Award Abstract # 2152258
Science to Policy Education: Activating Knowledge for Sustainable Transportation (SPEAKS)
NSF Org: |
DGE
Division Of Graduate Education
|
Recipient: |
REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE
|
Initial Amendment Date:
|
June 24, 2022 |
Latest Amendment Date:
|
June 24, 2022 |
Award Number: |
2152258 |
Award Instrument: |
Standard Grant |
Program Manager: |
Liz Webber
ewebber@nsf.gov
(703)292-4316
DGE
Division Of Graduate Education
EDU
Directorate for STEM Education
|
Start Date: |
July 1, 2022 |
End Date: |
June 30, 2027 (Estimated) |
Total Intended Award
Amount: |
$3,000,000.00 |
Total Awarded Amount to
Date: |
$3,000,000.00 |
Funds Obligated to Date:
|
FY 2022 = $3,000,000.00
|
History of Investigator:
|
-
Matthew
Barth
(Principal Investigator)
barth@cert.ucr.edu
-
Jan
Stets
(Co-Principal Investigator)
-
Kevin
Esterling
(Co-Principal Investigator)
-
Amir-Hamed
Mohsenian-Rad
(Co-Principal Investigator)
-
Susan
Hackwood
(Co-Principal Investigator)
|
Recipient Sponsored Research
Office: |
University of California-Riverside
200 UNIVERSTY OFC BUILDING
RIVERSIDE
CA
US
92521-0001
(951)827-5535
|
Sponsor Congressional
District: |
39
|
Primary Place of
Performance: |
University of California at Riverside
900 University Avenue
Riverside
CA
US
92501-0001
|
Primary Place of
Performance Congressional District: |
39
|
Unique Entity Identifier
(UEI): |
MR5QC5FCAVH5
|
Parent UEI: |
|
NSF Program(s): |
NSF Research Traineeship (NRT)
|
Primary Program Source:
|
04002223DB NSF Education & Human Resource
|
Program Reference
Code(s): |
090Z,
SMET,
9179,
063Z
|
Program Element Code(s):
|
199700
|
Award Agency Code: |
4900
|
Fund Agency Code: |
4900
|
Assistance Listing
Number(s): |
47.076
|
ABSTRACT

As society looks increasingly to scientific advances for solutions to major challenges, researchers must engage with the public and policymakers to develop and implement new technologies based on those advances to benefit society. For example, such engagement is essential to address climate change, as people and industries must quickly and equitably embrace renewable energy sources and sustainably powered vehicles and technologies. This NSF Research Traineeship (NRT) project will train STEM graduate students to integrate engineering, social and environmental science, and public policy to conduct research focused on accelerating the integration of renewable energy into the electric grid, taking advantage of renewable hydrogen and different energy storage capabilities. Such integration will ultimately help accelerate the decarbonization of transportation and other sectors. This project will use a novel science-to-policy (S2P) training program to teach students to engage stakeholder groups and understand and incorporate their needs into research programs while communicating the science, and prioritizing attention to diversity, equity, inclusion, and ethics. This project anticipates training eighty (80) Ph.D. students, including thirty (30) funded trainees, from different engineering programs, environmental sciences, sociology, and political science. Funded trainees will intern in legislative offices, government agencies, non-profits, and industry for hands-on career preparation with a tangible product, such as a policy recommendation or report. This project will convene expert practitioners from these areas to teach students and participate in research projects. Project faculty and researchers from engineering, policy, sciences, and humanities will implement an interdisciplinary training program providing Ph.D. students skills and experience necessary to address key scientific challenges to transportation decarbonization and to implement their findings in public policy. Faculty will also work with campus leadership to integrate elements of the S2P training program in campus-wide introductory graduate courses and collaborate with the National Science Policy Network to share this training program nationally. This training program is the first step in transforming STEM graduate education to better prepare students for any career and to translate societally beneficial research into public policy.
