Telematics company Risk Technology has launched Advanced Crash Detection (ACD), a patented technology that operates by using two independent methods for detecting impacts.
Negating the problems of false reports that conventional accelerometer technology utilises, Risk Technology’s ACD first detects G-forces acting on the vehicle in three axes x, y and z (fore and aft, lateral and vertical respectively) using an accelerometer array and then senses acoustic waves transmitted through the body of the vehicle. A collision is indicated only when the specific thresholds of both the acoustic and G-forces are met. Critically, acoustic sensing detects structure borne waves and not the sound from the impact (although the two occur simultaneously). Therefore loud music or the kids fighting on the rear seat will not trigger the sensing system.
Risk Technology has carried out extensive testing of its ACD technology using calibrated sensors within a controlled environment. The test vehicles were exposed to a range of test collisions at low speeds (to simulate the worst-case scenario), to evaluate the behaviour of the devices. The test vehicles were also fitted with laboratory instruments and cameras to record the tests in detail. The resulting data was sent to servers to ensure end-to-end functionality.
Vehicles were driven over a range of prepared test surfaces to ensure that noise, transmitted through the vehicle’s suspension, did not cause false readings. The findings, which have been validated by a world authority, proved that the technology provides the highest sensitivity and best crash discrimination.
Risk Technology is now planning to extract data from the vehicle to ascertain whether the brakes were applied at the time of the incident, the position of the throttle and if seat belts were fastened. The company also plans to expand the technology to include information on road conditions, weather, traffic density and traffic incidents at the locality. This information will help insurers and car investigators not only understand driver actions but also environmental factors thereby helping to increase accuracy and avoid possible misinterpretation of data.