{"id":412,"date":"2024-11-30T21:54:18","date_gmt":"2024-11-30T13:54:18","guid":{"rendered":"https:\/\/www.translab.top\/?p=412"},"modified":"2025-03-27T20:21:00","modified_gmt":"2025-03-27T12:21:00","slug":"%e3%80%8cep03%c2%b7international-conference-exchange%e3%80%8d-trans-research-group-participates-in-the-5th-ieee-its-career-path-to-netzero-workshop-and-presents-academic-report","status":"publish","type":"post","link":"https:\/\/www.translab.top\/index.php\/en\/2024\/11\/30\/%e3%80%8cep03%c2%b7international-conference-exchange%e3%80%8d-trans-research-group-participates-in-the-5th-ieee-its-career-path-to-netzero-workshop-and-presents-academic-report\/","title":{"rendered":"\u300cEP03\u00b7International Conference Exchange\u300d- TRANS Research Group Participates in the 5th IEEE: ITS Career Path to NetZero Workshop and Presents Academic Report"},"content":{"rendered":"\n
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On November 1, 2024, the 5th IEEE Intelligent Transportation Systems: Career Path to NetZero workshop was held at Beijing University of Posts and Telecommunications in China. The IEEE UK and Ireland Women in Engineering Affinity Group organized the workshop, sponsored by the IEEE Intelligent Transportation Systems Society (ITS Society). They are supported by the IEEE UK and Ireland ITS Chapter. The workshop brought together scholars and professional researchers in intelligent transportation systems, showcasing cutting-edge research results and sharing personal career development paths in ITS, providing valuable learning and networking opportunities for graduate students and early-career researchers. TRANS Research Group’s doctoral student, Hao Qi, from the class of 2024, was invited to attend the workshop and present a poster report.<\/p>\n\n\n\n

\u2728 Conference Report<\/h2>\n\n\n\n

Doctoral student Hao Qi from the class of 2024 presented a poster report titled “Optimizing Safety, Efficiency, and Battery Health: A Deep Reinforcement Learning Model for Car-Following in Electric Vehicles.” This study focused on optimizing the car-following behavior of electric vehicles through a deep reinforcement learning model, considering traffic safety, driving efficiency, and battery health. During the report presentation, doctoral student Hao Qi engaged in lively discussions with on-site experts and peers, sharing the core innovative aspects of the model design and practical application scenarios of the research results.<\/p>\n\n\n\n

\u2728 Workshop Link<\/h2>\n\n\n\n

For more details about the 5th IEEE ITS: Career Path to NetZero workshop, please visit: Workshop Details<\/a>.<\/p>\n\n\n\n

Thank you for your attention. Stay tuned for more updates from our team!<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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