Accelerating decarbonization of the transportation sector while continuing to integrate renewables into the electric grid is critical to address climate change. Towards this goal NRT trainees will pursue three key activities. First is to conduct cutting-edge research in integrating the high renewables electric grid with transportation infrastructure, investigating renewable hydrogen as a fuel and energy storage medium. Second is to understand policies around sustainability, air pollution, and renewable energy, learn to communicate science to all audiences, and appreciate the needs of various stakeholders to create equitable solutions for environmental justice. Third is to develop best practices for human interaction with renewable energy technology by designing solutions based on individual, societal, and political needs. Engaging key stakeholder groups during research and development will accelerate the deployment of renewable technologies and foster effective communication and decision-making on scientific topics. This project will prepare trainees to develop and deploy a model for scientific research that is closely connected with societal challenges through meaningful community engagement and responsive programs.
The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 58)
(Showing: 1 - 58 of 58)
Bai, Zhengwei and Hao, Peng and ShangGuan, Wei and Cai, Baigen and Barth, Matthew J.
"Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections"
IEEE Transactions on Intelligent Transportation Systems
, v.23
, 2022
https://doi.org/10.1109/TITS.2022.3145798
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Bai, Zhengwei and Nayak, Saswat P and Zhao, Xuanpeng and Wu, Guoyuan and Barth, Matthew J and Qi, Xuewei and Liu, Yongkang and Sisbot, Emrah Akin and Oguchi, Kentaro
"Cyber Mobility Mirror: A Deep Learning-Based Real-World Object Perception Platform Using Roadside LiDAR"
IEEE Transactions on Intelligent Transportation Systems
, v.24
, 2023
https://doi.org/10.1109/TITS.2023.3268281
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Bai, Zhengwei and Wu, Guoyuan and Barth, Matthew J and Liu, Yongkang and Akin_Sisbot, Emrah and Oguchi, Kentaro and Huang, Zhitong
"A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation"
IEEE Transactions on Intelligent Transportation Systems
, v.25
, 2024
https://doi.org/10.1109/TITS.2024.3436012
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Bai, Zhengwei and Wu, Guoyuan and Barth, Matthew J and Liu, Yongkang and Sisbot, Emrah Akin and Oguchi, Kentaro
"VINet: Lightweight, scalable, and heterogeneous cooperative perception for 3D object detection"
Mechanical Systems and Signal Processing
, v.204
, 2023
https://doi.org/10.1016/j.ymssp.2023.110723
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Bai, Zhengwei and Wu, Guoyuan and Barth, Matthew J and Qiu, Hang and Liu, Yongkang and Sisbot, Emrah Akin and Oguchi, Kentaro
"Pillar Attention Encoder for Adaptive Cooperative Perception"
IEEE Internet of Things Journal
, 2024
https://doi.org/10.1109/JIOT.2024.3390552
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Chen, L-W Antony and Wang, Xiaoliang and Lopez, Brenda and Wu, Guoyuan and Ho, Steven_Sai Hang and Chow, Judith C and Watson, John G and Yao, Qi and Yoon, Seungju and Jung, Heejung
"Contributions of non-tailpipe emissions to near-road PM2.5 and PM10: A chemical mass balance study"
Environmental Pollution
, v.335
, 2023
https://doi.org/10.1016/j.envpol.2023.122283
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Dong, Haoxuan and Zhuang, Weichao and Wu, Guoyuan and Li, Zhaojian and Yin, Guodong and Song, Ziyou
