{"id":46,"date":"2022-09-01T10:35:40","date_gmt":"2022-09-01T17:35:40","guid":{"rendered":"https:\/\/faculty.engineering.asu.edu\/jzhao\/?page_id=46"},"modified":"2026-04-15T21:37:19","modified_gmt":"2026-04-16T04:37:19","slug":"publication","status":"publish","type":"page","link":"https:\/\/faculty.engineering.asu.edu\/jzhao\/publication\/","title":{"rendered":"Publication"},"content":{"rendered":"\n

Publications<\/strong> (Google Scholar<\/a>)<\/h3>\n\n\n\n
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Conference Papers<\/strong><\/h4>\n\n\n\n

26. Hengcong Guo, DeAndre San Agustin, Venkata Seetha Ram Mohan, Shujauddin Rahimi, Steve Rundus, Jeffrey Wishart, and Junfeng Zhao, “Real-Time Driving Assessment in Simulation Based on SAE J3237”, IEEE Intelligent Vehicles Symposium (IV), 2026<\/p>\n\n\n\n

25. Pranav Ramesh Bidare, Nithish Kumar Saravanan, Jingxiong Meng, and Junfeng Zhao, “Optimizing Perception Capabilities of Autonomous Vehicles Through V2I Late Fusion using Kalman Filter”, 2025 Modeling, Estimation and Control Conference, 2025<\/p>\n\n\n\n

24. Haoran Ding, and Junfeng Zhao, “LLM-Driven Simulation Pipeline for Safety-Critical Scenario Evaluation in Autonomous Vehicles”, 2025 Modeling, Estimation and Control Conference, 2025<\/p>\n\n\n\n

23. Hengcong Guo, and Junfeng Zhao, “Enhancing Autonomous Driving Policy Stability through Auxiliary Network in Reinforcement Learning from Human Feedback”, 2025 American Control Conference (ACC), 2025 <\/p>\n\n\n\n

22. Rohan Khaire, Hengcong Guo, Harsh Gangwar, Nithish Kumar Saravanan, Jeffrey Wishart, and Junfeng Zhao, “Augmented Reality-Enhanced Digital Twin for Automated Vehicle Testing”, 12th IFAC Symposium on Intelligent Autonomous Vehicles, 2025<\/p>\n\n\n\n

21. Haoran Ding, Nithish Kumar Saravanan, Hengcong Guo, Nathan Fahner, Bidare, Pranav Ramesh Bidare, Jeffrey Wishart, and Junfeng Zhao, “Upgrading an Automated Vehicle Research Platform for Enhanced Perception and Distributed Computing”, 12th IFAC Symposium on Intelligent Autonomous Vehicles, 2025<\/p>\n\n\n\n

20. Sunder Swaminathan, Jeffrey Wishart, Junfeng Zhao, Brendan Russo, and Shujauddin Rahimi, “Adapting the Technology Readiness Level (TRL) Framework to AV Development”, SAE Technical Paper, 2025<\/p>\n\n\n\n

19. Jeffrey Wishart, Shujauddin Rahimi, Sunder Swaminathan, Junfeng Zhao, Matt Frantz, Satvir Singh, and Steven Gerard Como, “Dynamic Driving Task Assessment Scores for Scenarios Navigated by an OEM ADS-Equipped Vehicle”, SAE Technical Paper, 2025<\/p>\n\n\n\n

18. Jingxiong Meng, Yan Chen, Junfeng Zhao, “Starlink for Localization: A Low Earth Orbit Satellites Based Approach for Vehicle Localization”, 2024 Modeling, Estimation, and Control Conference, Oct. 2024.<\/p>\n\n\n\n

17. Shun-Yen Wang, Jingxiong Meng, Jeffrey Wishart, Junfeng Zhao, “Simultaneous Localization and Mapping with Road Markings Identified from LiDAR Intensity”, 2024 Modeling, Estimation, and Control Conference, Oct. 2024.<\/p>\n\n\n\n

16. Hengcong Guo, Jiangtao Li, Nithish Kumar Saravanan, Jeffrey Wishart, Junfeng Zhao, “Developing an Automated Vehicle Research Platform by Integrating Autoware with the DataSpeed Drive-By-Wire System”, SAE Technical Paper, 2024<\/p>\n\n\n\n

