R
R. Jayakrishnan
Researcher at University of California, Irvine
Publications - 160
Citations - 4366
R. Jayakrishnan is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Traffic simulation & Traffic flow. The author has an hindex of 30, co-authored 151 publications receiving 3887 citations. Previous affiliations of R. Jayakrishnan include Amrita Vishwa Vidyapeetham & Ernst & Young.
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An evaluation tool for advanced traffic information and management systems in urban networks
TL;DR: An evaluation model that incorporates the driver response to information, the traffic flow behavior, and the resulting changes in the characteristics of network paths, into an integrated simulation framework is presented.
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System performance and user response under real-time information in a congested traffic corridor
TL;DR: A modelling framework that consists of a special-purpose simulation component and a user decisions component that determines users' responses to the supplied information is developed to analyze the effect of in-vehicle real time information strategies on the performance of a congested traffic communing corridor.
Journal Article
A faster path-based algorithm for traffic assignment
TL;DR: A fresh look at the arguments against path-enumeration algorithms for the traffic assignment problem and the results of a gradient projection method are provided, showing that gradient projection converges in 1/10 iterations than the conventional Frank-Wolfe algorithm.
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Stochastic dynamic itinerary interception refueling location problem with queue delay for electric taxi charging stations
TL;DR: In this article, a new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flowinterception; (2) stochastic demand as dynamic service requests; and (3) queueing delay.
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Use of vehicle signature analysis and lexicographic optimization for vehicle reidentification on freeways
TL;DR: This paper formulates and solves the vehicle reidentification problem as a lexicographic optimization problem with the potential to yield reliable section measures such as travel times and densities, and enables the measurement of partial dynamic origin/destination demands.