Search Results

Monitoring driver’s postures has extensive applications. The postural information could be used for the development of smart airbags, for detecting possible fatigue in long travel and for recognizing activities which may determine if the driver has enough time to take over the control in an intelligent vehicle when encountering hazardous situations. Microsoft Kinect is one of the best candidates for monitoring driver’s posture thanks to its innovative feature of real time motion capture without use of markers and its low cost. However, when body parts are partially occluded, the accuracy of Kinect data will drop markedly. Inspired by previous researches, the present work focused on testing a data driven approach for improving driver’s upper body movement reconstruction with a Kinect camera. Firstly, we organize a database of accurately captured driver poses from different motion clips with filtered structures, including a global motion graph and multiple local motion graphs.

Rear-end accident is one of the most important collision modes in China, which often leads to severe accident consequences due to the high collision velocity. Autonomous Emergency Braking (AEB) system could perform emergency brake automatically in dangerous situation and mitigate the consequence. This study focused on the analysis of the rear-end accidents in China in order to discuss about the parameters of Time–to-Collision (TTC) and the comprehensive evaluation of typical AEB. A sample of 84 accidents was in-depth investigated and reconstructed, providing a comprehensive set of data describing the pre-crash matrix. Each accident in this sample is modeled numerically by the simulation tool PC-Crash. In parallel, a model representing the function of an AEB system has been established. This AEB system applies partial braking when the TTC ≤ TTC1 and full braking when the TTC ≤ TTC2.