15. Jingxiong Meng, Yan Chen, and Junfeng Zhao, “Development and Evaluation of a LEO Satellite-Based Vehicle Localization Method”, SAE Technical Paper, 2024<\/p>\n\n\n\n

14. Gavin O’Malley, Jeffrey Wishart, Junfeng Zhao, and Brendan Russo, “A Scenario-Based Test Selection and Scoring Methodology for Inclusion into a Safety Case Framework for Automated Vehicles”, SAE Technical Paper, 2024<\/p>\n\n\n\n

13. Jeffrey Wishart, Junfeng Zhao, Braeden Woodward, Gavin O’Malley, Hengcong Guo, Shujauddin Rahimi, and Sunder Swaminathan, “A Proposed Safety Case Framework for Automated Vehicles with Pillars of Safety Management System, Design Methods, and Scenario-Based Testing”, IEEE International Automated Vehicle Validation Conference, 2023<\/p>\n\n\n\n

12. Jingxiong Meng, Junfeng Zhao, and Yan Chen, ” Reinforcement Learning Enabled Safety Critical Tracking of Automated Vehicles with Uncertainties via Integrated Control-Dependent, Time-Varying Barrier Function, and Control Lyapunov Function”, IFAC-PapersOnLine<\/em>, 56<\/em>, 85\u201390, 2023<\/p>\n\n\n\n

11. Shunsuke Aoki, Lung En Jan, Junfeng Zhao, Anand Bhat, Ragunathan Rajkumar, and Chen-Fang Chang, “MultiCruise: Eco-Lane Selection Strategy with Eco-Cruise Control for Connected and Automated Vehicles”, IEEE Intelligent Vehicles Symposium<\/em>, 2021<\/p>\n\n\n\n

10. Junfeng Zhao*, Chen-Fang Chang, Ragunathan Rajkumar, and Jeffrey Gonder, “Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System”, SAE technical paper<\/em>, 2020-01-0588, 2020.<\/p>\n\n\n\n

9. Lung En Jan, Junfeng Zhao, Shunsuke Aoki, Anand Bhat, Chen-Fang Chang, and Ragunathan Rajkumar, “Speed Trajectory Generation for Energy-Efficient Connected and Automated Vehicles”, at 2020 ASME Dynamic Systems and Control Conference<\/em>, Pittsburg, PA, 2020<\/p>\n\n\n\n

8. Shunsuke Aoki, Lung En Jan, Anand Bhat, Junfeng Zhao, Ragunathan Rajkumar, and Chen-Fang Chang, “A Co-simulation Platform for Eco-driving Connected and Automated Vehicles”, at 2020 IEEE Intelligent Vehicles Symposium<\/em>, Las Vegas, NV, 2020<\/p>\n\n\n\n

7. Junfeng Zhao*, Hai Wu, and Chen-Fang Chang, “Virtual Traffic Simulator for Connected and Automated Vehicles”, SAE technical paper<\/em>, 2019-01-0676, 2019.<\/p>\n\n\n\n

6. Junfeng Zhao*, Yiran Hu, Steve Muldoon, and Chen-Fang Chang, “InfoRich Eco-Driving Control Strategy for Connected and Automated Vehicles”, at 2019 American Control Conference<\/em>, Philadelphia, PA, 2019<\/p>\n\n\n\n

5. Junfeng Zhao, and Junmin Wang, “Model Predictive Control of Integrated Hybrid Electric Powertrains Coupled with Aftertreatment Systems”, at 2014 ASME Dynamic Systems and Control Conference<\/em>, San Antonio, TX, 2014.<\/p>\n\n\n\n

4. Junfeng Zhao, and Junmin Wang, “Mass Airflow Sensor Fault Detection via an Adaptive Oxygen Fraction Observer,” at 2014 American Control Conference<\/em>, Portland, OR, 2014.<\/p>\n\n\n\n

3. Junfeng Zhao, and Junmin Wang, “Observer-Based Oxygen Fraction Estimation for a Dual-Loop EGR Diesel Engine Fueled with Biodiesel Blends,” at 2013 ASME Dynamic Systems and Control Conference<\/em>, San Francisco, CA, 2013.<\/p>\n\n\n\n

