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Learning Situational Driving
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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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
2013
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)
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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
2014
International Journal of Machine Learning and Computing
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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
2020
The European Symposium on Artificial Neural Networks
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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
1958
American Psychologist
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A THEORY OF EMOTIONALLY BASED DRIVE (D) AND ITS RELATION TO PERFORMANCE IN SIMPLE LEARNING SITUATIONS
KENNETH W. ...
and other learning situations. ...
doi:10.1037/h0045054
fatcat:4je6ozimpnhlpnq2sk6jqm3ioi
Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population
2022
International Journal of Power Electronics and Drive Systems (IJPEDS)
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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
2022
Frontiers in Humanities and Social Sciences
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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
2020
IEEE Access
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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
2001
Proceedings of the First International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design: driving assessment 2001
unpublished
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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]
2006
Lecture Notes in Computer Science
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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
1941
Psychological review
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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
2015
European Transport Research Review
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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
2016
Cognitive Computation
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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
Preserved Fulltext
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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
2010
2010 International Conference on Advances in ICT for Emerging Regions (ICTer)
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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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