CEE Seminar: MIDAS-CPS - The Possible Future of Proactive Traffic

Anteater Instruction & Research Building (AIRB) 4080
Pitu Mirchandani, Ph.D.

Computing, Informatics & Decision Systems Engineering
Arizona State University

Abstract:  While driving on your favorite route to a destination, have you ever wondered why the technology for traffic management is so antiquated? My answer is that the people and organization that manage the traffic are not cyber-physicists nor real-time optimizers. MIDAS hopes to demonstrate the synergistic use of a cyber-physical infrastructure consisting of smart-phone type devices, cloud computing, wireless communication, and intelligent transportation systems to manage vehicles in the complex urban network. Through the use of traffic controls, route advisories and road pricing/rewards, it can jointly optimize drivers’ mobility as well as achieve the sustainability goals of reducing energy usage and improving air quality. A key element of MIDAS-CPS is the real-time streaming data collection and data analysis, which enables subsequent traffic management through proactive traffic controls and advisories, through visualizations of predicted queues, effective road prices/rewards and route advisories. Although drivers will not be forced to use recommended routes, it is anticipated that MIDAS-CPS would lead to less driver stress and improved road safety, plus benefit the environment, energy consumption, congestion mitigation and driver mobility. This talk will focus on overall architecture of MIDAS and its proactive traffic management component, while the sponsored multidisciplinary NSF project is at the cutting edge in several areas: real-time image processing, real-time traffic prediction and supply/demand management, and data processing/management through cloud computing.

 Bio: Pitu B. Mirchandani, B.S./M.S. degrees in engineering from UCLA; S.M./Sc.D. degrees, operations research from MIT, is a professor of computing, informatics and decision systems engineering at Arizona State University (ASU) where he holds the AVNET Chair for Supply Chain Networks. Mirchandani has been studying dynamic stochastic networks for close to 40 years. HIs specific interests are in models and systems for making strategic/tactical/operational decisions in dynamic and stochastic networked environments. Mirchandani’s contributions are in location decision modeling, traveler and vehicle routing models,  real-time data-driven decision systems and general theoretical contributions to OR modeling, methods and algorithms. Mirchandani has authored/co-authored four books and approximately 200 articles, and he has been a principal investigator on many research programs. He is a lifetime member of IEEE and a Fellow of INFORMS.

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