Driving experience and anticipatory driving are essential skills for humans to operate vehicles in complex environments. In the context of autonomous vehicles, the software must …
Planning the trajectory of the controlled ego vehicle is a key challenge in automated driving. As for human drivers, predicting the motions of surrounding vehicles is important to plan the …
V Trentin, C Ma, J Villagra… - 2023 IEEE Intelligent …, 2023 - ieeexplore.ieee.org
Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is fundamental in order to assure safety while navigating through highly interactive complex …
G Li, Z Li, VL Knoop… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous …
Y Meng, C Fan - IEEE Robotics and Automation Letters, 2024 - ieeexplore.ieee.org
Generating realistic simulations is critical for autonomous system applications such as self- driving and humanrobot interactions. However, driving simulators nowadays still have …
R Huang, G Zhuo, L Xiong, S Lu, W Tian - Sustainability, 2023 - mdpi.com
Autonomous driving vehicles can effectively improve traffic conditions and promote the development of intelligent transportation systems. An autonomous vehicle can be divided …
M Kang, S Wang, S Zhou, K Ye… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Motion forecasting plays a crucial role in autonomous driving, with the aim of predicting the future reasonable motions of traffic agents. Most existing methods mainly model the …
This letter presents View-of-Delft Prediction, a new dataset for trajectory prediction, to address the lack of on-board trajectory datasets in urban mixed-traffic environments. View-of …