TransAnalytics Researchers Awarded Project to Explore Use of LiDAR Data and Machine Learning to Monitor Pavement Markings

The research team will investigate innovative approaches using machine learning to leverage large datasets from LiDAR and measure retroreflectivity from pavement markings. Outcomes from this project are expected to support monitoring programs to assess roadway maintenance and meet requirements from FHWA. This project is sponsored by the Utah DOT and will be executed in Fall/23.

TransAnalytics research awarded funding from the National Science Foundation

A new project is awarded to TransAnalytics from the NSF. The project is titled: Integrating and Learning on Spatial Data via Multi-Agent Simulation. This project will build metro-scale foundation models for studying human mobility and will allow social-technical spatial scientists to compare against and study human mobility in aggregate and at scale. Exemplar studies will address EV charging, and fair traffic policing. The project will train next-generation spatial scientists at the interface of civil engineering and data science. Details of the project can be found at: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311954&HistoricalAwards=false

New journal articles published by the TransAnalytics researchers

Over the past several months, the TransAnalytics researchers have published a series of journal articles in different fields, ranging from electrified mobility, transportation-energy modeling, racial segregation, to compter vision applications. See below for the list of our recent publications, and check our Publications section for details!

X. Liu, X. Liu, C. Xie & X. Ma (2023). Impacts of photovoltaic and energy storage system adoption on public transport: A simulation-based optimization approach. Renewable and Sustainable Energy Reviews. Vol. 181.

Y. Zhou, R. Wei, X. Liu, D. Wallace & T. Grubesic (2023). Delineating race-specific driving patterns for identifying racial segregation. Transportation Research Part D: Transport and Environment. Vol. 119.

X. Liu, X. Liu, Z. Liu, R. Shi & X. Ma (2023). A solar-powered bus charging infrastructure location problem under charging service degradation. Transportation Research Part D: Transport and Environment. Vol. 119.

Z. Yi, B. Chen, X. Liu, R. Wei, J. Chen & Z. Chen (2023). An agent-based modeling approach for public charging demand estimation and charging station location optimization at urban scale. Computers, Environment and Urban Systems. Vol. 101.

D. Wallace, E. Helderop, T. Grubesic, J. Walker, X. Liu, R. Wei, Y. Zhou & C. Stewart (2023). A two-step process to increase successful geocoding in publicly available police stop data. Police Practice and Research. 1-7.

Rahman, M. H., Chen, S., Sun, Y., Siddiqui, M. I. Y., Mohebbi, M., & Marković, N. (2023). Integrating dial-a-ride with transportation network companies for cost efficiency: A Maryland case study. Transportation Research Part E: Logistics and Transportation Review, 175, 103140.

Farhadmanesh, M., Marković, N., & Rashidi, A. (2023). Automated video-based air traffic surveillance system for counting general aviation aircraft operations at non-towered airports. Transportation research record, 2677(3), 250-273.

Z. Dai, X. Liu, H. Li, M. Wang & X. Ma (2022). Semi-autonomous bus platooning service optimization with surrogate modeling. Computer & Industrial Engineering.

X. Liu, X.C. Liu, X. Zhang, Y. Zhou, J. Chen & X. Ma (2022). Optimal Location Planning of Electric Bus Charging Stations with Integrated Photovoltaic and Energy Storage System. Computer-aided civil & infrastructure engineering.

Z. Ye, N. Yu, R. Wei & X.C. Liu (2022). Decarbonizing Regional Multi-modal Transportation System With Shared Electric Charging Hub. Transportation Research Part C: Emerging Technologies. Vol. 144.

Farhadmanesh, M., Rashidi, A., & Marković, N. (2022). General Aviation Aircraft Identification at Non-Towered Airports Using a Two-Step Computer Vision-Based Approach. IEEE Access, 10, 48778-48791.

Sheibani, M., Wang, Y., Ou, G., & Marković, N. (2022). Efficient Structural Reconnaissance Surveying for Regional Postseismic Damage Inference with Optimal Inspection Scheduling. Journal of Engineering Mechanics, 148(2), 04021156.

