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NEAT: Neural Attention Fields for End-to-End Autonomous Driving [article]

Kashyap Chitta, Aditya Prakash, Andreas Geiger
2021 arXiv   pre-print
We present NEural ATtention fields (NEAT), a novel representation that enables such reasoning for end-to-end imitation learning models.  ...  Efficient reasoning about the semantic, spatial, and temporal structure of a scene is a crucial prerequisite for autonomous driving.  ...  We thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Kashyap Chitta. The authors also thank Micha Schilling for his help in re-implementing AIM-VA.  ... 
arXiv:2109.04456v1 fatcat:l3bheqn3e5hfjjxc3frkkgwktm

Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer [article]

Hao Shao, Letian Wang, RuoBing Chen, Hongsheng Li, Yu Liu
2022 arXiv   pre-print
In this paper, we propose a safety-enhanced autonomous driving framework, named Interpretable Sensor Fusion Transformer(InterFuser), to fully process and fuse information from multi-modal multi-view sensors  ...  Large-scale deployment of autonomous vehicles has been continually delayed due to safety concerns.  ...  NEAT [17] proposes neural attention fields which enables the reasoning for end-to-end imitation learning.  ... 
arXiv:2207.14024v2 fatcat:y7n2cr2tl5gyhofmfj2ap2rruq

A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety [article]

A. M. Nascimento, L. F. Vismari, C. B. S. T. Molina, P.S. Cugnasca, J.B. Camargo Jr., J.R. de Almeida Jr., R. Inam, E. Fersman, M. V. Marquezini, A. Y. Hata
2019 arXiv   pre-print
Autonomous Vehicles (AV) are expected to bring considerable benefits to society, such as traffic optimization and accidents reduction.  ...  However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications  ...  and various object detection in real driving conditions Single monocular camera for autonomous vehicle in real driving conditions Artificial Neural Network combined to other techniques  ... 
arXiv:1904.02697v1 fatcat:jsruqsy3kvcyvdyfhzo4ojfaqi

TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving [article]

Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger
2022 arXiv   pre-print
How should we integrate representations from complementary sensors for autonomous driving? Geometry-based fusion has shown promise for perception (e.g. object detection, motion forecasting).  ...  However, in the context of end-to-end driving, we find that imitation learning based on existing sensor fusion methods underperforms in complex driving scenarios with a high density of dynamic agents.  ...  attention prediction [78] , [79] and recently also for end-to-end driving [39] , [41] .  ... 
arXiv:2205.15997v1 fatcat:nyteapdbr5dqbadxliletwnzcy

Brain Intelligence: Go Beyond Artificial Intelligence [article]

Huimin Lu, Yujie Li, Min Chen, Hyoungseop Kim, Seiichi Serikawa
2017 arXiv   pre-print
In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India.  ...  We will also conduct demonstrations of the developed BI intelligence learning model on automatic driving, precision medical care, and industrial robots.  ...  Amazon uses artificial intelligence for autonomous robots in delivery systems [5] .  ... 
arXiv:1706.01040v1 fatcat:hjjwpn4r6ff7vggvb4nskqisma

Real-time 3D Traffic Cone Detection for Autonomous Driving [article]

Ankit Dhall, Dengxin Dai, Luc Van Gool
2019 arXiv   pre-print
It runs efficiently on the low-power Jetson TX2, providing accurate 3D position estimates, allowing a race-car to map and drive autonomously on an unseen track indicated by traffic cones.  ...  This work investigates traffic cones, an object class crucial for traffic control in the context of autonomous vehicles. 3D object detection using images from a monocular camera is intrinsically an ill-posed  ...  We would like to thank AMZ Driverless team for their support. The work is also supported by Toyota Motor Europe via the project TRACE-Zurich.  ... 
arXiv:1902.02394v2 fatcat:zeydtkbsdrbwbjyz7dpgicxdeu

Revising the evolutionary computation abstraction

Joel Lehman, Kenneth O. Stanley
2010 Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO '10  
Though based on abstractions of nature, current evolutionary algorithms and artificial life models lack the drive to complexity characteristic of natural evolution.  ...  This abstraction leads to the key idea in this paper: Searching for novel ways of meeting the same minimal criteria, which is an accelerated model of this new abstraction, may be an effective search algorithm  ...  The field of biology aims primarily to decipher the vast complexity discovered Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee  ... 
doi:10.1145/1830483.1830503 dblp:conf/gecco/LehmanS10 fatcat:vbtlqn2h4jbmpgg7hs6dkaadci

