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Predicting Hazardous Driving Events Using Multi-Modal Deep Learning Based on Video Motion Profile and Kinematics Data

Z. Gao, Y. Liu, J. Y. Zheng, R. Yu, X. Wang, P. Sun
2018 2018 21st International Conference on Intelligent Transportation Systems (ITSC)  
In this study, we develop a model based on a low-definition driving record instrument and the vehicle kinematic data for postaccident analysis by multi-modal deep learning method.  ...  Finally, a multi-modal deep convolutional neural network (DCNN) combined both video and kinematic data is developed to identify potential collision risk in each 12-second vehicle trip.  ...  Engineering Laboratory for Integrated Optimization of Road Traffic and Safety Analysis Technologies, and Chinese 111 Project (B17032).  ... 
doi:10.1109/itsc.2018.8569659 dblp:conf/itsc/GaoLZYWS18 fatcat:amv4u5gtvnacrcr4vqjuowaehi

Pedestrian Models for Autonomous Driving Part II: high level models of human behaviour [article]

Fanta Camara, Nicola Bellotto, Serhan Cosar, Florian Weber, Dimitris Nathanael, Matthias Althoff, Jingyuan Wu, Johannes Ruenz, André Dietrich, Gustav Markkula, Anna Schieben, Fabio Tango, Natasha Merat (+1 others)
2020 arXiv   pre-print
Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions.  ...  Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets  ...  The trajectory prediction is modeled as a goal-oriented motion planning. The whole system is based on deep-learning and trained via inverse reinforcement learning.  ... 
arXiv:2003.11959v1 fatcat:acjjwohahvdlxgy56j45fjtkdq

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

Abolfazl Razi, Xiwen Chen, Huayu Li, 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  ...  estimation, event analysis, modeling and anomaly detection.  ...  Jason Pacheco, Larry Head, and Junsuo Qu from their thoughtful comments on this paper. Special thanks go to Greg Leeming from Intel for his insightful comments and continued support of this project.  ... 
arXiv:2203.10939v1 fatcat:h4o5zghhhfezncn7luy56yjusm

Detection of Physical Strain and Fatigue in Industrial Environments Using Visual and Non-Visual Low-Cost Sensors

Konstantinos Papoutsakis, George Papadopoulos, Michail Maniadakis, Thodoris Papadopoulos, Manolis Lourakis, Maria Pateraki, Iraklis Varlamis
2022 Technologies  
information, the correlation and fusion of these estimations with synchronous worker heart rate data, as well as the prediction of near-future heart rate using deep learning-based techniques.  ...  Moreover, a new multi-modal dataset of video and heart rate data captured in a real manufacturing workplace during car door assembly activities is introduced.  ...  Acknowledgments: The authors thank Consortium partner Stellantis-Centro Ricerche FIAT (CRF)/ SPW Research & Innovation department in Melfi, Italy, for their valuable feedback in the implementation and  ... 
doi:10.3390/technologies10020042 fatcat:v5c6zwqueneqdbq6exsjxzt4im

Table of Contents

2022 IEEE Robotics and Automation Letters  
Ren, and S. Yang Multi-Modal Model Predictive Control Through Batch Non-Holonomic Trajectory Optimization: Application to Highway Driving . . . . . . . . . . . . . . . . . . . . . . . . . V. K.  ...  Havoutis Self-Supervised Depth and Ego-Motion Estimation for Monocular Thermal Video Using Multi-Spectral Consistency Loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/lra.2022.3165102 fatcat:enjzebowe5hn7hsfwklc7nieuy

Unmanned Aerial Vehicle for Remote Sensing Applications—A Review

Huang Yao, Rongjun Qin, Xiaoyu Chen
2019 Remote Sensing  
simultaneously using multi-sensor data for fusion.  ...  Based on these solutions, we provide a brief summary of existing examples of UAV-based RS in agricultural, environmental, urban, and hazards assessment applications, etc., and by discussing their practical  ...  Acknowledgments: This work was established at the Geospatial Data Analytics (GDA) group in the Department of Civil, Environmental and Geodetic Engineering (CEGE) at the Ohio State University (OSU).  ... 
doi:10.3390/rs11121443 fatcat:qlo6rpg2s5f6jd4lmy3ypvp4wq

Human Motion Trajectory Prediction: A Survey [article]

Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M. Kitani, Dariu M. Gavrila, Kai O. Arras
2019 arXiv   pre-print
We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual  ...  Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems.  ...  Lilienthal for valuable feedback and suggestions.  ... 
arXiv:1905.06113v3 fatcat:cnomix2fs5gqvb6ormldgti2bm

LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving [article]

Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, Raquel Urtasun
2021 arXiv   pre-print
Through extensive evaluations, we show that our model demonstrates significantly more diverse and sample-efficient motion forecasting in a large-scale self-driving dataset as well as safer and less-conservative  ...  In particular, we learn a diverse joint distribution over multi-agent future trajectories in a traffic scene that covers a wide range of future modes with high sample efficiency while leveraging the expressive  ...  Baselines: For motion forecasting, we use state-of-the-art baselines in multi-modal and diverse prediction, all of them trained end-to-end with the same backbone network and object detector architectures  ... 
arXiv:2101.06547v3 fatcat:gmgk2i2ghrf7lojthkl2pw5gzq

