Srinivas Peeta, Ph.D.

ACT Lab, Georgia Institute of Technology

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Fort Benning visits ACT lab

(January, 2020)

ACT Lab was honored to host Fort Benning Garrison Commander Colonel Matthew Scalia and his team to discuss Installations for the Future for Fort Benning at Georgia Tech. Dr. Peeta demonstrated ACT lab’s facilities and capabilities to the Fort Benning team.

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New Tier 1 University Transportation Center awarded

(August, 2020)

Dr. Peeta is a member of the Georgia Tech-led $1 million Tier 1 University Transportation Center, T-SCORE: Transit – Serving Communities Optimally, Responsively, and Efficiently. The UTC aims to define a set of strategic visions that will guide transit into a sustainable and resilient future.

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Autonomous transportation and connected roads (ATCR) seed grant awarded

(January 2020)

ACT lab was awarded a grant from City of Peach Corners for investigating the role of urban infrastructure modifications on the performance of autonomous vehicles (AVs) in mixed traffic environments. ACT lab’s high-fidelity driving simulator would be used to evaluate the infrastructure designs that can enhance transportation safety.  read more

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Course on traffic management with the aid of modern sensors

(December 2019)

In association with Anna University, Dr. Peeta offered a one-week course in Chennai, India on the use and implementation of modern sensors and technologies for the traffic management in Indian traffic conditions. 

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Dr. Srinivas Peeta is recognized as IIT Madras distinguished alumnus

(2019)

Dr. Srinivas Peeta was awarded the Distinguished Alumnus Award from the Indian Institute of Technology (IIT) Madras. The honor was bestowed on only 159 alumni in the awards 25-year existence.

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Dr. Srinivas Peeta is the Dickerson Chair and Professor at Georgia Institute of Technology. His research interests are multidisciplinary, span several methodological domains, and include among others:

  • Connected and autonomous vehicles
  • Modeling and analysis of the dynamics of large-scale transportation systems
  • Modeling and methodologies to address interdependencies among infrastructure systems
  • Real-time information-based navigation in vehicular traffic networks
  • Modeling human behavior/learning associated with drivers/travelers
  • Integrated supply-demand-performance models for strategic planning and real-time operations for various applications
  • Understanding linkages between transportation, energy and the environment
  • Modeling policy options that impact transportation system evolution
  • Systems and system-of-systems perspectives to address complex adaptive systems (ranging from engineered systems to human enterprise systems)