Results 21 to 30 of about 462,929 (272)

Intelligent Environment Enabling Autonomous Driving

IEEE Access, 2021
Automated driving is expected to enormously evolve the transportation industry and ecosystems. Advancement in communications and sensor technologies have further accelerated the realization process of the autonomous driving goals.
Manzoor Ahmed Khan
doaj   +1 more source

Deep Reinforcement Learning framework for Autonomous Driving

, 2017
Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes.
Abdou, Mohammed, Perot, Etienne, Sallab, Ahmad El, Yogamani, Senthil   +3 more
core   +1 more source

A Model-Based Spatio-Temporal Behavior Decider for Autonomous Driving

Machines
Spatio-temporal planning has emerged as a robust methodology for solving trajectory planning challenges in complex autonomous driving scenarios. By integrating both spatial and temporal variables, this approach facilitates the generation of highly ...
Yiwen Huang, Huikang Zhang, Junchan Liao, Ruhong Zhuang, Honggou Yang, Xianming Liu   +5 more
doaj   +1 more source

Estimation of Vehicle Attitude, Acceleration, and Angular Velocity Using Convolutional Neural Network and Dual Extended Kalman Filter

Sensors, 2021
The acceleration of a vehicle is important information in vehicle states. The vehicle acceleration is measured by an inertial measurement unit (IMU). However, gravity affects the IMU when there is a transition in vehicle attitude; thus, the IMU produces ...
Minseok Ok, Sungsuk Ok, Jahng Hyon Park
doaj   +1 more source

Toward zero traffic deaths and disabilities with active and passive safety technologies in the association of southeast Asian nations

IATSS Research
Road traffic crashes caused more than 108,000 deaths and 6,200,000 injuries resulting in 7.7 million disability-adjusted life years (DALYs) lost in the Association of Southeast Asian Nations (ASEAN) in 2019.
Husam Muslim, Marko Medojevic, Sandra Watanabe, Hisashi Imanaga, Nobuyuki Uchida, Sou Kitajima, Genya Abe   +6 more
doaj   +1 more source

Analysis and Modeling of Lane-Changing Game Strategy for Autonomous Driving Vehicles

IEEE Access, 2022
Autonomous driving vehicles have some advantages, such as alleviating tasks of drivers and reducing carbon emissions. With the advancement of intelligent network connection technology, autonomous driving vehicles are showing a trend of practicality and ...
Dayi Qu, Kekun Zhang, Hui Song, Yanfeng Jia, Shouchen Dai   +4 more
doaj   +1 more source

WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving

, 2019
Machine learning can provide efficient solutions to the complex problems encountered in autonomous driving, but ensuring their safety remains a challenge.
Balakrishnan, Aravind, Czarnecki, Krzysztof, Gaurav, Ashish, Lee, Jaeyoung, Sedwards, Sean   +4 more
core   +1 more source

Correction: Osman, M., et al. A Novel Online Approach for Drift Covariance Estimation of Odometries Used in Intelligent Vehicle Localization. Sensors 2019, 19, 5178

Sensors, 2020
The authors wish to make the following corrections to this paper [...]
Mostafa Osman, Ahmed Hussein, Abdulla Al-Kaff, Fernando Garcia, Dongpu Cao   +4 more
doaj   +1 more source

Agile Autonomous Driving using End-to-End Deep Imitation Learning

, 2019
We present an end-to-end imitation learning system for agile, off-road autonomous driving using only low-cost sensors. By imitating a model predictive controller equipped with advanced sensors, we train a deep neural network control policy to map raw ...
Boots, Byron, Cheng, Ching-An, Lee, Keuntaek, Pan, Yunpeng, Saigol, Kamil, Theodorou, Evangelos, Yan, Xinyan   +6 more
core   +1 more source

Toward Feature-Based Low-Latency Localization With Rotating LiDARs

IEEE Journal of Indoor and Seamless Positioning and Navigation
An accurate global position is often considered to be one of the main requirements for autonomous driving. Even though GNSS provides a solution, it is dependent on the environment and not accurate enough.
Lukas Beer, Thorsten Luettel, Mirko Maehlisch   +2 more
doaj   +1 more source