein are systems and methods for applying machine learning to telematics data to generate a unique vehicle fingerprint by periodically receiving telematics data generated at a plurality of sensors of a vehicle; standardizing the telematics data; aggregating the standardized telematics data; applying a trained machine learning model to embed the aggregated telematics data into a low-dimensional state; and generating a unique vehicle fingerprint, the vehicle fingerprint comprising a static component, a dynamic component, or both a static component and a dynamic component; including iterative repetition to update the dynamic component of the vehicle fingerprint.

Systems and methods for crash determination in accordance with embodiments of the invention are disclosed. In one embodiment, a vehicle telematics device includes a processor and a memory storing a crash determination application, wherein the processor, on reading the crash determination application, is directed to obtain sensor data from at least one sensor installed in a vehicle, calculate peak resultant data based on the sensor data, where the peak resultant data describes the acceleration of the vehicle over a first time period, generate crash score data based on the peak resultant data and a set of crash curve data for the vehicle, where the crash score data describes the likelihood that the vehicle was involved in a crash based on the characteristics of the vehicle and the sensor data, and provide the obtained sensor data when the crash score data exceeds a crash threshold to a remote server system.

Systems and methods for crash determination in accordance with embodiments of the invention are disclosed. In one embodiment, a vehicle telematics device includes a processor and a memory storing a crash determination application, wherein the processor, on reading the crash determination application, is directed to obtain sensor data from at least one sensor installed in a vehicle, calculate peak resultant data based on the sensor data, where the peak resultant data describes the acceleration of the vehicle over a first time period, generate crash score data based on the peak resultant data and a set of crash curve data for the vehicle, where the crash score data describes the likelihood that the vehicle was involved in a crash based on the characteristics of the vehicle and the sensor data, and provide the obtained sensor data when the crash score data exceeds a crash threshold to a remote server system.

Path generation apparatus configured to generate target path of own vehicle, includes: sensor configured to detect objects in forward area of own vehicle; and electronic control unit including processor and memory coupled to processor. Electronic control unit is configured to perform: recognizing adjacent vehicle traveling in adjacent lane adjacent to travel lane in which own vehicle travels from among objects detected by sensor; generating reference path of own vehicle in travel lane; setting safe area from side end portion of adjacent vehicle toward travel lane; and generating target path of own vehicle based on reference path. Generating target path includes: setting reference path to target path in predetermined section on forward side of own vehicle; and modifying reference path to ensure safe area between own vehicle and adjacent vehicle on forward side of predetermined section to generate target path.

Path generation apparatus configured to generate target path of own vehicle, includes: sensor configured to detect objects in forward area of own vehicle; and electronic control unit including processor and memory coupled to processor. Electronic control unit is configured to perform: recognizing adjacent vehicle traveling in adjacent lane adjacent to travel lane in which own vehicle travels from among objects detected by sensor; generating reference path of own vehicle in travel lane; setting safe area from side end portion of adjacent vehicle toward travel lane; and generating target path of own vehicle based on reference path. Generating target path includes: setting reference path to target path in predetermined section on forward side of own vehicle; and modifying reference path to ensure safe area between own vehicle and adjacent vehicle on forward side of predetermined section to generate target path.

Among other things, planning a motion of a machine having moving capabilities is based on strategic guidelines derived from various basic principles, such as laws, ethics, preferences, driving experiences, and road environments.