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Extracting Human-like Driving Behaviors From Expert Driver Data Using Deep Learning
2020
IEEE Transactions on Vehicular Technology
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Deep learning techniques were used to extract latent features from the collected data. ...
This paper introduces a method to extract driving behaviors from a human expert driver which are applied to an autonomous agent to reproduce proactive driving behaviors. ...
Other methods attempt to learn how to drive from human drivers themselves [33] . ...
doi:10.1109/tvt.2020.2980197
fatcat:u3zlhuxkbzgrvogec23evfy22i
Introduction of Human Assistance in Self-Driving Car
2021
Journal of University of Shanghai for Science and Technology
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The present scenery of human being is addicted to automation and machine learning technology like medical, transportation and in IT sector. ...
From the past few years, updating automation technology day by day and using all aspects in regular human life. ...
Conclusion The Human assistance Model in self-driven car discussed in the paper provides a detailed information about how we can use human assistance System to get better functionality in self-driving ...
doi:10.51201/jusst/21/08425
fatcat:43j7l3r4aremze3vtozjhzrigq
Safe, efficient and socially-compatible decision of automated vehicles: a case study of unsignalized intersection driving
[article]
2022
arXiv
pre-print
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Human-in-the-loop experiments are carried out, in which 24 subjects are invited to drive and interact with AVs deployed with the proposed algorithm and two comparison algorithms. ...
A game-theoretic decision algorithm considering social compatibility is proposed to handle the interaction with a human-driven truck at an unsignalized intersection. ...
[11] obtained some reference speed profiles of specific styles based on human driving data clustering, which were used to achieve human-like driving in complex interactions. Chen et al. ...
arXiv:2111.02977v2
fatcat:tgqk6gk2krde3fb6vohh2jfwhe
Older Adults with Mild Cognitive Impairments Show Less Driving Errors after a Multiple Sessions Simulator Training Program but Do Not Exhibit Long Term Retention
2016
Frontiers in Human Neuroscience
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to indicate a lane change, to verify a blind spot, or to engage in a visual search before crossing an intersection). ...
The aim of the study was to provide support to the claim that individuals with MCI can benefit from a training program and improve their overall driving performance in a driving simulator. ...
ACKNOWLEDGMENTS This research has received support from the Alzheimer Society of Canada. CH and SD are both Research Scholars from the Fonds de la Recherche du Québec-Santé. ...
doi:10.3389/fnhum.2016.00653
pmid:28082883
pmcid:PMC5186807
fatcat:cugu6fnzwbfahdkmsppj26vfei
Modeling risk anticipation and defensive driving on residential roads with inverse reinforcement learning
2014
17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
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In this work, we provide a new framework of modeling risk anticipation and defensive driving with inverse reinforcement learning (IRL). ...
Experimental results using actual driver maneuver data over 20 km of residential roads indicate that our approach is successful in terms of providing precise learning models of risk anticipation and defensive ...
ACKNOWLEDGEMENTS We would like to sincerely thank Mr. ...
doi:10.1109/itsc.2014.6957937
dblp:conf/itsc/ShimosakaKN14
fatcat:colfut3a2zctdhpklydx47wcsa
BlindSpotNet: Seeing Where We Cannot See
[article]
2022
arXiv
pre-print
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We instead propose to learn to estimate blind spots in 2D, just from a monocular camera. We achieve this in two steps. ...
The key idea is to reason in 3D but from 2D images by defining blind spots as those road regions that are currently invisible but become visible in the near future. ...
How can we accomplish 2D blind spot detection? Just like we likely do, we could learn to estimate blind spots directly in 2D. ...
arXiv:2207.03870v1
fatcat:nhexzbnqfjd3bffqsts4kx635y
End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners
[chapter]
2018
Lecture Notes in Computer Science
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In particular, we develop a sensor setup that provides data for a 360-degree view of the area surrounding the vehicle, the driving route to the destination, and low-level driving maneuvers (e.g. steering ...
