An Accurate and Convenient Method of Vehicle Spatiotemporal Distribution Recognition Based on Computer Vision.

The Convenient and accurate identification of the traffic load of passing vehicles is of great significance to bridge health monitoring. The existing identification approaches often require prior environment knowledge to determine the location of the vehicle load, i.e., prior information of the road, which is inconvenient in practice and therefore limits its application. Moreover, camera disturbance usually reduces the measurement accuracy in case of long-term monitoring. In this study, a novel approach to identify the spatiotemporal information of passing vehicles is proposed based on computer vision. The position relationship between the camera and the passing vehicle is established, and then the location of the passing vehicle can be calculated by setting the camera shooting point as the origin. Since the angle information of the camera is pre-determined, the identification result is robust to camera disturbance. Lab-scale test and field measurement have been conducted to validate the reliability and accuracy of the proposed method.

A method for rapid demolition of a crossline arch bridge: a case study.

To reduce the adverse impact of demolition of the symmetrical rigid frame arch bridge overcrossing the highway with over-saturated traffic flow, a rapid demolition method based on the Self-Propelled Modular Transporter (SPMT) technique was developed in this study. The calculation formulae for reaction forces of the supporting brackets, as well as driving force and stability of SPMTs, were derived by analyzing the stability, synchronization, and influencing parameters of the cut bridge body-transport system. In addition, a monitoring system during the whole process was developed to ensure the demolition safety. An application of demolishing a crossline symmetrical rigid frame arch bridge in China within 5 h has been presented. The results showed that the proposed method can be successfully applied in real projects, leading to significant reduction in traffic impact, energy consumption, and environmental pollution.