Virtualized traffic at metropolitan scales
Abstract
Few phenomena are more ubiquitous than traffic in urban scenes, and few are more significant economically, socially, or environmentally. Many virtual-reality applications and systems, including virtual globes and immersive multi-player worlds that are often set in a large-scale modern or futuristic setting, feature traffic systems. Virtual-reality models can also aid in addressing the challenges of real-world traffic - the ever-present gridlock and congestion in cities worldwide: traffic engineers and planners can diagnose system instabilities and explore control strategies in virtual worlds reconstructed from available sensor data. To create these VR systems with traffic mimicking real-world conditions, road network models need to be created and represented. Traffic needs to be realistically and efficiently simulated. To analyze real-world scenarios, the traffic conditions need to be estimated and reconstructed. To create virtual scenarios, such as simulated cities, traffic needs to be intelligently and efficiently routed. These applications all require research advances in road network capture and modeling, intelligent traffic routing and simulation, and traffic state estimation and reconstruction. New systems need to be designed that combine these components with visual and analytical infrastructure. In this paper, we present some state-of-the-art approaches for these areas as well as our vision for unified virtual-reality traffic systems that combine and integrate them to achieve virtualized traffic.
Publication Title
Frontiers Robotics AI
Recommended Citation
Wilkie, D., Sewall, J., Li, W., & Lin, M. (2015). Virtualized traffic at metropolitan scales. Frontiers Robotics AI, 2 (MAY) https://doi.org/10.3389/frobt.2015.00011
