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Normal and risky driving patterns identification in clear and rainy weather on freeway segments using vehicle kinematics trajectories and time series cluster analysis

Elhashemi M. Ali, Mohamed M. Ahmed, Guangchuan Yang
2020 IATSS Research  
This paper introduces one on the new analysis protocol of identifying and discriminating between normal and risky driving in clear and rainy weather.  ...  Statistical results showed that risky driving patterns started on average one second earlier in rainy weather conditions than in clear weather conditions.  ...  sponsored by the Federal Highway Administration (FHWA) in cooperation with the American Association of State Highway and Transportation Officials (AASHTO).  ... 
doi:10.1016/j.iatssr.2020.07.002 fatcat:bbvuvpu3ordy3lirefgkdl7lii

Towards Driver's State Recognition on Real Driving Conditions

George Rigas, Yorgos Goletsis, Panagiota Bougia, Dimitrios I. Fotiadis
2011 International Journal of Vehicular Technology  
In this work a methodology for detecting drivers' stress and fatigue and predicting driving performance is presented.  ...  The results obtained from the combination of physiological signals, video features, and driving environment parameters indicate high classification accuracy (88% using three fatigue scales and 86% using  ...  real conditions).  ... 
doi:10.1155/2011/617210 fatcat:f6fyl5dqyvbb3kh5gne2s46sx4

Learning to Drive by Watching YouTube Videos: Action-Conditioned Contrastive Policy Pretraining [article]

Qihang Zhang, Zhenghao Peng, Bolei Zhou
2022 arXiv   pre-print
In this work, we aim to pretrain policy representations for driving tasks by watching hours-long uncurated YouTube videos.  ...  Deep visuomotor policy learning, which aims to map raw visual observation to action, achieves promising results in control tasks such as robotic manipulation and autonomous driving.  ...  ACO learns representation based on both ICP and ACP, where ICP focuses on learning discriminative general visual feature and ACP focuses on policy-relevant feature.  ... 
arXiv:2204.02393v2 fatcat:vrcqjo7ndnchvedbexma7qgwxi

Advanced Visual Analyses for Smart and Autonomous Vehicles

Zhijun Fang, Jenq-Neng Hwang, Shih-Chia Huang
2018 Advances in Multimedia  
More specifically, this special issue focuses on state-of-the-art researches of integrating advanced visual analysis techniques, which can be effectively applied to vehicle and driver sensing, road and  ...  "EVD" system components affect the overall safety and comfort of driving, as well as the condition of the traffic flow.  ... 
doi:10.1155/2018/1762428 fatcat:zfhljk3hdndxbnmej2zzgg56ry

Predicting the Driver's Focus of Attention: the DR(eye)VE Project

Andrea Palazzi, Davide Abati, Simone Calderara, Francesco Solera, Rita Cucchiara
2018 IEEE Transactions on Pattern Analysis and Machine Intelligence  
To this end we propose a new computer vision model based on a multi-branch deep architecture that integrates three sources of information: raw video, motion and scene semantics.  ...  The indication of which elements in the scene are likely to capture the driver's attention may benefit several applications in the context of human-vehicle interaction and driver attention analysis.  ...  As expected, the D KL value in rainy weather (1.53) is significantly lower than the ones for cloudy (1.61) and sunny weather (1.75), highlighting that when rainy the driver is more focused on the road  ... 
doi:10.1109/tpami.2018.2845370 pmid:29994193 fatcat:ccfjckk3yrhmvfvqjr3drpzchy

A Review and Comparative Analysis of Recent Advancements in Traffic Sign Detection and Recognition Techniques

Khyati Chourasia, Jitendra N. Chourasia
2015 SAMRIDDHI A Journal of Physical Sciences Engineering and Technology  
The practical difficulty that arises in actual time traffic sign is summarized. It describes also the techniques used for the detection, recognition and classification of the traffic signs.  ...  Most of the researcher used different type of Neural Network for recognition and classification. Some of the authors used fuzzy classifier and genetic algorithm.  ...  Kehtarnavaz and Ahmad [14] used a discriminant analysis on the YIQ color space for detecting various road signs from videos.  ... 
doi:10.18090/samriddhi.v2i1.1594 fatcat:sjsnc7a5fbeynlylj47dscpwre

Detection of Text on Road Signs From Video

W. Wu, X. Chen, J. Yang
2005 IEEE transactions on intelligent transportation systems (Print)  
A fast and robust framework for incrementally detecting text on road signs from video is presented in this paper.  ...  It can easily be applied to other tasks of text detection from video and potentially be embedded in a driver assistance system.  ...  Chen, anonymous reviewers, and the Associate Editor for their helpful comments and suggestions. The authors also gratefully acknowledge the assistance of J.  ... 
doi:10.1109/tits.2005.858619 fatcat:gortgesqbfha3au33qoyttttf4

Sensors on the Move: Onboard Camera-Based Real-Time Traffic Alerts Paving the Way for Cooperative Roads

Olatz Iparraguirre, Aiert Amundarain, Alfonso Brazalez, Diego Borro
2021 Sensors  
In this context, Cooperative Intelligent Transport Systems (C-ITS) are expected to significantly improve road safety, traffic efficiency and comfort of driving, by helping the driver to make better decisions  ...  The selected models for TSR implementation are based on Aggregated Chanel Features (ACF) and Convolutional Neural Networks (CNN) that reach more than 90% accuracy in real time.  ...  It records 10,000 km of driving in Northern Europe under different weather and illumination conditions in February and December 2019.  ... 
doi:10.3390/s21041254 pmid:33578740 pmcid:PMC7916518 fatcat:gjzrqsepnff2fn2kesdwl54fwe

