Author Archives: Junmin Wang

2023 IEEE International Automated Vehicle Validation Conference (IEEE-IAVVC) will be held Oct. 16-18 in Austin, Texas

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The 2023 IEEE International Automated Vehicle Validation Conference (IEEE-IAVVC) will be held Oct. 16-18 in Austin, Texas.  More details can be found at https://2023.iavvc.org.

Sponsored by the IEEE Instrumentation and Measurement Society, the IEEE Standards Association, the IEEE Transportation Electrification Community, and the International Alliance for Mobility Testing and Standardization (IAMTS), the 2023 IEEE-IAVVC aims to bring researchers and representatives from academia, industry, and government together to exchange ideas in the automated and connected vehicle and infrastructure space.  The conference will feature regular, invited, special, and tutorial sessions as well as workshops and demonstrations.

Zejiang receives 2022 IEEE Intelligent Transportation Systems Best Dissertation Award – First Prize

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Former MSL Ph.D. student, Dr. Zejiang Wang, received the 2022 IEEE Intelligent Transportation Systems Society (ITSS) Best Dissertation Award – First Prize for his dissertation titled, “Motion Control Considering Human Driver Characteristics for Driving Safety Enhancement of Connected and Automated Vehicles”.

This is a prestigious award competed by Ph.D. dissertations worldwide and judged by a committee of international experts.  The Award consists of a $2000 monetary prize and a plaque that will be presented at the IEEE Intelligent Vehicles Symposium to be held in Anchorage, Alaska, USA on 4-7 June. Congratulations Zejiang!

Zejiang graduated from MSL in Spring 2022, and is a R&D Associate Staff at Oak Ridge National Lab.

MSL Papers Received Recognitions at IFAC-MECC 2022

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Two MSL papers received award recognitions at the 2022 IFAC Modeling, Estimation and Control Conference in Oct. 2022.

The paper “A Two-Stage Genetic Algorithm for Battery Sizing and Route Optimization of Medium-Duty Electric Delivery Fleets,” by Hyunjin Ahn, Zejiang Wang, Heran Shen, Xingyu Zhou, and Junmin Wang, received the ASME Automotive and Transportation Systems Best Paper Award judged by a committee of international experts from academia and industry.

The paper “Linear Motor Command Tracking: A Novel Immersion and Invariance Adaptive Control Method With Arctangent-Function-Based Parameter Projection,” by Xingyu Zhou, Heran Shen, Zejiang Wang, Hyunjin Ahn, and Junmin Wang, was recognized as one of the finalists for the 2022 MECC Best Student Paper Award.

Congratulations!