Chen, Y., Marković, N., Ryzhov, I. O., & Schonfeld, P. (2022). Data-driven robust resource allocation with monotonic cost functions. Operations Research, 70(1), 73-94.

TransAnalytics received funding from the Department of Energy

TransAnalytics researcher is part of the team led by the Utah State University to receive funding from the DOE for zero-emission medium- and heavy duty vehicle corridors. The project is titled the Wasatch Front Multimodal Corridor Electrification Plan, and plans to develop a community, state and industry action plan to improve air quality in communities most impacted by high-density traffic in the greater Salt Lake City region.

TransAnalytics faculty awarded the TSL Best Paper Award

Nikola Marković, a faculty member at TransAnalytics, was honored with the prestigious 2022 TSL Best Paper Award at the annual INFORMS conference. The award recognizes exceptional contributions to the field of transportation science and logistics. Marković's paper, titled "Robust resource allocation for monotonic cost functions," was published in Operations Research and presents a groundbreaking methodological framework for robust optimization—a rapidly evolving field.

TransAnalytics student awarded competitive scholarship

Yirong Zhou, a Ph.D. candidate working at TransAnalytics, was recently awarded a scholarship from the Utah Institute of Transportation Engineers. Winners of the $500 scholarships are selected based on outstanding scholarship, work experience, and activity within their student section of ITE. Yirong’s research focuses on data-driven transportation engineering, including operation research, optimization, machine learning, and spatiotemporal analysis and simulation. Congratulations to Yirong!

TransAnalytics granted FTA AoPP project

TransAnalytics researchers are awarded grant from the Federal Transit Administration’s Areas of Persistent Poverty (AoPP) Program. The program supports the President’s initiatives to mobilize American ingenuity to build modern infrastructure and an equitable, clean energy future. The project, named, Paratransit Forward Study, aims to improve the customer experience and cost-effectiveness of Utah Transit Authority (UTA)’s paratransit services for customers with disabilities who are often below the poverty line.

TransAnalytics researcher is awarded funding from Seed2Soil

A new project is awarded to TransAnalytics titled “Telematic Data for Fleet Vehicles: A Data-Driven Solution Towards Optimal Fleet Management and Clean Vehicle Adoption”. The SEED2SOIL program brings together experts and stakeholders along with operational sustainability topics to expand, prioritize, and refine known opportunities for carbon reduction. More info can be found at: https://facilities.utah.edu/se/seed2soil/index.php. The project aims to offer strategic solutions for efficient fleet service management by using telematic data to examine the performance of the fleet operating system. It further introduces a web-based visualization tool that incorporates performance metrics along with the geospatial locations of the vehicles. The deployed version of this tool is available at https://sparkling-klepon-14f37e.netlify.app.

New journal articles published by the TransAnalytics researchers

Over the past several months, the TransAnalytics researchers have published a series of journal articles in different fields, ranging from microtransit, electrified transportation, to data-driven driver behavior modeling, safety analysis, robust optimization and postseismic reconnaissance. See below for the list of our recent publications, and check our Publications section for details!

Himes, J. Bonneson, V. Gayah, X.C. Liu. “Safety prediction method for freeway facilities with high occupancy lanes. Transportation Research Record, 2022. https://doi.org/10.1177/03611981221083918

Z. Yi, X.C. Liu, and R. Wei. “Electric vehicle demand estimation and charging station allocation using urban informatics”. Transportation Research Part D: Transport and Environment, Vol 106, 2022.

Y. Zhou, J. Medina, J. Taylor, X. C. Liu. “Empirical Verification of Car-Following Parameters Using Naturalistic Driving Data on Freeway Segments”. Journal of Transportation Engineering, Part A: Systems, 148(2), 2022.

Y. Zhou, X.C. Liu, and T. Grubesic. “Unravel the impact of COVID-19 on the spatio-temporal mobility patterns of microtransit”. Journal of Transport Geography, 97, 103226, 2022.

Chen, Y., Marković, N., Ryzhov, I. O., & Schonfeld, P. “Data-Driven Robust Resource Allocation with Monotonic Cost Functions”. Operations Research, 70(1), 73-94, 2022.

