A comprehensive survey on transfer learning
Transfer learning aims at improving the performance of target learners on target domains by
transferring the knowledge contained in different but related source domains. In this way, the …
transferring the knowledge contained in different but related source domains. In this way, the …
Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving
The last decade witnessed a great development of automated driving vehicles (ADVs) and
vehicle intelligence. The significant increment of machine intelligence poses a new …
vehicle intelligence. The significant increment of machine intelligence poses a new …
Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning
Multi-agent interacting systems are prevalent in the world, from purely physical systems to
complicated social dynamic systems. In many applications, effective understanding of the …
complicated social dynamic systems. In many applications, effective understanding of the …
Path following control of autonomous four-wheel-independent-drive electric vehicles via second-order sliding mode and nonlinear disturbance observer techniques
J Chen, Z Shuai, H Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, we aim to investigate the path following control problem for four-wheel-
independent-drive electric vehicles with consideration of modeling errors and complex …
independent-drive electric vehicles with consideration of modeling errors and complex …
Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …
and will dominate road transportation in the future. Energy management, which optimizes …
A hierarchical framework for interactive behaviour prediction of heterogeneous traffic participants based on graph neural network
In complex and dynamic urban traffic scenarios, the accurate prediction of trajectories of
surrounding traffic participants (vehicles, pedestrians, etc) with interactive behaviours plays …
surrounding traffic participants (vehicles, pedestrians, etc) with interactive behaviours plays …
Driver behavior modeling toward autonomous vehicles: Comprehensive review
Driver behavior models have been used as input to self-coaching, accident prevention
studies, and developing driver-assisting systems. In recent years, driver behavior …
studies, and developing driver-assisting systems. In recent years, driver behavior …
[HTML][HTML] Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges
Modelling, predicting and analysing driver behaviours are essential to advanced driver
assistance systems (ADAS) and the comprehensive understanding of complex driving …
assistance systems (ADAS) and the comprehensive understanding of complex driving …
Multi-scale driver behavior modeling based on deep spatial-temporal representation for intelligent vehicles
The mutual understanding between driver and vehicle is critical to the realization of
intelligent vehicles and customized interaction interface. In this study, a unified driver …
intelligent vehicles and customized interaction interface. In this study, a unified driver …
[HTML][HTML] Review on vehicle detection technology for unmanned ground vehicles
Q Liu, Z Li, S Yuan, Y Zhu, X Li - Sensors, 2021 - mdpi.com
Unmanned ground vehicles (UGVs) have great potential in the application of both civilian
and military fields, and have become the focus of research in many countries. Environmental …
and military fields, and have become the focus of research in many countries. Environmental …