AA-FVDM: an accident-avoidance full velocity difference model for animating realistic street-level traffic in rural scenes

Most of existing traffic simulation efforts focus on urban regions with a coarse two-dimensional representation; relatively few studies have been conducted to simulate realistic three-dimensional traffic flows on a large, complex road web in rural scenes. In this paper, we present a novel agent-based approach called accident-avoidance full velocity difference model (abbreviated as AA-FVDM) to simulate realistic street-level rural traffics, on top of the existing FVDM. The main distinction between FVDM and AA-FVDM is that FVDM cannot handle a critical real-world traffic problem while AA-FVDM settles this problem and retains the essence of FVDM. We also design a novel scheme to animate the lane-changing maneuvering process (in particular, the execution course). Through numerous simulations, we demonstrate that besides addressing a previously unaddressed real-world traffic problem, our AA-FVDM method efficiently (in real time) simulates large-scale traffic flows (tens of thousands of vehicles) with realistic, smooth effects. Furthermore, we validate our method using real-world traffic data, and the validation results show that our method measurably outperforms state-of-the-art traffic simulation methods.Copyright © 2013 John Wiley & Sons, Ltd. We present a novel agent-based approach called accident-avoidance full velocity difference model (AA-FVDM) to simulate realistic street-level rural traffics, on the basis of the existing FVDM. We also design a novel scheme to animate the lane-changing process. Through numerous simulations, we demonstrate that besides addressing a previously unaddressed real-world traffic problem, our AA-FVDM method efficiently simulates large-scale realistic traffic flows. We validate our method using real traffic data, and the results show that our method measurably outperforms state-of-the-art traffic simulation methods. Copyright © 2013 John Wiley & Sons, Ltd.