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Lin Hu, Jian Ou, Jing Huang, Yimin Chen, Dongpu Cao
2020 IEEE Access  
The major challenges are accurately perceiving the road traffic environment, detecting the potential traffic conflicts, and proposing the alternative driving strategies.  ...  The intelligent vehicles can perceive the surrounding environment, extract road condition information, and detect obstacles for avoiding collisions or mitigating accidents.  ...  His research focuses on vehicle dynamics and control, driver cognition, automated driving, and parallel driving, where he has contributed more than 150 publications and one U.S. patent. Dr.  ... 
doi:10.1109/access.2020.2970164 fatcat:rd44et55sfgffb2dakzcat6wmq

Are happy drivers safer drivers? Evidence from hazard response times and eye tracking data

Tatjana Zimasa, Samantha Jamson, Brian Henson
2017 Transportation Research Part F: Traffic Psychology and Behaviour  
Previous research shows that negative emotions have a detrimental effect on cognitive processes in general and on driving safety in particular.  ...  This research examined the influence of mood on driving safety using hazard perception videos an P mood was manipulated (Sad, Neutral, Happy) after which they had to observe videos containing a number  ...  Shinar and N. Meiran. 2012. Situational (state)  ... 
doi:10.1016/j.trf.2016.12.005 fatcat:4dsigolxizh6zo5gaaejfkph7i

SVM-Based Real-Time Identification Model of Dangerous Traffic Stream State

Ming Huang
2022 Wireless Communications and Mobile Computing  
By comparing and studying the correlation between traffic stream parameters and traffic safety of different highways, the correlations of traffic natural quantity, traffic equivalent, passenger-cargo ratio  ...  This paper studies the risk early warning model of road traffic accidents, which can transform the problem of road traffic safety into active early warning and improve the level of traffic safety.  ...  Traffic stream characteristics differ in space; that is, they differ in different locations affected by weather, visibility, and road alignment conditions, but they are similar in different sections of  ... 
doi:10.1155/2022/6260395 doaj:72d37795da9847b2b8ba6aedda8c999c fatcat:ljpisvsy7zcd7kijpe6x577l7a

Weather and Light Level Classification for Autonomous Driving: Dataset, Baseline and Active Learning [article]

Mahesh M Dhananjaya, Varun Ravi Kumar, Senthil Yogamani
2021 arXiv   pre-print
There is no public dataset for weather and light level classification focused on autonomous driving to the best of our knowledge.  ...  One of the foremost outstanding hurdles is to obtain robust visual perception in harsh weather and low light conditions where accuracy degradation is severe.  ...  Road safety analysis should include the system behavior in these challenging conditions.  ... 
arXiv:2104.14042v3 fatcat:bbu5iqup5ndijnsfdsjs2vgaxq

International Large-Scale Vehicle Corpora for Research on Driver Behavior on the Road

Kazuya Takeda, John H. L. Hansen, Pınar Boyraz, Lucas Malta, Chiyomi Miyajima, Hüseyin Abut
2011 IEEE transactions on intelligent transportation systems (Print)  
This paper considers a comprehensive and collaborative project to collect large amounts of driving data on the road for use in a wide range of areas of vehicle-related research centered on driving behavior  ...  While most efforts on in-vehicle research are generally focused within individual countries, this effort links a collaborative team from three diverse regions (i.e., Asia, American, and Europe).  ...  We can see three video windows (two focused on the driver and one on the road ahead) and listen to three audio microphones signals (close talking, rearview mirror mounted, and mobile phone).  ... 
doi:10.1109/tits.2011.2167680 fatcat:mhm7bmb54jhi3g6r5zjgbw3vve

Predicting Driver Self-Reported Stress by Analyzing the Road Scene [article]

Cristina Bustos, Neska Elhaouij, Albert Sole-Ribalta, Javier Borge-Holthoefer, Agata Lapedriza, Rosalind Picard
2021 arXiv   pre-print
) end-to-end image classification; and (3) end-to-end video classification.  ...  0.33 when tested on a set of nine drivers.  ...  with eyes closed, driving on a highway under optimal conditions (dry pavement, no traffic or construction, and good weather), and city driving in a busy area.  ... 
arXiv:2109.13225v1 fatcat:fyuz7wsfirgidgoe5zvjgdzkky

Driver Stress State Evaluation by Means of Thermal Imaging: A Supervised Machine Learning Approach Based on ECG Signal

Daniela Cardone, David Perpetuini, Chiara Filippini, Edoardo Spadolini, Lorenza Mancini, Antonio Maria Chiarelli, Arcangelo Merla
2020 Applied Sciences  
Thermal imaging was acquired during an experiment on a driving simulator, and thermal features of stress were investigated with comparison to a gold-standard metric (i.e., the stress index, SI) extracted  ...  The ROC analysis showed a good classification performance with an AUC of 0.80, a sensitivity of 77%, and a specificity of 78%.  ...  The experimental session consisted of 45 min of urban context driving with pre-established weather and traffic conditions.  ... 
doi:10.3390/app10165673 fatcat:hn3mlsi4cfd7naaksc3bmmnmh4
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