2. Junfeng Zhao, and Junmin Wang, “On-Board Fuel Property Identification Method Based on Common Rail Pressure Signal,” at 2012 ASME Dynamic Systems and Control Conference<\/em>, Ft. Lauderdale, FL, 2012.<\/p>\n\n\n\n

1. Junfeng Zhao, and Junmin Wang, “Energy-based and Oxygen-based Biodiesel Blend Level Estimation Methods for Diesel Engines,” at 2012 American Control Conference<\/em>, Montreal, Canada, 2012.<\/p>\n\n\n\n

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Journal Articles<\/strong><\/h4>\n\n\n\n

14. Pranav Rajesh, Dheeraj Kallakuri, Sudeeksha Chagarlamudi, Sai Manoj Vissavajhula, Jingxiong Meng, and Junfeng Zhao, “Intelligent Parking Guidance System using Computer Vision, IoT, and Edge Computing”, in IEEE Open Journal of Intelligent Transportation Systems<\/em>, 2025, doi: 10.1109\/OJITS.2025.3605318<\/p>\n\n\n\n

13. Hengcong Guo, Rohan Khaire, and Junfeng Zhao, “Reinforcement Learning from Human Feedback with Fast-Slow Updates for Stable Driving
Strategies”, Control Engineering Practice<\/em>, 2025, doi: 10.1016\/j.conengprac.2025.106549<\/p>\n\n\n\n

12. Nithish Kumar Saravanan, Varun Chandra Jammula, Yezhou Yang, Jeffrey Wishart, and Junfeng Zhao, “Enhanced Cooperative Perception Through Asynchronous V2I Framework with Delay Mitigation for Connected and Automated Vehicles” in SAE Journal of Connected and Automated Vehicles<\/em>, 2025<\/p>\n\n\n\n

11. Jingxiong Meng and Junfeng Zhao, “VI-BEV: Vehicle-Infrastructure Collaborative Perception for 3D Object Detection on Bird\u2019s-Eye View,” in IEEE Open Journal of Intelligent Transportation Systems<\/em>, 2025, doi: 10.1109\/OJITS.2025.3543831.<\/p>\n\n\n\n

10. Junfeng Zhao, Wan Li, Junmin Wang, and Xuegang Ban, “Dynamic Traffic Signal Timing Optimization Strategy Incorporating Various Vehicle Fuel Consumption Characteristics”, IEEE<\/em> Transactions on Vehicular Technology-Special Issue on Connected Vehicles,<\/em> 65, No. 6, pp. 3874-3887, 2016. (10.1109\/TVT.2015.2506629)<\/p>\n\n\n\n

9. Junfeng Zhao, Junmin Wang, “Integrated Modeling and Model Predictive Control of Hybrid Electric Vehicle Coupled with Aftertreatment Systems”, IEEE Transactions on Vehicular Technology<\/em>, Vol. 65, No. 3, pp.1199-1211, 2016. (10.1109\/TVT.2015.2405918)<\/p>\n\n\n\n

8. Junfeng Zhao, Pingen Chen, Umar Ibrahim, Junmin Wang, “Comparative Study and Accommodation of Biodiesel in Diesel-electric Hybrid Vehicles Coupled with Aftertreatment Systems”, Asian Journal of Control, <\/em> 18, No. 1, pp. 3-15, 2016 (DOI: 10.1002\/asjc.1137).<\/p>\n\n\n\n

7. Junfeng Zhao and Junmin Wang, “Adaptive Observer for Joint Estimation of Oxygen Fractions and Blend Level in Biodiesel Fueled Engines,” IEEE Transactions on Control System Technology<\/em>, Vol. 23, no. 1, pp. 80 – 90, 2015 (DOI: 10.1109\/TCST.2014.2313003).<\/p>\n\n\n\n

6. Junfeng Zhao and Junmin Wang, “On-Board Fuel Property Identification Method Based on Common Rail Pressure Signal,” ASME Transactions Journal of Dynamic Systems, Measurement, and Control<\/em>, Vol. 136, Issue 3, 031010, 2014 (DOI: 10.1115\/1.4026130).<\/p>\n\n\n\n

