Showing papers by "Gitakrishnan Ramadurai published in 2009"

Comprehensive Review of Emerging Technologies for Congestion Reduction and Safety

Abstract: The New York Metropolitan Transportation Council (NYMTC) funded a project executed by a team from Rensselaer Polytechnic Institute to perform a comprehensive scan of emerging technologies that could affect transportation in the New York City metropolitan region in the next 20 years. A primary goal of the technology scan is to develop a document that serves as a one-stop shop for emerging technology that may be considered for implementation by different transportation agencies in the NYMTC region. This paper briefly presents the different emerging technologies, their characteristics, and important results from the project pertaining to congestion reduction and safety objectives.

Complementarity Formulations for User Equilibrium and Ideal System State in Dynamic Transportation Networks

Abstract: A key fundamental research question in real-time guidance in dynamic transportation networks is: Can this paper characterize and compute system states which are close to system-optimal state but does not make any individual worse off as compared to the equilibrium problem? Within the static network assignment context this question has recently been addressed by Jahn et al. (2005), where they motivate a route-guidance system based on a constrained system optimal formulation that maximizes the total travel time subject to certain user constraints. Unlike static traffic assignment, dynamic traffic assignment does not have a well-accepted analytical formulation with realistic traffic flow models. The present paper provides an analytical formulation of dynamic traffic equilibrium problem with a realistic traffic flow model – the cell transmission model. We develop an analytical formulation using complementarity constraints for the cell transmission model. The dynamic user equilibrium (DUE) state is formulated as a Mixed Linear Complementarity problem. We subsequently define an ideal system state that ensures the best possible system state such that no user is worse off compared to the user equilibrium state. The ideal system state is modeled as a Linear Program with Linear Complementarity Constraints. The paper provides a strong theoretical modeling framework for prescriptive travel guidance systems that seek to improve overall system payoff without negatively impacting any user.