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Learning Situational Driving

Eshed Ohn-Bar, Aditya Prakash, Aseem Behl, Kashyap Chitta, Andreas Geiger
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Motivated by this observation, we develop a framework for learning a situational driving policy that effectively captures reasoning under varying types of scenarios.  ...  Our key idea is to learn a mixture model with a set of policies that can capture multiple driving modes.  ...  Situational Driving Model We now describe our situational driving model which facilitates efficient learning of diverse driving behaviors, e.g., fast driving in an empty road vs. driving cautiously in  ... 
doi:10.1109/cvpr42600.2020.01131 dblp:conf/cvpr/Ohn-BarPBCG20 fatcat:4jxbpkfxhzdxxbf4py7pfhmchm

Learning driving situations and behavior models from data

Matthias Platho, Horst-Michael Gross, Julian Eggert
2013 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)  
Current methods for situation recognition usually rely on an expert for defining the considered driving situations manually while solely the parameters of the corresponding behavior models are learned  ...  In order to circumvent these problems, we propose to learn types of situations and behavior models from data simultaneously.  ...  learned driving situations (BMLVP-Orig).  ... 
doi:10.1109/itsc.2013.6728245 dblp:conf/itsc/PlathoGE13 fatcat:zdubsxqjara6faabxb2rm2flhy

Classifying Cognitive Load and Driving Situation with Machine Learning

Yutaka Yoshida, Hayato Ohwada, Fumio Mizoguchi, Hirotoshi Iwasaki
2014 International Journal of Machine Learning and Computing  
Index Terms-Driver's cognitive load, eye movement, machine learning, driving task.  ...  This paper classifies a driver's cognitive state in real driving situations to improve the in-vehicle information service that judges a user's cognitive load and driving situation.  ...  The driving situation determines to what degree the user should concentrate on the driving task.  ... 
doi:10.7763/ijmlc.2014.v4.414 fatcat:pgxfnfk26jhovf6d3ee2fwmwgu

Detection of abnormal driving situations using distributed representations and unsupervised learning

Florian Mirus, Terrence C. Stewart, Jörg Conradt
2020 The European Symposium on Artificial Neural Networks  
In this paper, we present an anomaly detection system employing an unsupervised learning model trained on the information encapsulated within distributed vector representations of automotive scenes.  ...  In automotive context, the main application domain beside production plant diagnosis [3] is the detection of abnormal driving situations.  ...  Introduction In this paper, we investigate the information encapsulated within distributed vector representations of automotive scenes and if they can be used to detect potentially dangerous driving situations  ... 
dblp:conf/esann/MirusSC20 fatcat:wvoyqcbxe5cxrpqbl6f2ukzkkm

A theory of emotionally based drive (D) and its relation to performance in simple learning situations

Kenneth W. Spence
1958 American Psychologist  
doi:10.1037/h0045054 fatcat:4je6ozimpnhlpnq2sk6jqm3ioi

Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population

Al-Akhir Nayan, Boonserm Kijsirikul, Yuji Iwahori
2022 International Journal of Power Electronics and Drive Systems (IJPEDS)  
The model presents a report about the risky situation and impending coronavirus disease (COVID-19) attack.  ...  This study distinguishes machine learning models and creates a prediction system to anticipate the infected and death rate for the coming days.  ...  We have tried to make advanced predictions through machine learning techniques to help the authorities understand the upcoming situation.  ... 
doi:10.11591/ijece.v12i4.pp4217-4227 fatcat:d22nho6fybg7dcnyjhldqxfcjy

Analysis of the Current Situation and Driving Factors of College Students' Autonomous Learning in the Network Environment

Ruikun Zheng, Fei Li, Ling Jiang, Shuman Li
2022 Frontiers in Humanities and Social Sciences  
autonomous learning attitude and the status of autonomous learning ability, and it is concluded that the factors driving autonomous learning of college students include perfect supervision mechanism,  ...  This paper analyzes the current situation and characteristics of college students' autonomous learning in the network environment, the status of autonomous learning resources acquisition, the status of  ...  Through the analysis of the current situation of college students' autonomous learning ability, this paper starts from the adjustment mechanism to explore the driving factors of college students' autonomous  ... 
doi:10.54691/fhss.v2i7.1306 fatcat:vak7ucykobfm3k34gp26ywn3em

Detection of road objects with small appearance in images for autonomous driving in various traffic situations using a deep learning based approach

