Probabilistic trajectory prediction for autonomous vehicles with attentive recurrent neural process
Predicting surrounding vehicle behaviors are critical to autonomous vehicles when
negotiating in multi-vehicle interaction scenarios. Most existing approaches require tedious …
negotiating in multi-vehicle interaction scenarios. Most existing approaches require tedious …
On the application of machine learning for cut-in maneuver recognition in platooning scenarios
Cut-in into vehicle platoons is a dangerous driving maneuver that affects the safety and
efficiency of platooning vehicles. An accurate prediction of such maneuver enables the …
efficiency of platooning vehicles. An accurate prediction of such maneuver enables the …
[PDF][PDF] Modeling uncertainty in vehicle trajectory prediction in a mixed connected and autonomous vehicle environment using deep learning and kernel density …
T Li - The Fourth Annual Symposium on Transportation …, 2018 - academia.edu
The advent of connected and autonomous vehicles (CAVs) will change driving behavior and
the travel environment, providing opportunities for safer, smoother, and smarter road …
the travel environment, providing opportunities for safer, smoother, and smarter road …
Limits of probabilistic safety guarantees when considering human uncertainty
R Cheng, RM Murray, JW Burdick - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
When autonomous robots interact with humans, such as during autonomous driving, explicit
safety guarantees are crucial in order to avoid potentially life-threatening accidents. Many …
safety guarantees are crucial in order to avoid potentially life-threatening accidents. Many …
Parkpredict: Motion and intent prediction of vehicles in parking lots
We investigate the problem of predicting driver behavior in parking lots, an environment
which is less structured than typical road networks and features complex, interactive …
which is less structured than typical road networks and features complex, interactive …
Trajectory prediction based on planning method considering collision risk
Anticipating the trajectory of Autonomous Vehicles (AV) plays an important role in improving
its driving safety. With the rapid development of learning-based method in recent years, the …
its driving safety. With the rapid development of learning-based method in recent years, the …
Exploring Spatial Frequency Information for Enhanced Video Prediction Quality
J Lai, L Gan, J Zhu, H Liu, L Gao - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Video prediction is a challenging spatiotemporal prediction task that generates future frames
based on historical observations. Although recently proposed deep learning-based methods …
based on historical observations. Although recently proposed deep learning-based methods …
Lane departure prediction based on closed-loop vehicle dynamics
D Li, S Lin, G Liu - … of the Institution of Mechanical Engineers …, 2022 - journals.sagepub.com
An automated driving system should have the ability to supervise its own performance and
to request human driver to take over when necessary. In the lane keeping scenario, the …
to request human driver to take over when necessary. In the lane keeping scenario, the …
Learning self-awareness for autonomous vehicles: Exploring multisensory incremental models
The technology for autonomous vehicles is close to replacing human drivers by artificial
systems endowed with high-level decision-making capabilities. In this regard, systems must …
systems endowed with high-level decision-making capabilities. In this regard, systems must …
Autonomous vehicle path prediction using conditional variational autoencoder networks
Path prediction of autonomous vehicles is an essential requirement under any given traffic
scenario. Trajectory of several agent vehicles in the vicinity of ego vehicle, at least for a short …
scenario. Trajectory of several agent vehicles in the vicinity of ego vehicle, at least for a short …