Vehicle Plan
Vehicle plan research focuses on developing algorithms and systems for efficient and safe vehicle navigation and control, encompassing aspects like trajectory planning, behavior prediction, and sensor integration. Current research emphasizes the use of deep reinforcement learning, convolutional neural networks, and other advanced machine learning techniques to address challenges such as robust lane detection, stabilizing vehicle motion in diverse terrains, and optimizing energy management in electric vehicles. This work is crucial for advancing autonomous driving, improving traffic safety and efficiency, and enabling innovative applications in intelligent transportation systems.
Papers
Scene Modeling of Autonomous Vehicles Avoiding Stationary and Moving Vehicles on Narrow Roads
Qianyi Zhang, Jinzheng Guang, Zhenzhong Cao, Jingtai Liu
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
Hugo Math, Rainer Lienhart, Robin Schön
Machine Learning-Based Estimation Of Wave Direction For Unmanned Surface Vehicles
Manele Ait Habouche, Mickaël Kerboeuf, Goulven Guillou, Jean-Philippe Babau
A Comprehensive Review on Traffic Datasets and Simulators for Autonomous Vehicles
Supriya Sarker, Brent Maples, Weizi Li
An End-to-End Smart Predict-then-Optimize Framework for Vehicle Relocation Problems in Large-Scale Vehicle Crowd Sensing
Xinyu Wang, Yiyang Peng, Wei Ma
A Cost-Effective Approach to Smooth A* Path Planning for Autonomous Vehicles
Lukas Schichler, Karin Festl, Selim Solmaz, Daniel Watzenig
Power-Efficient Actuation for Insect-Scale Autonomous Underwater Vehicles
Cody R. Longwell, Conor K. Trygstad, Nestor O. Perez-Arancibia
Vehicles, Pedestrians, and E-bikes: a Three-party Game at Right-turn-on-red Crossroads Revealing the Dual and Irrational Role of E-bikes that Risks Traffic Safety
Gangcheng Zhang, Yeshuo Shu, Keyi Liu, Yuxuan Wang, Donghang Li, Liyan Xu
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
Robert Fonod, Haechan Cho, Hwasoo Yeo, Nikolas Geroliminis