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Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature Review

Nijat Rajabli, Francesco Flammini, Roberto Nardone, Valeria Vittorini
2020 IEEE Access  
Autonomous, or self-driving, cars are emerging as the solution to several problems primarily caused by humans on roads, such as accidents and traffic congestion.  ...  trustworthy AI and safe autonomy.  ...  For human drivers, the decision-making is 90% based on visual perception, and as a matter of fact, humans are not capable to be fully aware of potential hazards in the surrounding environment [2] .  ... 
doi:10.1109/access.2020.3048047 fatcat:7mgx34zscvfavenyznqmbul7cm

Is it Safe to Drive? An Overview of Factors, Challenges, and Datasets for Driveability Assessment in Autonomous Driving [article]

Junyao Guo, Unmesh Kurup, Mohak Shah
2018 arXiv   pre-print
With recent advances in learning algorithms and hardware development, autonomous cars have shown promise when operating in structured environments under good driving conditions.  ...  adverse environments.  ...  Once all the scenes are labeled safe or hazardous, another CNN model is trained to predict whether a new scene is safe or hazardous.  ... 
arXiv:1811.11277v1 fatcat:ztrxyydtuveijizfn6a2dmt5ui

The Dispute Over Safe Uses of X-rays in Medical Practice

Claire Nader
1975 Health Physics  
the Radiation Control for Health and Safety Act of 1968 by officials of the Department of Health, Education and Welfare are examined.  ...  The long-standing medical stewardship over diagnostic X-rays in these areas is found wanting.  ...  Depending on the classification, the training can vary from 3 to 24 months.  ... 
doi:10.1097/00004032-197507000-00023 pmid:1150456 fatcat:as2uu6kkbvgxhnpbl5lsosyc5i

Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO)

Lixin Yan, Yishi Zhang, Yi He, Song Gao, Dunyao Zhu, Bin Ran, Qing Wu
2016 Sensors  
Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data.  ...  Considering the safety of an on-road experiment and the difficulty of crash data collection in China, crash and near-crash events (events which appear in China's transportation industry standard JTT 916  ...  The relationship between influence factors from driver-vehicle-road-environment and traffic hazards has already been explored in a previous study.  ... 
doi:10.3390/s16071084 pmid:27420073 pmcid:PMC4970130 fatcat:jktvyvrfqzbnnm5sr5aqnuxpl4

Detecting Human Driver Inattentive and Aggressive Driving Behavior using Deep Learning: Recent Advances, Requirements and Open Challenges

Monagi H. Alkinani, Wazir Zada Khan, Quratulain Arshad
2020 IEEE Access  
After describing the background of deep learning and its algorithms, we present an in-depth investigation of most recent deep learning-based systems, algorithms, and techniques for the detection of Distraction  ...  INDEX TERMS Deep learning, human inattentive driving behavior, connected vehicles, road accident avoidance, abnormal behavior detection, distraction or aggressiveness detection, fatigue or drowsiness detection  ...  Safe driving behavior requires human driver to be alert and attentive while making fast cognitive decisions in a dynamically changing road environment.  ... 
doi:10.1109/access.2020.2999829 fatcat:5nxtzm6yfbe4jf6nqgreqw45r4

A taxonomy for autonomous vehicles for different transportation modes

Marialena Vagia, Ørnulf Jan Rødseth
2019 Journal of Physics, Conference Series  
Different autonomous vehicles that are used in different environments, constrained or not, like roads, rails, overwater, underwater, air, need to have different capabilities and characteristics and in  ...  However, there is some common base between the different taxonomies that are proposed for various vehicles and it would be beneficial to try and learn from the experience of the approaches proposed.  ...  Acknowledgements The paper is based on investigations and results carried within the ASTAT and SAREPTA projects at SINTEF in Trondheim.  ... 
doi:10.1088/1742-6596/1357/1/012022 fatcat:cedp2pb7afgxhiya2qyiqlh6ja

Abstracts

2020 IEEE Transactions on Intelligent Vehicles  
In the context of autonomous driving, where humans may need to take over in the event where the computer may issue a takeover request, a key step towards driving safety is the monitoring of the hands to  ...  Control of whole-body vibration (WBV) via a seat suspension in off-road vehicles is a challenging task due to the presence of severe external disturbances and parametric uncertainties.  ...  With augmentative images, the DDR system achieves an improvement of 11.45% on image classification performance in a driving simulation environment.  ... 
doi:10.1109/tiv.2020.2978681 fatcat:n7ifvfboe5crbdlqykb7rfwgk4

Conceptual Model for Connected Vehicles Safety and Security using Big Data Analytics

