A soft body system adapted to form the body and exterior surface of a Guided Soft Target for testing crash avoidance technologies in a subject vehicle is disclosed. The soft body system is adapted to be mounted atop a motorized Dynamic Motion Element (DME) and when so mounted is adapted to collide with the subject vehicle while the DME is moving. The soft body system includes a semi-rigid form with an exterior surface. The form is sufficiently yielding so as to impart a minimal force to the subject vehicle upon impact. The form may be shaped like a vehicle or a part of a vehicle. The exterior surface includes a side skirt made of radar absorptive material (RAM), radar reflective material (RRM) or a combination of both, which is positioned adjacent to the ground and constructed to prevent radar wave from entering the soft body system.

A soft body system adapted to form the body and exterior surface of a Guided Soft Target for testing crash avoidance technologies in a subject vehicle is disclosed. The soft body system is adapted to be mounted atop a motorized Dynamic Motion Element (DME) and when so mounted is adapted to collide with the subject vehicle while the DME is moving. The soft body system includes a semi-rigid form with an exterior surface. The form is sufficiently yielding so as to impart a minimal force to the subject vehicle upon impact. The form may be shaped like a vehicle or a part of a vehicle. The exterior surface includes a side skirt made of radar absorptive material (RAM), radar reflective material (RRM) or a combination of both, which is positioned adjacent to the ground and constructed to prevent radar wave from entering the soft body system.

An input unit 81 receives input of a normal pattern file including information indicating a normal condition of a vehicle, and a fault pattern file including information indicating a sign that a vehicle fault is about to occur. A collection unit 82 collects observation data observed by each device in the target vehicle. A comparison unit 83 compares the content of the normal pattern file with the content of the observation data. when the difference between the content of the normal pattern file and the content of the observation data is greater than a predetermined first threshold value, the comparison unit 83 further compares the content of the fault pattern file and the observation data, and when the difference between the content of the fault pattern file and the observation data is within a predetermined second threshold value, determines that there is the sign of the fault in the target vehicle.

Various embodiments of the present disclosure are directed to test stands for generating test runs on the basis of a test drive using a vehicle along a driving route. In some embodiments, a test stand determines at least one idle operating time of an internal combustion engine and/or at least one overrun operating time of the internal combustion engine from a time curve of a vehicle speed and a time curve of a gas pedal position. The test stand may further set a specified idle control mode instead of the operating control mode during an idle operating time and/or a specified overrun control mode is set instead of the operating control mode during an overrun operating time in the test stand automation unit in order to carry out the test run.

Various embodiments of the present disclosure are directed to test stands for generating test runs on the basis of a test drive using a vehicle along a driving route. In some embodiments, a test stand determines at least one idle operating time of an internal combustion engine and/or at least one overrun operating time of the internal combustion engine from a time curve of a vehicle speed and a time curve of a gas pedal position. The test stand may further set a specified idle control mode instead of the operating control mode during an idle operating time and/or a specified overrun control mode is set instead of the operating control mode during an overrun operating time in the test stand automation unit in order to carry out the test run.

There is provided a method of specifying a location of occurrence of an abnormal sound, the method including: storing mapping data in a storage device, the mapping data prescribing mapping that receives, as inputs, a sound variable that matches a sound detected in a vehicle and a state variable of a drive-system device of the vehicle synchronized with the sound, and that outputs a location as a main cause of the sound; executing a sound signal acquisition process of acquiring a sound signal output from a microphone that detects a sound; a state variable acquisition process of acquiring the state variable of the drive-system device; and a specifying process of specifying the location of occurrence of the sound corresponding to the sound signal using the sound variable and the state variable as inputs to the mapping. There are also provided a non-transitory storage medium and an in-vehicle device.

Systems and methods are provided for monitoring the structural integrity of a vehicle. In particular, systems and methods are provided for using transducers positioned at various location in and on a vehicle to measure parameters related vehicle structural health. In various implementations, the integrity of the vehicle frame and the integrity of the vehicle body are monitored using a multi-axis accelerometer and/or microphone. The use of transducers for monitoring can replace time-consuming and expensive manual inspections.

Systems and methods are provided for monitoring the structural integrity of a vehicle. In particular, systems and methods are provided for using transducers positioned at various location in and on a vehicle to measure parameters related vehicle structural health. In various implementations, the integrity of the vehicle frame and the integrity of the vehicle body are monitored using a multi-axis accelerometer and/or microphone. The use of transducers for monitoring can replace time-consuming and expensive manual inspections.

Disclosed are a Type-II Autonomous Emergency Braking System (AEBS) test and evaluation device and method based on a BeiDou space-time reference, where the device includes three parts: a roadside-end information acquisition module, a vehicle-end information acquisition module, and an integrated information processing module. The roadside-end information acquisition module can acquire accurate message sending time by means of a BeiDou time service unit; the vehicle-end information acquisition module can acquire accurate time of receiving a roadside-end message, information acquired by a combined inertial navigation unit, and audio/vibration information acquired by a Single Chip Microcomputer (SCM) embedded unit; and the integrated information processing module can implement accurate, quantitative test and evaluation of indexes such as a vehicle-road communication delay and warning signal sending time. The method of the present disclosure performs data analysis and processing based on a globally unified BeiDou space-time reference and by means of a Support Vector Machine (SVM)-based dynamic Hermite interpolation method, which has an accurate test and evaluation result. Further, the method does not have any requirements for a communication system of the type-II AEBS, thus achieving convenient testing and a wide range of application.

Disclosed are a Type-II Autonomous Emergency Braking System (AEBS) test and evaluation device and method based on a BeiDou space-time reference, where the device includes three parts: a roadside-end information acquisition module, a vehicle-end information acquisition module, and an integrated information processing module. The roadside-end information acquisition module can acquire accurate message sending time by means of a BeiDou time service unit; the vehicle-end information acquisition module can acquire accurate time of receiving a roadside-end message, information acquired by a combined inertial navigation unit, and audio/vibration information acquired by a Single Chip Microcomputer (SCM) embedded unit; and the integrated information processing module can implement accurate, quantitative test and evaluation of indexes such as a vehicle-road communication delay and warning signal sending time. The method of the present disclosure performs data analysis and processing based on a globally unified BeiDou space-time reference and by means of a Support Vector Machine (SVM)-based dynamic Hermite interpolation method, which has an accurate test and evaluation result. Further, the method does not have any requirements for a communication system of the type-II AEBS, thus achieving convenient testing and a wide range of application.