Main Achievements of the Multidisciplinary SINAPS@ Research Project: Towards an Integrated Approach to Perform Seismic Safety Analysis of Nuclear Facilities

C. Berge-Thierry, F. Voldoire, F. Ragueneau, F. Lopez-Caballero, A. Le Maoult
2019 Pure and Applied Geophysics  
of models available to describe physical phenomena (i.e., prediction of seismic motion, site effects, soil and structure interactions, linear and nonlinear wave propagation, material constitutive laws  ...  The main lessons learned from SINAPS@ are highlighted.  ...  The authors thank all of the SINAPS@ contributors, reseachers, engineers, PhD students, post-doctoral researchers, internships and technicians: the content of this article is based on their work.  ... 
doi:10.1007/s00024-019-02194-4 fatcat:izvgve7255ed7pltvrw7cd25yy

Autonomous Driving in Adverse Weather Conditions: A Survey [article]

Yuxiao Zhang, Alexander Carballo, Hanting Yang, Kazuya Takeda
2021 arXiv   pre-print
a holistic overview on the obstacles and directions of ADS development in terms of adverse weather driving conditions.  ...  Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer new possibilities for future transportation with higher efficiency and comfortable experiences.  ...  Pitropov et al. [312] and multi-layer deep learning approaches [292] are used presented the first AV dataset that focuses on snow con- in pedestrian detection tasks in bad weather.  ... 
arXiv:2112.08936v1 fatcat:hmgjhywy7rgx3fgrk6yxnu56ie

NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge [article]

Ali Agha, Kyohei Otsu, Benjamin Morrell, David D. Fan, Rohan Thakker, Angel Santamaria-Navarro, Sung-Kyun Kim, Amanda Bouman, Xianmei Lei, Jeffrey Edlund, Muhammad Fadhil Ginting, Kamak Ebadi (+60 others)
2021 arXiv   pre-print
; (iv) global motion planning and exploration behavior; (i) risk-aware mission planning; (vi) networking and decentralized reasoning; and (vii) learning-enabled adaptation.  ...  We discuss various components of the NeBula framework, including: (i) geometric and semantic environment mapping; (ii) a multi-modal positioning system; (iii) traversability analysis and local planning  ...  Institute for Occupational Safety and Health, Polytechnique Montreal, and West Virginia University.  ... 
arXiv:2103.11470v4 fatcat:rq2wgczzl5clphzgujjdbd3ywm

Modeling and Simulation of Sport Games, Sport Movements, and Adaptations to Training (Dagstuhl Seminar 15382)

Ricardo Duarte, Björn Eskofier, Martin Rumpf, Josef Wiemeyer, Marc Herbstritt
2016 Dagstuhl Reports  
For instance, computational models are applied in motor control and learning, biomechanics, game analysis, training science, sport psychology, and sport sociology.  ...  , Ricardo Duarte, Björn Eskofier, and Martin Rumpf Computational modeling and simulation are essential to analyze human motion and interaction in sport science, sport practice and sport industry.  ...  Two sensing modalities are in use for field studies of human movement: inertial sensing and video.  ... 
doi:10.4230/dagrep.5.9.38 dblp:journals/dagstuhl-reports/DuarteERW15 fatcat:bavxhyhkwfc57dtt7nux7wjoea

CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020

2020 International Journal of Computer Assisted Radiology and Surgery  
With an increasing general demand and pressure on CARS to also go fully digital in the long term, many members of the CARS Congress Organizing Committee, however, are more cautious and convinced that one  ...  Aiming to stimulate complimentary thoughts and actions on what is being presented at CARS, implies a number of enabling variables for optimal analogue scholarly communication, such as (examples given are  ...  Kimura and Dr. Nagaoka (BOST, Kindai University) for their technical assistance. The work is supported by a grant-in-aid for scientific research on innovative areas, JSPS KAKENHI 17K17680.  ... 
doi:10.1007/s11548-020-02171-6 pmid:32514840 fatcat:lyhdb2zfpjcqbf4mmbunddwroq

Visual Analysis in Traffic & Re-identification [article]

Andreas Møgelmose
2015 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
Acknowledgment The authors would like to thank their colleagues at the LISA lab for useful discussion and encouragement, especially Eshed Ohn-Bar for his valuable comments.  ...  Sujitha Martin, and Mr. Eshed Ohn-Bar for their comments.  ...  As opposed to the works described above, in this paper we introduce a truly multi-modal approach based on RGB, depth and thermal data.  ... 
doi:10.5278/ fatcat:taivrerts5debi734ddeeaq244

Deep learning-based ambient assisted living for self-management of cardiovascular conditions

Maria Ahmed Qureshi, Kashif Naseer Qureshi, Gwanggil Jeon, Francesco Piccialli
2021 Neural computing & applications (Print)  
learning strategies can be used to improve the medical services.  ...  The paper is divided into four main themes, including self-monitoring wearable systems, ambient assisted living in aged populations, clinician management systems and deep learning-based systems for cardiovascular  ...  Deep learning methods are helpful for better and superior performance, integration, feature learning, handling complex and multi-modality data.  ... 
doi:10.1007/s00521-020-05678-w fatcat:fkabjm33xza2ncgq6ecu2qifaq
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