"Overtaking-Enabled Eco-Approach Control at Signalized Intersections for Connected and Automated Vehicles"
IEEE Transactions on Intelligent Transportation Systems
, v.25
, 2024
https://doi.org/10.1109/TITS.2023.3328022
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Ehsani, Narges and Ahmadi-Gorjayi, Fatemeh and Ye, Zong-Jhen and McEachern, Alex and Mohsenian-Rad, Hamed
"Sub-Cycle Event Detection and Characterization in Continuous Streaming of Synchro-Waveforms: An Experiment Based on GridSweep Measurements"
, 2023
https://doi.org/10.1109/NAPS58826.2023.10318763
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Fang, Shan and Yang, Lan and Zhao, Xiangmo and Wang, Wei and Xu, Zhigang and Wu, Guoyuan and Liu, Yang and Qu, Xiaobo
"A Dynamic Transformation Car-Following Model for the Prediction of the Traffic Flow Oscillation"
IEEE Intelligent Transportation Systems Magazine
, v.16
, 2024
https://doi.org/10.1109/MITS.2023.3317081
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Fernando Enriquez-Contreras, Luis and Jahid Hasan, A S and Yusuf, Jubair and Garrido, Jacqueline and Ula, Sadrul
"Microgrid Demand Response: A Comparison of Simulated and Real Results"
Proceedings Article published 9 Oct 2022 in 2022 North American Power Symposium (NAPS)
, 2022
https://doi.org/10.1109/NAPS56150.2022.10012248
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Garrido, Jacqueline and Hidalgo, Emmanuel and Barth, Matthew and Boriboonsomsin, Kanok
"En-Route Opportunity Charging for Heavy-Duty Battery Electric Trucks in Drayage Operations: Case Study at the Southern California Ports"
Proceedings Article published Nov 2022 in 2022 IEEE Vehicle Power and Propulsion Conference (VPPC)
, 2022
https://doi.org/10.1109/VPPC55846.2022.10003273
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Garrido, Jacqueline and Hidalgo, Emmanuel and Barth, Matthew J and Boriboonsomsin, Kanok
"An Intelligently Controlled Charging Model for Battery Electric Trucks in Drayage Operations"
IEEE Transactions on Vehicular Technology
, v.73
, 2024
https://doi.org/10.1109/TVT.2023.3347730
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Details
Gonzalez, Emmanuel Hidalgo and Garrido, Jacqueline and Barth, Matthew and Boriboonsomsin, Kanok
"Comparative Assessment of Machine Learning Techniques for Modeling Energy Consumption of Heavy-Duty Battery Electric Trucks"
, 2024
https://doi.org/10.1109/FISTS60717.2024.10485539
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Hu, Jia and Li, Shuoyuan and Wang, Haoran and Wang, Ziran and Barth, Matthew J
"Eco-approach at an isolated actuated signalized intersection: Aware of the passing time window"
Journal of Cleaner Production
, v.435
, 2024
https://doi.org/10.1016/j.jclepro.2023.140493
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Hurren, Troy and Durbin, Thomas D and Johnson, Kent C and Karavalakis, Georgios
"The impacts of improving heavy-duty internal combustion engine technology on reducing NOx emissions inventories going into the future"
Science of The Total Environment
, v.986
, 2025
https://doi.org/10.1016/j.scitotenv.2025.179781
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Hussein, Ahmed and Barth, Matthew
"IEEE Intelligent Transportation Systems Society Outreach Committee: Bridging Connections and Fostering Engagement [Society News]"
IEEE Intelligent Transportation Systems Magazine
, v.16
, 2024
https://doi.org/10.1109/MITS.2024.3428896
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Liao, Xishun and Wu, Guoyuan and Yang, Lan and Barth, Matthew J.
