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Engineering: Recent Advances in Autonomous Ground Vehicles

Participating journal: Discover Applied Sciences

Recently, autonomous ground vehicles(AGV), especially, fully autonomous ground vehicles are expected to significantly provide increased highway capacity and traffic mobility with faster response times, less fuel consumption and environmental pollution with foresighted driving, greater driving safety benefits and convenience with intelligent driving by applying vehicle-to-other entities(V2X).As an important part of future intelligent transportation system, autonomous ground vehicles have attracted the increasing concern from the academia, industry and governments due to its potential applications such as automated highways, urban transportation. However, AGV with automated driving technologies will lead to complex challenges. e.g. high precision environment perception schemes using low cost sensors and information fusion extended from multi-source sensors, human-like decision-making and motion planning of automated driving for surrounding dynamic traffic objects such as other vehicles, cyclists, and pedestrians, advanced chassis dynamics modeling and control technologies in the presence of vehicle active safety system nonlinearities and parameters uncertainties, hybrid powertrain configurations and energy optimization and saving strategies for maximizing the true potential of connected vehicles, the design of new V2X communication protocols and the creation for in-vehicle network applications against vehicle network bandwidth limitation. The main objective of this collection is to provide an opportunity for scientists, engineers, and practitioners to exhibit recent theoretical and technological achievements in autonomous ground vehicles.

This Collection supports and amplifies research related to: SDG 7, SDG 9

Participating journal

Submit your manuscript to this collection through the participating journal.

Discover Applied Sciences is a multi-disciplinary open access journal covering applied life sciences, chemistry, earth and environmental sciences, engineering, materials science and...

Editors

  • Xianjian Jin

    Xianjian Jin

    Associate Professor Xianjian Jin, PhD, Shanghai University, China.

    He joined Shanghai University as an Assistant Professor and founded the Intelligent Electric Vehicle Laboratory (iEVL) in 2018. His major research interests cover modeling, estimation, control, and optimization for dynamic systems of advanced electric vehicles, intelligent and connected ground electric vehicles.

Articles

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