Sheibani, M., Wang, Y., Ou, G., & Marković, N. “Efficient Structural Reconnaissance Surveying for Regional Postseismic Damage Inference with Optimal Inspection Scheduling”. Journal of Engineering Mechanics, 148(2), 04021156, 2022.

Azin, B., Yang, X. T., Marković, N., & Liu, M. “Infrastructure enabled and electrified automation: Charging facility planning for cleaner smart mobility”. Transportation Research Part D: Transport and Environment, 101, 10307, 2021.

TransAnalytics redesigns snowplow routes in Utah

A TransAnalytics graduate student, Yinhu Wang, has successfully completed a project concerned with optimizing snowplow routes in Northern Utah. Compared to the original routes, Yinhu’s routes reduced the turnaround time by 15% on average.
Check out the youtube video for the cool work.

TransAnalytics’ research featured in NITC

NITC (National Institute for Transporation and Communities), a U.S. DOT Transportation Center, featured our TransAnalytics research in its recent newsletter. Come check out the details of our work in the space of electrified transportation and urban mobility modeling. Check out the details.

Congratulations to Zhiyan Yi for passing his dissertation proposal defense

TransAnalytics researcher Zhiyan Yi successfully passed his proposal defense, titled “Public Electric Vehicle Charging Demand Estimation – A Comprehensive Data-Driven Approach from Macroscopic to Microscopic”. The work explores the public EV charging behaviors from both macroscopic and microscopic perspectives, and serves several meaningful purposes for future study with respect to urban planning and energy planning. Zhiyan has accumulated a significant amount of track records and publications in this space, and his expertise includes machine learning, data science, urban mobility modeling and visualization. Congratulations to Zhiyan and we look forward to your final dissertation defense in a couple of months!

Deep Learning Certificate Program sponsored by the Utah System of Higher Education

TransAnalytics researchers joined forces with the School of Computing at the University of Utah in developing a deep learning certificate program that provides a working knowledge of the use of state-of-the-art deep learning technology to engineering students beyond those with computing background. Several of our graduate courses offered by the TransAnalytics groups are counted towards the core courses of the certificate program. For more information, please check the program flyer and contact us for details.

Congratulations to Kai for a successful thesis defense

TransAnalytics researcher Kian Kai Chee successfully defended his Master’s thesis titled “Exploration of Relationships between Citation Event Data and Crash Records on Utah Freeways”. The study explored the relationship between citation records, as a measure of enforcement exposure and crash data. Upon graduation, Kai joined BHB Engineers as a Project Engineer. Congratulations to Kai and we wish you all the best in your future endeavors!

New NITC grants on older adults’ accessibility and electric bus deployment visualization

TransAnalytics researchers are awarded two grants by the National Institute for Transportation and Communities (NITC). One project is titled “Transportation for Seniors (T4S): Developing a New Accessibility Measure to Support Older Adults in a Post-Pandemic World”, and the other one is titled “Enable Decision Making for Battery Electric Bus Deployment using Robust High-Resolution Interdependent Visualization”. The projects will help decision makers integrate equity and new technologies into the future policy framework.

New paper published on electric vehicles

TransAnalytics researchers have a new paper published on electric vehicle in Journal of Intelligent Transportation Systems: Technology, Planning, and Operations. The paper uses a deep learning approach - Sequence to Sequence (Seq2Seq) to forecast the monthly commercial EV charging demand.

New NSF grant on improving paratransit systems

TransAnalytics researchers are collaborating with two Historically Black Universities and Colleges on improving transportation systems for transportation-disadvantaged people. The study will focus on developing mechanisms for collaboration between independent paratransit service providers, similar to the code-share arrangements that exist in the airlines industry.

New NSF grant on improving post-earthquake reconnaissance missions

TransAnalytics researchers received an NSF grant to develop optimal learning theory that accounts for resource constraints, which naturally arise in field information collection. The developed methodology is expected to speed up the post-earthquake reconnaissance by more efficiently guiding inspection teams through their mission.