"A Real-World Data-Driven approach for estimating environmental impacts of traffic accidents"
Transportation Research Part D: Transport and Environment
, v.117
, 2023
https://doi.org/10.1016/j.trd.2023.103664
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Liao, Xishun and Zhao, Xuanpeng and Wang, Ziran and Zhao, Zhouqiao and Han, Kyungtae and Gupta, Rohit and Barth, Matthew J and Wu, Guoyuan
"Driver Digital Twin for Online Prediction of Personalized Lane-Change Behavior"
IEEE Internet of Things Journal
, v.10
, 2023
https://doi.org/10.1109/JIOT.2023.3262484
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Liao, Xishun and Zhao, Zhouqiao and Barth, Matthew J and Abdelraouf, Amr and Gupta, Rohit and Han, Kyungtae and Ma, Jiaqi and Wu, Guoyuan
"A Review of Personalization in Driving Behavior: Dataset, Modeling, and Validation"
IEEE Transactions on Intelligent Vehicles
, 2024
https://doi.org/10.1109/TIV.2024.3425647
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Liao, Yejia and Liu, Haishan and Yao, Ruili and Wu, Guoyuan and Barth, Matthew J and Huang, Zhitong and Osman, Osama and Hourdos, John and McHale, Gene
"Analysis, Modeling, and Simulation of Connected and Automated Trucks: State-of-the-Art and Identified Gaps"
Transportation Research Record: Journal of the Transportation Research Board
, 2025
https://doi.org/10.1177/03611981241306750
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Li, Siyan and Wei, Chuheng and Wu, Guoyuan and Barth, Matthew J and Abdelraouf, Amr and Gupta, Rohit and Han, Kyungtae
"Personalized Trajectory Prediction for Driving Behavior Modeling in Ramp-Merging Scenarios"
, 2023
https://doi.org/10.1109/IRC59093.2023.00054
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Details
Liu, Haishan and Hao, Peng and Barth, Matthew
"Evaluation of Mixed Electric Fleet for Ride-Hailing Services under California's Clean Miles Standard: A Case Study in San Francisco"
, 2024
https://doi.org/10.1109/FISTS60717.2024.10485541
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Liu, Haishan and Hao, Peng and Liao, Yejia and Boriboonsomsin, Kanok and Barth, Matthew
"Model-Based Vehicle-Miles Traveled and Emission Evaluation of On-Demand Food Delivery Considering the Impact of COVID-19 Pandemic"
Transportation Research Record: Journal of the Transportation Research Board
, 2023
https://doi.org/10.1177/03611981231169276
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Liu, Haishan and Hao, Peng and Liao, Yejia and Tanvir, Shams and Boriboonsomsin, Kanok and Barth, Matthew J
"Eco-Friendly Crowdsourced Meal Delivery: A Dynamic On-Demand Meal Delivery System with a Mixed Fleet of Electric and Gasoline Vehicles"
IEEE Transactions on Intelligent Transportation Systems
, 2024
https://doi.org/10.1109/TITS.2024.3367621
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Liu, Haishan and Hao, Peng and Tanvir, Shams and Pande, Anurag and Barth, Matthew
"Vehicle Miles Traveled and Environmental Impacts from On-Demand Delivery: A Literature Review"
, 2024
https://doi.org/10.1061/9780784485521.004
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Liu, Haishan and Liao, Yejia and Hao, Peng and Boriboonsomsin, Kanok and Barth, Matthew
"Evaluating the Order Dispatching Strategies for a Dynamic On-Demand Meal Delivery SystemA Case Study in the City of Riverside"
Proceedings Article published 13 Jun 2023 in International Conference on Transportation and Development 2023
, 2023
https://doi.org/10.1061/9780784484883.043
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Li, Weixia and Dong, Zhurong and Miao, Ling and Wu, Guoyuan and Deng, Zhijun and Zhao, Jianfeng and Huang, Wenwei
"On-road evaluation and regulatory recommendations for NOx and particle number emissions of China VI heavy-duty diesel trucks: A case study in Shenzhen"
Science of The Total Environment
, v.928
, 2024
https://doi.org/10.1016/j.scitotenv.2024.172427
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Mohsenian-Rad, Hamed and Xu, Wilsun