5. Fengjun Yan, Song Chen, Xiangrui Zeng, Junfeng Zhao, and Junmin Wang, “Modeling and Analysis of Fuel Injection Split for Diesel Engine Active Fueling Control,” ASME Transactions Journal of Dynamic Systems, Measurement, and Control<\/em>, Vol. 135, Issue 6, 061016, 2013 (DOI: 10.1115\/1.4024806).<\/p>\n\n\n\n

4. Junfeng Zhao and Junmin Wang, “Control-Oriented Multi-Phase Combustion Model for Biodiesel Fueled Engines,” Applied Energy<\/em>, vol. 108, pp. 92 – 99, 2013 (DOI: 10.1016\/j.apenergy.2013.03.001).<\/p>\n\n\n\n

3. Junfeng Zhao and Junmin Wang, “Effect of Exhaust Gas Recirculation on Biodiesel Blend Level Estimation in Diesel Engines,” ASME Transactions Journal of Dynamic Systems, Measurements, and Control<\/em>, vol. 135, no.1, 011011, 2013 (DOI: 10.1115\/1.4006884).<\/p>\n\n\n\n

2. Junfeng Zhao and Rudolf Seethaler, “A Fully Flexible Valve Actuation System for Internal Combustion Engines”, IEEE\/ASME Transactions on Mechatronics<\/em>, vol.16, no.2, pp.361-370, 2011.<\/p>\n\n\n\n

1. Junfeng Zhao and Rudolf Seethaler, “Compensating Combustion Forces for Automotive Electromagnetic Valves”, Mechatronics<\/em>, Vol 20, no. 4, pp 433-441, 2010.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Patents<\/strong><\/h3>\n\n\n\n
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16. US Patent 63\/688,724, Intelligent Parking Guidance System, Filed in 2024<\/p>\n\n\n\n

15. US Patent 20240047979, Multi-Voltage Vehicle Operation, Granted in 2024<\/p>\n\n\n\n

14. US Patent 20230398887, Switching High Voltage for an Electric Vehicle, Granted in 2023<\/p>\n\n\n\n

13. US Patent 20230366943, Detecting the State of Charge Sensing of a Mixed Chemistry Battery, Granted in 2023<\/p>\n\n\n\n

12. US Patent 20240025271, Low Loss Electric Drive Speed Guideline System for EV, Granted in 2024<\/p>\n\n\n\n

11. US Patent 11865932, High Voltage Operation Strategy for Electric Vehicles, 2022 <\/p>\n\n\n\n

10. US Patent 16\/559,738, Connected and Automated Vehicles, Driving Systems, And Control Logic for Info-Rich Eco-Autonomous Driving, Granted in 2022<\/p>\n\n\n\n

9. US Patent 16\/380,275, Method and apparatus for controlling a vehicle including an adaptive cruise control system, Granted in 2021<\/p>\n\n\n\n

8. US Patent 16\/884,198, Control Systems, and Methods Using Parametric Driver Model, Granted in 2021<\/p>\n\n\n\n

7. US Patent 16\/116,129, Electric-Drive Motor Vehicles, Systems, and Control Logic for Predictive Charge Planning and Powertrain Control, Granted in 2020<\/p>\n\n\n\n

6. US Patent 16\/003,223, Powertrain Control System and Method of Operating the Same, Granted in 2019<\/p>\n\n\n\n

5. US Patent 15\/880,918, Method and System for Routing Based on a Predicted Connectivity Quality. Granted in 2020<\/p>\n\n\n\n

4. US Patent 10,215,576, Energy-Optimized Vehicle Route Selection, Granted in 2019<\/p>\n\n\n\n

3. US Patent 10,371,116, Method and Apparatus for Controlling a Multi-Cylinder Internal Combustion Engine, Granted in 2019<\/p>\n\n\n\n

2. US Patent 10,273,928, Model-Based Combustion Timing and Torque Control for Internal Combustion Engine Assemblies, Granted in 2019<\/p>\n\n\n\n

1. US Patent 10,081,360, Vehicle Propulsion Systems and Methods, Granted in 2019<\/p>\n<\/div>\n<\/div>\n\n\n\n

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