Data-Driven Transportation Research for Decarbonized Freight

I am a doctoral candidate at TUM working at the intersection of agent-based simulation, optimization, and behavioral modelling for freight electrification and automation.

This site highlights my research outputs, applied projects, and professional updates for both academic and industry audiences.

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Shahriar Iqbal Zame

Doctoral Candidate & Research Associate

Chair of Transportation Systems Engineering, Technical University of Munich (TUM)

Biography

I am a Research Associate and PhD Candidate at the Technical University of Munich (TUM), Chair of Transportation Systems Engineering, working on the DFG-funded project SEE-FAr.

My research combines agent-based simulations, optimization, and choice modelling to explore innovative electrification and automation strategies for road freight. With an M.Sc. in Transportation Systems (TUM) and professional experience in large-scale infrastructure projects, I focus on methods that support both policy design and industry decision-making in sustainable logistics.

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Interests

Freight electrification and automation
Agent-based simulation (MATSim)
Optimization & choice modelling
Sustainable urban mobility
High-performance computing

Education

Ph.D. Candidate, Transportation Systems Engineering, 2025 -
Technical University of Munich (TUM)
M.Sc. Transportation Systems, 2021 - 2024
Technical University of Munich (TUM)
B.Sc. Civil & Environmental Engineering, 2014 - 2017
Islamic University of Technology, Bangladesh

Research Impact and Industry Relevance

System-level analysis for freight transition: evaluating electrification and automation pathways under realistic operational constraints.
Decision support: translating simulation and optimization outputs into policy and infrastructure insights.
Applied methods: combining MATSim-based modelling, discrete choice analysis, and data-driven scenario evaluation.

Projects

Selected projects with methodological depth and practical relevance.

Shaping E-Roads Efficiency for Freight Automation (SEE-FAr)

SEE-FAr develops simulation- and optimization-based methods to evaluate freight electrification and automation strategies, with focus on charging infrastructure trade-offs and system-level impacts.

Shahriar Iqbal Zame

Last updated on Aug 5, 2025

Selected Research Outputs

Journal articles, working papers, and thesis outputs

Tao Guo, Hao Wu, Shahriar Iqbal Zame, Constantinos Antoniou (2025). Data-driven vertiport siting: A comparative analysis of clustering methods for Urban Air Mobility. Journal of Urban Mobility, Vol. 7.

PDF DOI

Hao Wu, Shahriar Iqbal Zame, Tao Guo, Qing-Long Lu, Constantinos Antoniou (2025). A sustainable multi-objective framework for multi-phased, capacitated vertiport siting with land use integration. Communications in Transportation Research, Vol. 5.

PDF DOI

Filippos Adamidis, Shahriar Iqbal Zame, Constantinos Antoniou (2024). Developing and testing robust data-driven car-following models. Working paper.

Shahriar Iqbal Zame, Hao Wu, Tao Guo, Constantinos Antoniou (2022). UAM siting approach considering capacity and land use: A case study of Munich. Master’s Thesis, Technical University of Munich.

PDF DOI