Evolutionary Robotics: What, Why, and Where to

Stephane Doncieux, Nicolas Bredeche, Jean-Baptiste Mouret, Agoston E. (Gusz) Eiben
2015 Frontiers in Robotics and AI  
We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work.  ...  The use of robots as a substrate can help to address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies.  ...  These issues are receiving much attention, and serving to drive further developments in the field.  ... 
doi:10.3389/frobt.2015.00004 fatcat:xwwgonhohbh25dsaoofnps7wvq

Conference Guide [Front matter]

2020 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)  
To complete the classification task, we propose the attention block in the attention-fusion classifier, which is effective to fuse and encode the feature and attention in an end-to-end manner.  ...  However, current research in the field of reinforcement learning for autonomous driving is mainly focused on highway setup with little to no emphasis on urban environments.  ...  In this paper we investigate the resilient consensus problem for multi-agent systems under the specific attack scenarios where the attacker can eavesdrop on initial information of agents among the system  ... 
doi:10.1109/icarcv50220.2020.9305477 fatcat:4h7gpoj7ljgsrlkjoyw3qcfzxi

Abandoning Objectives: Evolution Through the Search for Novelty Alone

Joel Lehman, Kenneth O. Stanley
2011 Evolutionary Computation  
By decoupling open-ended search from artificial life worlds, the search for novelty is applicable to real world problems.  ...  capture open-endedness, the idea is to simply search for behavioral novelty.  ...  and hence the field is beginning to encounter the limits of what the objective-based paradigm has to offer.  ... 
doi:10.1162/evco_a_00025 pmid:20868264 fatcat:jvqwuapazzerthz47rxucli4zm

Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review [article]

Abolfazl Razi, Xiwen Chen, Huayu Li, Hao Wang, Brendan Russo, Yan Chen, Hongbin Yu
2022 arXiv   pre-print
This paper explores Deep Learning (DL) methods that are used or have the potential to be used for traffic video analysis, emphasizing driving safety for both Autonomous Vehicles (AVs) and human-operated  ...  Our main goal is to guide traffic analysts to develop their own custom-built processing frameworks by selecting the best choices for each step and offering new designs for the lacking modules by providing  ...  Acknowledgment We would like to thank Drs. Junsuo Qu and Greg Leeming for his insightful comments.  ... 
arXiv:2203.10939v2 fatcat:oml733wvjfh3blne4h7kg5y3du

Computational Intelligence in Games

2005 IEEE Transactions on Neural Networks  
This approach can be used to construct adaptive characters in existing video games, and it can serve as a foundation for a new genre of games based on machine learning.  ...  This article reviews the achievements and future prospects of one particular approach, that of evolving neural networks, or neuroevolution.  ...  Acknowledgments Thanks to David Aha and Matthew Molineaux for providing the TIELT platform, for Thomas D'Silva and Craig Varrichio for help with the TIELT experiments, and for Aliza Gold and the entire  ... 
doi:10.1109/tnn.2005.845548 fatcat:jrts7sojfzarroiv3wsdefajom

Computational Intelligence in Games 2014

2013 IEEE Transactions on Computational Intelligence and AI in Games  
This approach can be used to construct adaptive characters in existing video games, and it can serve as a foundation for a new genre of games based on machine learning.  ...  This article reviews the achievements and future prospects of one particular approach, that of evolving neural networks, or neuroevolution.  ...  Acknowledgments Thanks to David Aha and Matthew Molineaux for providing the TIELT platform, for Thomas D'Silva and Craig Varrichio for help with the TIELT experiments, and for Aliza Gold and the entire  ... 
doi:10.1109/tciaig.2013.2280882 fatcat:tqujapx735fhhdlqs3oqoooaii

Towards behaviour based testing to understand the black box of autonomous cars

Fabian Utesch, Alexander Brandies, Paulin Pekezou Fouopi, Caroline Schießl
2020 European Transport Research Review  
It is argued that penetration testing can be applied to identify weaknesses of the system. Both can be applied to improve autonomous driving systems.  ...  DNNs excel in identifying objects in sensor data which is essential for autonomous driving. These networks build their decision logic through training instead of explicit programming.  ...  für Verkehrssystemtechnik, DLR Braunschweig) for his insight about autonomous driving.  ... 
doi:10.1186/s12544-020-00438-2 fatcat:i6ash7qmzzgzhfuzlfelygmysm

A Review of Deep-Learning-Based Medical Image Segmentation Methods

Xiangbin Liu, Liping Song, Shuai Liu, Yudong Zhang
2021 Sustainability  
Now it has become an important research direction in the field of computer vision.  ...  For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low.  ...  The neurons are connected to each other in a certain way to form the entire deep neural network. The emergence of neural networks makes end-to-end image processing possible.  ... 
doi:10.3390/su13031224 fatcat:pn2qbyv53zbuhhiuem2pc4dg3u
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