Narayana Raju

About

Narayana Raju, Ph.D. is presently working as a postdoctoral researcher in TU Delft, The Netherlands. His research primarily focuses on traffic flow modeling, microscopic traffic simulation, flow theory safety analytics, traffic stability, etc. in connection to autonomous vehicles. Before joining TU Delft, he was a postdoctoral researcher at Ryerson University, Canada supported by MITACS Global Research Grant. During this, he focused on safety analytics with the help of deep learning. Narayana completed his doctoral research from SVNIT, India on driving behavior under heterogeneous traffic in the Indian context with the help of vehicular trajectory data.

Employment

• Delft University of Technology (TU Delft) Post Doc
  2020 - Present
• Toronto Metropolitan University Post Doc
  2020 - 2020
• Sardar Vallabhbhai National Institute of Technology Project Associate
  2016 - 2016

Education

• Sardar Vallabhbhai National Institute of Technology Ph.D.
  2016 - 2019
• Sardar Vallabhbhai National Institute of Technology M.Tech.
  2014 - 2016
• VNR Vignana Jyothi College of Engineering and Technology B.Tech.
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (45)

• Incorporating Behavioral Adaptation of Human Drivers in Predicting Traffic Efficiency of Mixed Traffic
  European Journal of Transport and Infrastructure Research 2025 DOI: 10.59490/ejtir.2025.25.2.7557
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• Understanding cyclists’ perception of driverless vehicles through eye-tracking and interviews
  Transportation Research Part F: Traffic Psychology and Behaviour 2025 DOI: 10.1016/j.trf.2024.11.015
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• Exploring the Impact of Car-Following Models and Controller Formulations on Autonomous Vehicle Motion Planning
  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 2025 DOI: 10.1061/AJRUA6.RUENG-1595
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• Influence of Behavioural Model Formulation on Surrogate Safety Measures in Traffic Microsimulation
  102nd Annual Meeting of the Transportation Research Board (TRB), Washington, United States, 8/01/23 2023
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• Receptiveness angle
  IATSS Research 2023 DOI: 10.1016/j.iatssr.2023.11.004
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• Modeling Automated Driving in Microscopic Traffic Simulations for Traffic Performance Evaluations: Aspects to Consider and State of the Practice
  IEEE Transactions on Intelligent Transportation Systems 2022 DOI: 10.1109/tits.2022.3200176
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• Proposed Empirical Approach to Measuring Traffic String Stability
  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 2022 DOI: 10.1061/AJRUA6.0001227
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• Experimental Design for Measuring Operational Performance of Truck Parking Terminal Using Simulation Technique
  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 2022 DOI: 10.1061/AJRUA6.0001275
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• Empirical approach for identifying potential rear-end collisions using trajectory data
  Journal of Transportation Safety and Security 2022 DOI: 10.1080/19439962.2021.1919261
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• Data-Driven Approach for Modeling the Nonlane-Based Mixed Traffic Conditions
  Journal of Advanced Transportation 2022 DOI: 10.1155/2022/6482326
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