Tarun Rambha

  • Citations Per Year
Learn More
In recent years, the automotive industry has been rapidly advancing toward connected vehicles with higher degrees of autonomous capabilities. This trend opens up many new possibilities for AI-based efficient traffic management. This paper investigates traffic optimization through the setting and broadcasting of dynamic and adaptive tolls under the(More)
Connected and autonomous vehicle technology has advanced rapidly in recent years. These technologies create possibilities for advanced AI-based traffic management techniques. Developing such techniques is an important challenge and opportunity for the AI community as it requires synergy between experts in game theory, multiagent systems, behavioral science,(More)
4. Title and Subtitle Investigating Regional Dynamic Traffic Assignment Modeling for Improved Bottleneck Analysis: Final Report 5. Report Date October 2012; Revised March 2013 Published June 2013 6. Performing Organization Code 7. Author(s) Jennifer C. Duthie, N. Nezamuddin, Natalia Ruiz Juri, Tarun Rambha, Chris Melson, C. Matt Pool, Stephen Boyles, S.(More)
Dynamic traffic assignment has grown steadily in popularity and use since its inception. It has become an important and permanent tool in transportation agencies across the country. However, the exact nature of DTA equilibrium, including existence and uniqueness results, is not fully known in simulation-based models. Specifically, we discuss the(More)
Traffic assignment is used to determine the number of users on roadway links in a network. While this problem has been widely studied in transportation literature, its use of the concept of equilibrium has attracted considerable interest in the field of game theory. The approaches used in both transportation and game theory disciplines are explored, and the(More)
This paper focuses on two commonly used path assignment policies for agents traversing a congested network: selfinterested routing, and system-optimum routing. In the selfinterested routing policy each agent selects a path that optimizes its own utility, while the system-optimum routing agents are assigned paths with the goal of maximizing system(More)
  • 1