Noor Afiza Mat Razali, Nuraini Shamsaimon, Muslihah Wook, Khairul Khalil
2020 International Journal of Advanced Computer Science and Applications  
Data volume generated from the sensors and infrastructure in CVs environment are enormous.  ...  Thus, CVs implementations require a real-time big data processing and analytics to detect any anomaly in the CVs's environment which are physical layer, network layer and application layer.  ...  Norazman Mohamad Nor for precious contribution in provided their insight and expertise that greatly assisted towards the whole research activities.  ... 
doi:10.14569/ijacsa.2020.0111136 fatcat:mbkdp23rm5h77c43f2khoae37q

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc.  ...  Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.  ...  In level 4, it is the same to level 3, but no driver attention is ever required for safety, e.g. the driver may safely go to sleep or leave the driver's seat. B.  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

Repeated usage of a motorway automated driving function: Automation level and behavioural adaption

Barbara Metz, Johanna Wörle, Michael Hanig, Marcus Schmitt, Aaron Lutz, Alexandra Neukum
2021 Transportation Research Part F: Traffic Psychology and Behaviour  
In a driving simulator study, N = 61 drivers used an automated driving system for motorways during six experimental sessions.  ...  For most aspects, behavioural adaptation is independent of system level (e.g., for system evaluation, distribution of attention).  ...  Responsibility for the information and views set out in this publication lies entirely with the authors.  ... 
doi:10.1016/j.trf.2021.05.017 fatcat:4uxxku7umvaphlh54rhvbja7sq

Applications of Deep Learning Techniques for Pedestrian Detection in Smart Environments: A Comprehensive Study

Fen He, Paria Karami Olia, Rozita Jamili Oskouei, Morteza Hosseini, Zhihao Peng, Touraj BaniRostam, Chunjia Han
2021 Journal of Advanced Transportation  
Many studies in this field have been done by various researchers, but there are still many errors in the accurate detection of pedestrians in self-made cars made by different car companies, so in the research  ...  in this study, we focused on the use of deep learning techniques to identify pedestrians for the development of intelligent transportation systems and self-driving cars and pedestrian identification in  ...  maintaining road safety.  ... 
doi:10.1155/2021/5549111 fatcat:64ok37zu4vgbtoum3yxpmgm464

Child-Pedestrian Traffic Safety at Crosswalks—Literature Review

Aleksandra Deluka-Tibljaš, Sanja Šurdonja, Irena Ištoka Otković, Tiziana Campisi
2022 Sustainability  
Child pedestrians make up 30% of the total number of children injured in road traffic in the EU.  ...  This paper provides an overview of research of parameters that affect the safety of children in the conflict zones of the intersection—crosswalks.  ...  the urban transport network" and by the project "Transport infrastructure in the function of sustainable mobility" (uniri-tehnic-18-143-1289) supported by the University of Rijeka, Croatia.  ... 
doi:10.3390/su14031142 fatcat:nb44ba2uejfxllr5xn3cexuug4

Dynamic and Systematic Survey of Deep Learning Approaches for Driving Behavior Analysis [article]

Farid Talebloo, Emad A. Mohammed, Behrouz H. Far
2021 arXiv   pre-print
In this regard, we try to create a dynamic survey paper to review and present driving behaviour survey data for future researchers in our research.  ...  Improper driving results in fatalities, damages, increased energy consumptions, and depreciation of the vehicles. Analyzing driving behaviour could lead to optimize and avoid mentioned issues.  ...  The most vital aspect of on-road driving safety is the behaviour of drivers.  ... 
arXiv:2109.08996v1 fatcat:r2faox3pdrfedb72ewkecpp64a

Towards Better Driver Safety: Empowering Personal Navigation Technologies with Road Safety Awareness [article]

Runsheng Xu, Shibo Zhang, Yue Zhao, Peixi Xiong, Allen Yilun Lin, Brent Hecht, Jiaqi Ma
2021 arXiv   pre-print
Based on this road safety definition, we then developed a machine learning-based road safety classifier that predicts the safety level for road segments using a diverse feature set constructed only from  ...  Evaluations in four different countries show that our road safety classifier achieves satisfactory performance.  ...  drivers for abnormal road environments (e.g., [16]).  ... 
arXiv:2006.03196v5 fatcat:gxj2kt3vqfdjroraoa47jeowmm

2012 Index IEEE Transactions on Intelligent Transportation Systems Vol. 13

2012 IEEE transactions on intelligent transportation systems (Print)  
., FPGA-Based Track Circuit for Railways Using Transmission Encoding; TITS June 2012 437-448 Hernandez, N., see 1167-1178 Herrera, F., see Cobo, M.  ...  ., +, TITS March 2012 154-165 Unsupervised learning Robust Road Detection and Tracking in Challenging Scenarios Based on Markov Random Fields With Unsupervised Learning.  ...  ., +, TITS Dec. 2012 1498-1506 Robust Road Detection and Tracking in Challenging Scenarios Based on Markov Random Fields With Unsupervised Learning.  ... 
doi:10.1109/tits.2012.2230475 fatcat:ykhillnzynf7vhfonoyzcohsya
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