A computer-implemented method of generating and broadcasting telematics and/or image data is provided. Telematics and/or image data may be collected, with customer permission, in real-time by a mobile device (or a Telematics App running thereon) traveling within an originating vehicle. The telematics data may include acceleration, braking, speed, heading, and location data associated with the originating vehicle. The mobile device may generate an updated telematics data broadcast including up-to-date telematics data at least every few seconds; and then broadcast the updated telematics data broadcast at least every few seconds via wireless communication to another computing device to facilitate alerting another vehicle or driver of an abnormal traffic condition or event that the originating vehicle is experiencing. An amount that an insured uses or otherwise employs the telematics data-based risk mitigation or prevention functionality may be used with usage-based insurance, or to calculate or adjust insurance premiums or discounts.

A computer-implemented method of generating and broadcasting telematics and/or image data is provided. Telematics and/or image data may be collected, with customer permission, in real-time by a mobile device (or a Telematics App running thereon) traveling within an originating vehicle. The telematics data may include acceleration, braking, speed, heading, and location data associated with the originating vehicle. The mobile device may generate an updated telematics data broadcast including up-to-date telematics data at least every few seconds; and then broadcast the updated telematics data broadcast at least every few seconds via wireless communication to another computing device to facilitate alerting another vehicle or driver of an abnormal traffic condition or event that the originating vehicle is experiencing. An amount that an insured uses or otherwise employs the telematics data-based risk mitigation or prevention functionality may be used with usage-based insurance, or to calculate or adjust insurance premiums or discounts.

A method for calculating a lateral position of an ego motor vehicle on a traffic lane includes calculating a first theoretical lateral position of the ego vehicle, calculating a second theoretical lateral position of the ego vehicle, calculating a third theoretical lateral position of the ego vehicle, calculating the lateral position of the ego vehicle using a weighted average of the first lateral position, the second lateral position, and the third lateral position.

A method of processing data for an autonomous vehicle, an electronic device, a storage medium, and an autonomous vehicle are provided. The method includes: acquiring sensor data for the autonomous vehicle, wherein the sensor data includes inertial measurement data, LiDAR data, and visual image data; determining a first constraint factor for the inertial measurement data according to the inertial measurement data and the visual image data; determining a second constraint factor for the LiDAR data according to the inertial measurement data and the LiDAR data; determining a third constraint factor for the visual image data according to the inertial measurement data, the visual image data and the LiDAR data; and processing the sensor data based on the first constraint factor, the second constraint factor and the third constraint factor, so as to obtain positioning data for positioning the autonomous vehicle.

A method of processing data for an autonomous vehicle, an electronic device, a storage medium, and an autonomous vehicle are provided. The method includes: acquiring sensor data for the autonomous vehicle, wherein the sensor data includes inertial measurement data, LiDAR data, and visual image data; determining a first constraint factor for the inertial measurement data according to the inertial measurement data and the visual image data; determining a second constraint factor for the LiDAR data according to the inertial measurement data and the LiDAR data; determining a third constraint factor for the visual image data according to the inertial measurement data, the visual image data and the LiDAR data; and processing the sensor data based on the first constraint factor, the second constraint factor and the third constraint factor, so as to obtain positioning data for positioning the autonomous vehicle.

A tracking system has a first tracking module and a second tracking module, the position and/or orientation of which relative to each other can be determined by means of a sensor device of the tracking system to determine relative movements of a first vehicle part of a set of vehicles relative to a second vehicle part of the set of vehicles that is movably connected to the first vehicle part. The first tracking module is connected to the first vehicle part and the second tracking module is connected to the second vehicle part.

A tracking system has a first tracking module and a second tracking module, the position and/or orientation of which relative to each other can be determined by means of a sensor device of the tracking system to determine relative movements of a first vehicle part of a set of vehicles relative to a second vehicle part of the set of vehicles that is movably connected to the first vehicle part. The first tracking module is connected to the first vehicle part and the second tracking module is connected to the second vehicle part.

A method may include obtaining, by an autonomous driving system, input information relating to an autonomous vehicle (AV). The method may include determining, by the autonomous driving system, one or more driving signals that describe operations of the AV. The method may include instructing the AV to move according to the driving signals and simulating, by a virtual driving system, movement of the AV based on the driving signals, wherein the simulating the movement of the AV occurs concurrently with the AV moving according to the driving signals as instructed.

A method may include obtaining, by an autonomous driving system, input information relating to an autonomous vehicle (AV). The method may include determining, by the autonomous driving system, one or more driving signals that describe operations of the AV. The method may include instructing the AV to move according to the driving signals and simulating, by a virtual driving system, movement of the AV based on the driving signals, wherein the simulating the movement of the AV occurs concurrently with the AV moving according to the driving signals as instructed.

Provided are methods for controlling vehicle performance based on data associated with an environmental condition.