"Synchro-Waveforms: A Window to the Future of Power Systems Data Analytics"
IEEE Power and Energy Magazine
, v.21
, 2023
https://doi.org/10.1109/MPE.2023.3288583
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Oswald, David and Escobar, Jacqueline and Wu, Guoyuan and Jung, Heejung and Barth, Matthew
"Electric Vehicle Modeling: Advanced Torque Split Analysis across Different Architectures"
, 2024
https://doi.org/10.4271/2024-01-2166
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Peng, Dongbo and Barth, Matthew and Boriboonsomsin, Kanok
"Addressing the Robust Battery Electric Truck Dispatching Problem with Backhauls and Time Windows Under Travel Time Uncertainty"
, 2024
https://doi.org/10.1109/ITSC58415.2024.10919697
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Peng, Dongbo and Wu, Guoyuan and Boriboonsomsin, Kanok
"Bi-Objective Battery Electric Truck Dispatching Problem with Backhauls and Time Windows"
Transportation Research Record: Journal of the Transportation Research Board
, v.2678
, 2024
https://doi.org/10.1177/03611981241246270
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Peng, Dongbo and Wu, Guoyuan and Boriboonsomsin, Kanok
"Energy-Efficient Dispatching of Battery Electric Truck Fleets with Backhauls and Time Windows"
SAE International Journal of Electrified Vehicles
, v.13
, 2024
https://doi.org/10.4271/14-13-01-0009
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Qin, Ziye and Ji, Ang and Sun, Zhanbo and Wu, Guoyuan and Hao, Peng and Liao, Xishun
"Game Theoretic Application to Intersection Management: A Literature Review"
IEEE Transactions on Intelligent Vehicles
, 2024
https://doi.org/10.1109/TIV.2024.3379986
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Details
Shang, Wen-Long and Zhang, Mengxiao and Wu, Guoyuan and Yang, Lan and Fang, Shan and Ochieng, Washington
"Estimation of traffic energy consumption based on macro-micro modelling with sparse data from Connected and Automated Vehicles"
Applied Energy
, v.351
, 2023
https://doi.org/10.1016/j.apenergy.2023.121916
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Shan, Xiaonian and Wan, Changxin and Hao, Peng and Wu, Guoyuan and Barth, Matthew J
"Developing A Novel Dynamic Bus Lane Control Strategy With Eco-Driving Under Partially Connected Vehicle Environment"
IEEE Transactions on Intelligent Transportation Systems
, 2024
https://doi.org/10.1109/TITS.2023.3336895
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Details
Un-Noor, Fuad and Vu, Alexander and Tanvir, Shams and Gao, Zhiming and Barth, Matt and Boriboonsomsin, Kanok
"Range Extension of Battery Electric Trucks in Drayage Operations with Wireless Opportunity Charging at Port Terminals"
Proceedings Article published Nov 2022 in 2022 IEEE Vehicle Power and Propulsion Conference (VPPC)
, 2022
https://doi.org/10.1109/VPPC55846.2022.10003392
Citation
Details
Un-Noor, Fuad and Vu, Alexander and Tanvir, Shams and Gao, Zhiming and Barth, Matthew and Boriboonsomsin, Kanok
"Application of Wireless Charging at Seaports for Range Extension of Drayage Battery Electric Trucks"
IEEE Transactions on Vehicular Technology
, v.73
, 2024
https://doi.org/10.1109/TVT.2023.3344213
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Details
Un-Noor, Fuad and Wu, Guoyuan and Perugu, Harikishan and Collier, Sonya and Yoon, Seungju and Barth, Mathew and Boriboonsomsin, Kanok
"Off-Road Construction and Agricultural Equipment Electrification: Review, Challenges, and Opportunities"
Vehicles
, v.4
, 2022
https://doi.org/10.3390/vehicles4030044
Citation
Details
Wan, Changxin and Shan, Xiaonian and Hao, Peng and Wu, Guoyuan
"Multi-objective coordinated control strategy for mixed traffic with partially connected and automated vehicles in urban corridors"
Physica A: Statistical Mechanics and its Applications
, v.635
, 2024
https://doi.org/10.1016/j.physa.2023.129485
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Details
Wang, Chao and Hao, Peng and Boriboonsomsin, Kanok and Barth, Matthew
