Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
Research advances and challenges of autonomous and connected ground vehicles
Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …
solution for the public, but the complex and various environments in the real world make it …
A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
Sequence-to-sequence prediction of vehicle trajectory via LSTM encoder-decoder architecture
In this paper, we propose a deep learning based vehicle trajectory prediction technique
which can generate the future trajectory sequence of surrounding vehicles in real time. We …
which can generate the future trajectory sequence of surrounding vehicles in real time. We …
Autonomous vehicle safety: An interdisciplinary challenge
P Koopman, M Wagner - IEEE Intelligent Transportation …, 2017 - ieeexplore.ieee.org
Ensuring the safety of fully autonomous vehicles requires a multi-disciplinary approach
across all the levels of functional hierarchy, from hardware fault tolerance, to resilient …
across all the levels of functional hierarchy, from hardware fault tolerance, to resilient …
Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network
In this paper, we propose an efficient vehicle trajectory prediction framework based on
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …
[HTML][HTML] Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions
Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …
research because of its multi-faceted advantages that includes improved safety, reduced …
Using online verification to prevent autonomous vehicles from causing accidents
Ensuring that autonomous vehicles do not cause accidents remains a challenge. We
present a formal verification technique for guaranteeing legal safety in arbitrary urban traffic …
present a formal verification technique for guaranteeing legal safety in arbitrary urban traffic …
Recent advances in motion and behavior planning techniques for software architecture of autonomous vehicles: A state-of-the-art survey
Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …
industrial research because of various advantages such as safety improvement, lower …
The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review
ZE Abou Elassad, H Mousannif… - … Applications of Artificial …, 2020 - Elsevier
Driving Behavior (DB) is a complex concept describing how the driver operates the vehicle
in the context of the driving scene and surrounding environment. Recently, DB assessment …
in the context of the driving scene and surrounding environment. Recently, DB assessment …