The present disclosure relates to a testing method and a testing system for a human stress reaction, and a computer-readable storage medium. The testing method for the human stress reaction includes acquiring position information and visual field information of a testee in a virtual road traffic scene after the virtual road traffic scene is established; guiding the testee into a test zone when the testee is within a test-waiting zone and when a visual field direction of the testee faces the test zone, and simultaneously, starting acquiring stress reaction data of the testee; controlling a virtual reality environment module to create a virtual stress event in the test zone after it is determined that the testee is within the test zone, and applying a stimulation to the testee, such that the testee make a stress reaction.

The present disclosure relates to a testing method and a testing system for a human stress reaction, and a computer-readable storage medium. The testing method for the human stress reaction includes acquiring position information and visual field information of a testee in a virtual road traffic scene after the virtual road traffic scene is established; guiding the testee into a test zone when the testee is within a test-waiting zone and when a visual field direction of the testee faces the test zone, and simultaneously, starting acquiring stress reaction data of the testee; controlling a virtual reality environment module to create a virtual stress event in the test zone after it is determined that the testee is within the test zone, and applying a stimulation to the testee, such that the testee make a stress reaction.

Systems and methods are disclosed for educating vehicle drivers. Auto insurance claim data may be analyzed to identify hazardous areas associated with an abnormally high amount or severity of vehicle collisions. A virtual navigation map of roads within the hazardous areas may be built or generated. A common cause of several vehicle collisions at a hazardous area may be identified, and a virtual reconstruction of a scenario involving the common cause and/or a road map of collisions locations of may be created. The virtual reconstruction of the scenario may be displayed on a driver education virtual simulator to enhance driver education and reduce the likelihood of vehicle collisions.

Systems and methods are disclosed for educating vehicle drivers. Auto insurance claim data may be analyzed to identify hazardous areas associated with an abnormally high amount or severity of vehicle collisions. A virtual navigation map of roads within the hazardous areas may be built or generated. A common cause of several vehicle collisions at a hazardous area may be identified, and a virtual reconstruction of a scenario involving the common cause and/or a road map of collisions locations of may be created. The virtual reconstruction of the scenario may be displayed on a driver education virtual simulator to enhance driver education and reduce the likelihood of vehicle collisions.

Methods and systems are described for generating a vehicle-to-vehicle traffic alert and updating a vehicle-usage profile. Various aspects include detecting, via one or more processors associated with a first vehicle, that an abnormal traffic condition exists in an operating environment of the first vehicle. An electronic message is generated and transmitted wirelessly, via a vehicle-mounted transceiver associated with the first vehicle, to alert a nearby vehicle of the abnormal traffic condition and to allow the nearby vehicle to avoid the abnormal traffic condition. The first vehicle receives telematics data regarding operation of the nearby vehicle after the nearby vehicle received the electronic message, and transmits the telematics data to a remote server for updating a vehicle-usage profile associated with the nearby vehicle.

Method and system for generating virtual experiences. For example, the method includes receiving first real-world telematics data associated with a first real-world user, determining first real-world driving characteristics based upon the first real-world telematics data, generating first virtual experiences based upon the first real-world driving characteristics, presenting the first virtual experiences in a virtual game, receiving second real-world telematics data associated with a second real-world user, determining second real-world driving characteristics based upon the second real-world telematics data, generating second virtual experiences based upon the second real-world driving characteristics, and presenting the second virtual experiences in the virtual game, where the first virtual experiences are different from the second virtual experiences.

Methods and systems for improving vehicular safety by utilizing uplift modeling techniques to improve a driving tip treatment generation model are provided. According to embodiments, a tip server can analyze telematics data associated with operation of one or more vehicles to determine that a driving tip should be provided to a driver of a vehicle. The tip server then utilize a treatment generation model to determine a treatment for how to provide the driving tip in a manner optimized for the particular driver. The tip server can analyze additional telematics data to determine an effectiveness of the driving tip and to update the treatment generation model in accordance with uplift modeling techniques.

Methods and systems for improving vehicular safety by utilizing uplift modeling techniques to improve a driving tip treatment generation model are provided. According to embodiments, a tip server can analyze telematics data associated with operation of one or more vehicles to determine that a driving tip should be provided to a driver of a vehicle. The tip server then utilize a treatment generation model to determine a treatment for how to provide the driving tip in a manner optimized for the particular driver. The tip server can analyze additional telematics data to determine an effectiveness of the driving tip and to update the treatment generation model in accordance with uplift modeling techniques.

Methods and systems are described for generating a vehicle-to-vehicle traffic alert and updating a vehicle-usage profile. Various aspects include detecting, via one or more processors associated with a first vehicle, that an abnormal traffic condition exists in an operating environment of the first vehicle. An electronic message is generated and transmitted wirelessly, via a vehicle-mounted transceiver associated with the first vehicle, to alert a nearby vehicle of the abnormal traffic condition and to allow the nearby vehicle to avoid the abnormal traffic condition. The first vehicle receives telematics data regarding operation of the nearby vehicle after the nearby vehicle received the electronic message, and transmits the telematics data to a remote server for updating a vehicle-usage profile associated with the nearby vehicle.

A method of training a trainee includes a sensor configured to measure at least one biological indicator of stress in the trainee. The method includes presenting a training segment in the simulation while monitoring inputs from the trainee. Data is read from the sensor and an instantaneous stress level of the trainee is calculated from the data. If the instantaneous stress level greater than a predetermined value, a stress-change feature is selected that will reduce stress and applying the stress-change feature to the training segment, thereby reducing complexity of the training segment for reducing the instantaneous stress of the trainee. for example, the stress-change feature is changing the weather, adding/removing bad drivers, adding/removing pedestrians, etc.