Andalib Shams Graduate Research Assistant Civil, Construction, and Environmental Engineering Iowa State University Transportation System Research Assistant AI, Learning and Intelligent Systems Group Computational Science Center National Renewable Energy Lab Phone: 307-223-6666 Email: ashams@iastate.edu CV

Home  ||  Research Experience  ||  Resources

Transportation Systems Research Assistant at National Renewable Energy Lab

Real-Time Data and Simulation for Optimizing Regional Mobility in the United States (a.k.a. “Digital Twin”)

• Developed a framework to implement a previously developed “Model Predictive Control (MPC)” algorithm for signal optimization.
• Emulated sensor inaccuracies in simulation and tested the impact of inaccuracies on signal control.
• Used High-Performance Computing tools (slurm & w/supercomputer Eagle) to estimate fuel consumptions.

Integration of Energy with Electric Vehicle Charging Stations

• Working on developing a framework to integrate discrete event simulator ASPIRE with Large-Scale Co-Simulation software (HELICS) to simulate electric bus movements

EVI-Equity

• Developing a geospatial tool to estimate on-street parking spots for a given City/ County using Python (GeoPandas)
• Exploring spatial relationships among on-street parking spots and demographic parameters

Graduate Research Assistant at Iowa State University

Trajectory-enabled traffic signal controller (Green Box Signal Controller) software

• “Digital twin” of real-world intersection can be modeled to integrate vehicle trajectory data with core signal control logic (similar to a V2I communication). No commercial signal controller can integrate trajectory data explicitly.
• Working on making this signal controller a stand-alone piece to be integrated with any simulation framework or deployed in the field.

New Traffic Signal Actuation Concepts using Advanced Sensor Data

• Working on enhancing actuated control strategies by integrating vehicle trajectory data from advanced sensors (e.g., LiDAR/ RADAR/ Video Camera).
• Implemented several trajectory-based features (elimination of passage time, dilemma zone protection, queue clearance, progression for platoons) in GBSC and performed detailed analysis on performance benefits of each of the methods.

Comparison of Flow- and Bandwidth-Based Methods of Traffic Signal Offset Optimization

• Six flow-based and five bandwidth-based offset optimization methods were compared, and the Hill-climb algorithm or Mixed Integer Linear Programming (MILP) was used to optimize offsets.

Identifying the Performance Potential for Intersection Control using Advanced Infrastructure Sensing

• Implemented and evaluated the performances of actuation-based and dynamic programming-based traffic signal control algorithms.

Graduate Research Assistant at University of Wyoming

• Evaluated operational performances of innovative intersections and transit priority in Redwood Road Corridor at Salt Lake City, Utah. (sponsored by Avenue Consultant)
• Implemented driver behavior model for Connected and Automated Vehicles and evaluated the operational benefits

Briefly worked as a Short-Term Consultant at The World Bank Group (December 2015 - June 2016) and as an Intern at Dhaka Transport Corporation Authority (DTCA) (January 2015 - February 2015)

Journal Publications

1. Shams, A., Mahmud, S., & Day, C. M. (2023). Comparison of Flow-and Bandwidth-Based Methods of Traffic Signal Offset Optimization. Journal of Transportation Engineering, Part A: Systemsi, 149(5), 04023033.
2. Shams, A., & Day, C. M. (2022). Advanced Gap Seeking Logic for Actuated Signal Control Using Vehicle Trajectory Data: Proof of Concept. Transportation Research Record, 2677.2 (2023): 610-623.
3. Yang, Y., Shams, A., & Day, C. (2021). Application of Pareto Front to Evaluate Adaptive Traffic Signal Timing for Multiple Objectives. Journal of Modern Mobility Systems 2.
4. Shams, A., Zlatkovic, M., (2020). Effects of Capacity and Transit Improvements on Traffic and Transit Operations Transportation Planning and Technology, 43:6, 602-619, DOI: 10.1080/03081060.2020.1780710
5. Shams, A., Zlatkovic, M., (2019). Platoon Signal Priority in Connected-Autonomous Vehicle Environments: Algorithm Development and Testing Put I Saobraćaj, 65(4), 1-9. https://doi.org/10.31075/PIS.65.04.01

