Safe and efficient reinforcement learning for behavioural planning in autonomous driving
E Leurent - 2020 - inria.hal.science
In this Ph. D. thesis, we study how autonomous vehicles can learn to act safely and avoid
accidents, despite sharing the road with human drivers whose behaviours are uncertain. To …
accidents, despite sharing the road with human drivers whose behaviours are uncertain. To …
Integrating safety distances with trajectory planning by modifying the occupancy grid for autonomous vehicle navigation
H Mouhagir, R Talj, V Cherfaoui… - 2016 IEEE 19th …, 2016 - ieeexplore.ieee.org
The goal of the work in this paper is to use occupancy grid in integrating safety distances
with the planning strategy for autonomous vehicle navigation. The challenge is to avoid …
with the planning strategy for autonomous vehicle navigation. The challenge is to avoid …
Interaction-aware occupancy prediction of road vehicles
M Koschi, M Althoff - 2017 IEEE 20th International Conference …, 2017 - ieeexplore.ieee.org
A crucial capability of autonomous road vehicles is the ability to cope with the unknown
future behavior of surrounding traffic participants. This requires using non-deterministic …
future behavior of surrounding traffic participants. This requires using non-deterministic …
Trajectory prediction of traffic agents at urban intersections through learned interactions
To navigate a complex urban environment, it is essential for autonomous vehicles to make
educated assumptions and accurate predictions of the movement of other traffic agents …
educated assumptions and accurate predictions of the movement of other traffic agents …
Does haptic steering guidance instigate speeding? A driving simulator study into causes and remedies
An important issue in road traffic safety is that drivers show adverse behavioral adaptation
(BA) to driver assistance systems. Haptic steering guidance is an upcoming assistance …
(BA) to driver assistance systems. Haptic steering guidance is an upcoming assistance …
Understanding v2v driving scenarios through traffic primitives
Understanding driver interaction behavioral semantics has potential benefits to autonomous
car's decision-making design. This article presents a framework of analyzing various …
car's decision-making design. This article presents a framework of analyzing various …
Modeling multiple vehicle interaction constraints for behavior prediction of vehicles on highways
P Tripicchio, S D'Avella - Computers & Electrical Engineering, 2022 - Elsevier
In the context of autonomous driving and road situation awareness, this manuscript
introduces a Bayesian network that enables the prediction of participant vehicles (PVs) …
introduces a Bayesian network that enables the prediction of participant vehicles (PVs) …
Early prediction of driver's action using deep neural networks
Intelligent transportation systems (ITSs) are one of the most widely-discussed and
researched topic across the world. The researchers have focused on the early prediction of …
researched topic across the world. The researchers have focused on the early prediction of …
Multimodal trajectory predictions for autonomous driving without a detailed prior map
A Kawasaki, A Seki - Proceedings of the IEEE/CVF Winter …, 2021 - openaccess.thecvf.com
Predicting the future trajectories of surrounding vehicles is a key competence for safe and
efficient real-world autonomous driving systems. Previous works have presented deep …
efficient real-world autonomous driving systems. Previous works have presented deep …
Systems and methods for predicting entity behavior
A Jammalamadaka, R Bhattacharyya… - US Patent …, 2020 - Google Patents
Abstract Systems and method are provided for controlling a vehicle. In one embodiment, a
method includes: receiving sensor data sensed from an environment associated with the …
method includes: receiving sensor data sensed from an environment associated with the …