We propose to estimate 3D human pose from multi-view images and a few IMUs attached at person's limbs. It operates by firstly detecting 2D poses from the two signals, and then lifting them to the 3D space. We present a geometric approach to reinforce the visual features of each pair of joints based on the IMUs. This notably improves 2D pose estimation accuracy especially when one joint is occluded. We call this approach Orientation Regularized Network (ORN). Then we lift the multi-view 2D poses to the 3D space by an Orientation Regularized Pictorial Structure Model (ORPSM) which jointly minimizes the projection error between the 3D and 2D poses, along with the discrepancy between the 3D pose and IMU orientations. The simple two-step approach reduces the error of the state-of-the-art by a large margin on a public dataset. Our code will be released at https://github.com/microsoft/imu-human-pose-estimation-pytorch.

This paper proposes three route control strategies for autonomous vehicles (AVs) exiting to off-ramps. First, two microscopic lane-changing models are developed to simulate the off-ramp behaviors for AVs. A risk factor λ is introduced in the discretionary lane-changing (DLC) model, and a five-step process is developed for the mandatory lane-changing (MLC) model. Second, three route control strategies are presented, i.e., grading strategy (GS), half-overlap strategy (HOS), and full-overlap strategy (FOS). Finally, the extensive numerical simulations are conducted to analyze the characteristics of each strategy based on the MATLAB platform. The results indicate that the studied area displays significant variability in spatiotemporal dynamics of average velocity and road capacity under different strategies. It is found that the GS is the most effective control strategy for traffic congestion dissipation and travel delay reduction, followed by the HOS and, then, the FOS. The road capacity under the GS is increased by 19.1% and 7.8% compared to the FOS and the HOS, respectively. Furthermore, the GS consumes lower costs in terms of safety, travel efficiency, and route and lane switch frequency compared to the HOS and FOS, which is verified as the optimal strategy according to overall running cost. The findings of this paper can provide useful references for the design of AVs as well as the management of the automated highway systems.