Conference Proceedings

1. Shams, A., Day, C.M., and Mahmud, S., (2023) Digital Twin of Physical Intersection to Trajectory-based Traffic Signal Controller Presented at IEEE International Automated Vehicle Validation Conference, October 16-18, Austin, TX, United States
2. Mahmud, S., Carydis, M., Shams, A.b, Day, C.M., (2023) Calibration of Robertson’s Platoon Dispersion Model with Connected Vehicle Data Presented at IEEE Intelligent Transportation Systems Conference , September 24-28, Bilbao, Bizkaia, Spain
3. Shams, A., Wang, Q., Ugirumurera, J., Severino, J., & Jones, W. (2023). Impact of Online Traffic Signal Optimization on Operation and Energy Performance. Presented at the International Conference on Transportation & Developmenti>, June 14-17, Austin, TX, United States
4. Shams, A., and Day, C.M. (2021) Impact of Sensing Range on Real-Time Adaptive Control of Signalized Intersections Using Vehicle Trajectory Information Proceedings of the 100th Transportation Research Board Annual Meeting, January 21-29, Virtual Meeting.

Invited Talks

1. Shams, A., Wang, Q., and Ugirumurera, J., (2022) Impact of On-line Traffic Signal Optimization on Operation and Energy Performance. NREL Brown Bag Seminer, October 18, Virtual Meeting.
2. Day, C.M., and Shams, A. (2022) Concept of Operations for Trajectory-Based Actuation. Mid-Continent Transportation Research Symposium, September 14, Ames, IA.
3. Shams, A., and Day, C.M. (2021 Vehicle Trajectory based Advanced Gap Seeking Logic for Actuated Signal Control: Proof of Concept PTV User Group Meeting, November 10, Atlanta, GA.
4. Shams, A., and Day, C.M. (2021) Impact of Sensing Range on Real-Time Adaptive Control of Signalized Intersections Using Vehicle Trajectory Information PTV Student Talk 2021, March 17, Virtual Meeting.

Papers Under Review

1. Shams, A., Emtenan, A. M .T., and Day, C.M.; A Taxonomy of Adaptive Traffic Signal Control Manuscript under review at IEEE Transactions on Intelligent Transportation Systems
2. Shams, A., Wang, Q., Ugirumurera, J., Severino, J., and Jones, W., Sanayal, J.; Simulation Evaluation of a Large-scale Implementation of Virtual-Phase Link based Model Predictive Control Accepted for presentations at 103rd Transportation Research Board Annual Meeting [For publication: manuscript under review at Journal of Transportation Engineering Part A: Systems]
3. Shams, A., Dobrota, N., Cesme, B., and Day, C.M.; Integration of Real-Time Vehicle Trajectories into Actuated Traffic Signals to Improve Local Intersection and Arterial Control Accepted for presentations at 103rd Transportation Research Board Annual Meeting [For publication: manuscript under review]

Journal Referee Services

1. Reviewer, Transportation Research Record
2. Reviewer, Journal of Transportation Engineering Part A: Systems
3. Reviewer, Transportation Research Board Annual Meeting Conference
4. Reviewer, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations
5. Reviewer, Journal of Transportation Planning and Technology
6. Reviewer, IEEE Transactions on Intelligent Transportation Systems

Memberships

1. Student Member, American Society of Civil Engineers
2. Student Member, Institute of Transportation Engineers

Awards

1. ITS Minnesota Graduate Student Scholarship, 2021
2. Bangladesh-Sweden trust fund travel grant, Govt. of the People’s Republic of Bangladesh, 2018

Last updated October 19, 2022