Guofa Li, Heng Xie, Weiquan Yan, Yunlong Chang, Xingda Qu
2020 IEEE Access  
This large-scale dataset includes various traffic situations in naturalistic driving and has been widely used in environment perception studies for AVs [39] .  ...  The lightweight of our method better supports its practical application in autonomous driving.  ... 
doi:10.1109/access.2020.3036620 fatcat:zjp6yxa245axjjn4yzlu47glr4

The Role of Simulation in a Staged Learning Model for Novice Driver Situational Awareness Training

Loren Staplin, James C Dowdell
2001 Proceedings of the First International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design: driving assessment 2001   unpublished
The success of applying such models hinges upon information presentation techniques that can maximize depth of processing, and hence comprehension and retention, at a specific stage of learning.  ...  This paper theorizes that an optimal strategy for training novice drivers to acquire situational awareness skills will rely on a hierarchical approach consistent with traditional models of cognitive development  ...  It also depends upon a shift from perceiving a driving situation strictly through one's own eyes; to an ability to visualize one's actions as perceived by others; to a complete understanding of the interactions  ... 
doi:10.17077/drivingassessment.1052 fatcat:krpx7sgnxvg6los7txokvux53u

Using Agents to Create Learning Opportunities in a Collaborative Learning Environment [chapter]

Yongwu Miao, Ulrich Hoppe, Niels Pinkwart, Oliver Schilbach, Sabine Zill, Tobias Schloesser
2006 Lecture Notes in Computer Science  
In order to foster situated learning in a virtual community of practice, we developed a multi-user, real-time, 3D car-driving simulation environment.  ...  In such a situation-based learning environment, the availability of enough appropriate learning situations is crucial for success.  ...  These situations provide learners with learning opportunities, and thus indirectly affect the learning processes.  ... 
doi:10.1007/11774303_104 fatcat:kjt4s4aqebcivnn54cmfo5qaty

The externalization of drive. I. Theoretical considerations

E. E. Anderson
1941 Psychological review  
If this internally aroused drive is satisfied over a long period of time in a relatively constant external situation, then the drive mechanism will become aroused by this external situation.  ...  Other external situations, E-z, E-3, E-4, etc., may, by being associated with I-1, I-2, E-1, etc., come to arouse the drive X. (4) The drive having be- come dependent upon a given external situation, say  ... 
doi:10.1037/h0062656 fatcat:2xwhztzz35bnvhgnec5pit3uxq

The Virtual Driving Coach - design and preliminary testing of a predictive eco-driving assistance system for heavy-duty vehicles

Daniel Heyes, Thomas J. Daun, Andreas Zimmermann, Markus Lienkamp
2015 European Transport Research Review  
Furthermore, the results point towards a positive correlation between user acceptance and the subjects' judgment of learning.  ...  Therefore, an eco-driving assistance system (EDAS) is developed in order to support the driver in sustainably maintaining an efficient driving stylethe Virtual Driving Coach (ViDCo).  ...  Driving error detection For every situation relevant for eco-driving, an optimal driving strategy is defined.  ... 
doi:10.1007/s12544-015-0174-4 fatcat:ys2wvqadqjcahkvieb6swrln54

Toward Self-Referential Autonomous Learning of Object and Situation Models

Florian Damerow, Andreas Knoblauch, Ursula Körner, Julian Eggert, Edgar Körner
2016 Cognitive Computation  
This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome.  ...  Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize  ...  leaving initial driving with ped else R leaving P leaving Policy Learning ahigh drive drive drive drive approaching z.c.  ... 
doi:10.1007/s12559-016-9407-7 pmid:27563358 pmcid:PMC4981634 fatcat:ngyb3iagebdhliqluh67zfm3ta

Page 455 of None Vol. 58, Issue 6 [page]

1959 None  
That is, the increase in drive level is expended on all components of the learning situation.  ...  A theory of emotionally based drive (D) and its relation to perform- ance in simple learning situations. Psychologist, 1958, 13, 131-141. TayYLor, J. A. A personality scale of mani- fest anxiety.  ... 

Game interaction state graphs for evaluation of user engagement in explorative and experience-based training games

Hiran Ekanayake, Per Backlund, Tom Ziemke, Robert Ramberg, Kamalanath Hewagamage
2010 2010 International Conference on Advances in ICT for Emerging Regions (ICTer)  
This type of learning is more beneficial for practicing critical situations which are difficult or impossible in real world training, for instance experience the consequences of unsafe driving.  ...  For training education, simulators are considered as offering more realistic learning environments to experience situations that are similar to real world.  ...  For example, in a driving simulator learning game, the high speed driving is considered as more challenging than low speed driving.  ... 
doi:10.1109/icter.2010.5643272 fatcat:zeoq6wl6vzea5m2beivdrtaxji
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