1 code implementation • 16 Oct 2023 • Jiajia Li, Raju Thada Magar, Dong Chen, Feng Lin, Dechun Wang, Xiang Yin, Weichao Zhuang, Zhaojian Li
Soybeans are a critical source of food, protein and oil, and thus have received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques.
1 code implementation • 13 Aug 2023 • Jiajia Li, Mingle Xu, Lirong Xiang, Dong Chen, Weichao Zhuang, Xunyuan Yin, Zhaojian Li
These models are trained on a large amount of data from multiple domains and modalities.
no code implementations • 13 Aug 2023 • Xubo Gu, Hanyu Bai, Xiaofan Cui, Juner Zhu, Weichao Zhuang, Zhaojian Li, Xiaosong Hu, Ziyou Song
Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent.
no code implementations • 16 Jun 2023 • Haoxuan Dong, Weichao Zhuang, Guoyuan Wu, Zhaojian Li, Guodong Yin, Ziyou Song
To potentially mitigate the negative effect of preceding vehicles on eco-driving control at the signalized intersection, this paper proposes an overtakingenabled eco-approach control (OEAC) strategy.
no code implementations • 5 Oct 2022 • Qun Wang, Haoxuan Dong, Fei Ju, Weichao Zhuang, Chen Lv, Liangmo Wang, Ziyou Song
A comprehensive simulation is conducted to statistically verify the positive impacts of CAV on the holistic energy efficiency of the mixed traffic flow with uncertain and diverse human driving behaviors.
no code implementations • 1 Nov 2021 • Haoji Liu, Weichao Zhuang, Guodong Yin, Rongcan Li, Chang Liu, Shanxing Zhou
We first formulate the optimal merging control problem, which includes the constraints of safety and vehicle dynamics, with the objectives of minimizing travel time and energy consumption.
no code implementations • 13 Oct 2021 • Mohammad R. Hajidavalloo, Zhaojian Li, Xin Xia, Ali Louati, Minghui Zheng, Weichao Zhuang
Promising results on extensive simulations and hardware-in-the-loop experiments show that the proposed collaborative estimation can significantly enhance estimation and iteratively improve the performance from vehicle to vehicle, despite vehicle heterogeneity, model uncertainty, and measurement noises.