[PDF][PDF] MIT autonomous vehicle technology study: Large-scale deep learning based analysis of driver behavior and interaction with automation

L Fridman, DE Brown, M Glazer, W Angell… - arXiv preprint arXiv …, 2017 - researchgate.net
Today, and possibly for a long time to come, the full driving task is too complex an activity to
be fully formalized as a sensing-acting robotics system that can be explicitly solved through …

MIT advanced vehicle technology study: Large-scale naturalistic driving study of driver behavior and interaction with automation

L Fridman, DE Brown, M Glazer, W Angell… - IEEE …, 2019 - ieeexplore.ieee.org
Today, and possibly for a long time to come, the full driving task is too complex an activity to
be fully formalized as a sensing-acting robotics system that can be explicitly solved through …

A survey of deep learning techniques for autonomous driving

S Grigorescu, B Trasnea, T Cocias… - Journal of field …, 2020 - Wiley Online Library
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

EDGAR: An Autonomous Driving Research Platform--From Feature Development to Real-World Application

P Karle, T Betz, M Bosk, F Fent, N Gehrke… - arXiv preprint arXiv …, 2023 - arxiv.org
While current research and development of autonomous driving primarily focuses on
developing new features and algorithms, the transfer from isolated software components into …

Key ingredients of self-driving cars

R Fan, J Jiao, H Ye, Y Yu, I Pitas, M Liu - arXiv preprint arXiv:1906.02939, 2019 - arxiv.org
Over the past decade, many research articles have been published in the area of
autonomous driving. However, most of them focus only on a specific technological area …

DrivAid: Augmenting driving analytics with multi-modal information

B Qi, P Liu, T Ji, W Zhao… - 2018 IEEE Vehicular …, 2018 - ieeexplore.ieee.org
The way people drive vehicles has a great impact on traffic safety, fuel consumption, and
passenger experience. Many research and commercial efforts today have primarily …

[HTML][HTML] Deep learning sensor fusion for autonomous vehicle perception and localization: A review

J Fayyad, MA Jaradat, D Gruyer, H Najjaran - Sensors, 2020 - mdpi.com
Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …

A maneuver-based urban driving dataset and model for cooperative vehicle applications

B Toghi, D Grover, M Razzaghpour… - 2020 IEEE 3rd …, 2020 - ieeexplore.ieee.org
Short-term future of automated driving can be imagined as a hybrid scenario in which both
automated and human-driven vehicles co-exist in the same environment. In order to address …

EU long-term dataset with multiple sensors for autonomous driving

Z Yan, L Sun, T Krajník… - 2020 IEEE/RSJ …, 2020 - ieeexplore.ieee.org
The field of autonomous driving has grown tremendously over the past few years, along with
the rapid progress in sensor technology. One of the major purposes of using sensors is to …

[PDF][PDF] Nuts and bolts of building AI applications using Deep Learning

A Ng - NIPS Keynote Talk, 2016 - media.nips.cc
Given the safety-critical requirement of autonomous driving and thus the need for extremely
high levels of accuracy, a pure end-to-end approach is still challenging to get to work. End …