"Developing a Mesoscopic Energy Consumption Model for Battery Electric Trucks Using Real-World Diesel Truck Driving Data"
Proceedings Article published Nov 2022 in 2022 IEEE Vehicle Power and Propulsion Conference (VPPC)
, 2022
https://doi.org/10.1109/VPPC55846.2022.10003335
Citation
Details
Wei, Chuheng and Qin, Ziye and Wu, Guoyuan and Barth, Matthew J and Abdelraouf, Amr and Gupta, Rohit and Han, Kyungtae
"Dilemma Zone: A Comprehensive Study of Influential Factors and Behavior Analysis"
, 2024
https://doi.org/10.1109/FISTS60717.2024.10485546
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Details
Wei, Chuheng and Qin, Ziye and Wu, Guoyuan and Barth, Matthew J and Sun, Zhanbo
"Cost-Efficient Driver Distraction Detection System: Transformer-Based Classification on Bayer Image"
, 2024
https://doi.org/10.1061/9780784485484.012
Citation
Details
Wei, Chuheng and Wu, Guoyuan and Barth, Matthew and Chan, Pak Hung and Donzella, Valentina and Huggett, Anthony
"Enhanced Object Detection by Integrating Camera Parameters into Raw Image-Based Faster R-CNN"
, 2023
https://doi.org/10.1109/ITSC57777.2023.10422473
Citation
Details
Wei, Chuheng and Wu, Guoyuan and Barth, Matthew J
"Feature Corrective Transfer Learning: End-to-End Solutions to Object Detection in Non-Ideal Visual Conditions"
, 2024
https://doi.org/10.1109/cvprw63382.2024.00007
Citation
Details
Wei, Chuheng and Wu, Guoyuan and Barth, Matthew J
"RAF-RCNN: Adaptive Feature Transfer from Clear to Rainy Conditions for Improved Object Detection"
, 2024
https://doi.org/10.1109/ITSC58415.2024.10920096
Citation
Details
Wei, Chuheng and Wu, Guoyuan and Barth, Matthew J and Abdelraouf, Amr and Gupta, Rohit and Han, Kyungtae
"KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersections"
, 2024
https://doi.org/10.1109/cvprw63382.2024.00706
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Details
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"Computationally Efficient Approach for Evaluating Eco-Approach and Departure for Heavy-Duty Trucks"
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, v.2678
, 2024
https://doi.org/10.1177/03611981241254112
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Details
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https://doi.org/10.1109/ITSC58415.2024.10919581
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Details
Yusuf, Jubair and Hasan, A S and Garrido, Jacqueline and Ula, Sadrul and Barth, Matthew J.
"A comparative techno-economic assessment of bidirectional heavy duty and light duty plug-in electric vehicles operation: A case study"
Sustainable Cities and Society
, v.95
, 2023
https://doi.org/10.1016/j.scs.2023.104582
Citation
Details
Zhao, Xuanpeng and Liao, Xishun and Wu, Guoyuan and Boriboonsomsin, Kanok and Barth, Matthew
"Improving Truck Merging at Ramps in a Mixed Traffic Environment: A Multi-human-in-the-loop (MHuiL) Approach"
, 2023
https://doi.org/10.1109/ITSC57777.2023.10422261
Citation
Details
Zhao, Xuanpeng and Wu, Guoyuan and Venkatram, Akula and Luo, Ji and Hao, Peng and Boriboonsomsin, Kanok and Hu, Shaohua
"Integrated Simulation Platform for Quantifying the Traffic-Induced Environmental and Health Impacts"
, 2024
https://doi.org/10.1109/FISTS60717.2024.10485596
Citation
Details
Zhao, Zhouqiao and Liao, Xishun and Abdelraouf, Amr and Han, Kyungtae and Gupta, Rohit and Barth, Matthew J and Wu, Guoyuan
"Inverse Reinforcement Learning and Gaussian Process Regression-based Real-Time Framework for Personalized Adaptive Cruise Control"
, 2023
https://doi.org/10.1109/ITSC57777.2023.10422413
Citation
Details
Zhao, Zhouqiao and Liao, Xishun and Abdelraouf, Amr and Han, Kyungtae and Gupta, Rohit and Barth, Matthew J and Wu, Guoyuan
"Real-Time Learning of Driving Gap Preference for Personalized Adaptive Cruise Control"
, 2023
https://doi.org/10.1109/SMC53992.2023.10394260
Citation
Details
(Showing: 1 - 10 of 58)
(Showing: 1 - 58 of 58)
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