Keywords: Autonomous driving · end-to-end learning of driving · route planning for driving · surround-view cameras · driving dataset ...
driving according to the speed of human driving; and 2) intersection scenarios by human annotation. ...
doi:10.1007/978-3-030-01234-2_27
fatcat:5wfbfiegcrbn3c46fwyu4yyaqy
Autonomous Vehicles and Vulnerable Road-Users—Important Considerations and Requirements Based on Crash Data from Two Countries
2021
Behavioral Sciences
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vulnerable road-users, for a variety of reasons. (2) Crash data were analysed in two countries (Great Britain and Australia) to examine some challenging traffic scenarios that are prevalent in both countries ...
However, the full effects of offering such systems, which may allow for drivers to become less than 100% engaged with the task of driving, may have detrimental impacts on other road-users, particularly ...
humans from the responsibility of driving. ...
doi:10.3390/bs11070101
fatcat:uvam76rgozahfnqyiu3z3z4qeq
End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners
[article]
2018
arXiv
pre-print
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In particular, we develop a sensor setup that provides data for a 360-degree view of the area surrounding the vehicle, the driving route to the destination, and low-level driving maneuvers (e.g. steering ...
Finally, we learn a novel driving model by integrating information from the surround-view cameras and the route planner. ...
driving according to the speed of human driving; and 2) intersection scenarios by human annotation. ...
arXiv:1803.10158v2
fatcat:6bgsca7qofhixdvnmwjgzy2idi
Semi-Autonomous Vehicles as a Cognitive Assistive Device for Older Adults
2019
Geriatrics
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Losing the capacity to drive due to age-related cognitive decline can have a detrimental impact on the daily life functioning of older adults living alone and in remote areas. ...
Semi-autonomous vehicles (SAVs) could have the potential to preserve driving independence of this population with high health needs. ...
Acknowledgments: We would like to acknowledge the coordination support of Karen de Libero and the technical help on the figures of Julie Oleynik. ...
doi:10.3390/geriatrics4040063
pmid:31744041
pmcid:PMC6961042
fatcat:xw3oj54m7fecdo3mbnkicglpbi
Learning in the age of algorithmic cultures
2017
E-Learning and Digital Media
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This Editorial describes the main challenges at the intersections between algorithmic cultures and human learning. ...
It suggests that studies of algorithms and learning are in their infancy and emphasizes that they carry potentials to confirm our existing ideas and surprise us with fresh insights. ...
In this Special Issue, guest editors Petar Jandric, Jeremy Knox, Hamish Macleod and Christine Sinclair have invited authors to explore the intersections between algorithmic cultures and human learning. ...
doi:10.1177/2042753017731237
fatcat:voswbox77vd6xkgxwytffmt54a
Sustainability in the Digital Age [Special Issue Introduction]
2020
IEEE technology & society magazine
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We would also like to thank Andrea Ventimiglia for her support in editing. Finally, we thank Nilufar Sabet-Kassouf for her coordination, research, and editing support.
Guest Editor Information ...
We also thank Jeremy Pitt for the invitation to produce this issue and thank him and the Managing Editor, Terri Bookman, for their patience in pulling this issue together during a difficult time for the ...
We include articles from researchers working on both the mechanics and ethics of AI and machine learning, analysts working on data and digital governance, scientists studying environmental and human dimensions ...
doi:10.1109/mts.2020.2991493
fatcat:v3cb6msyibgxtbknxlas6iftwm
Predicting driving behavior using inverse reinforcement learning with multiple reward functions towards environmental diversity
2015
2015 IEEE Intelligent Vehicles Symposium (IV)
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In recent years, modeling driving behavior in residential roads through inverse reinforcement learning (IRL) has been attracting attention in intelligent vehicle community thanks to the superiority of ...
However, it suffers from poor performance in diverse environment due to the fact that the single reward function could not handle all the environment with large diversity. ...
ACKNOWLEDGMENT We would like to sincerely thank Mr. Keita Sato and Mr. ...
doi:10.1109/ivs.2015.7225745
dblp:conf/ivs/ShimosakaNSK15
fatcat:wbtfd5aninh6dgl4lszmzhat24
Seeing Beyond the Line of Site – Controlling Connected Automated Vehicles
2017
Mechanical engineering (New York, N.Y. 1919)
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also when the lights will change, which may help it to decide how to approach an intersection [9] . ...
Connected automated vehicles are able to see around a blind corner when moving toward an intersection, and know whether any vehicle is approaching from other directions. ...
doi:10.1115/1.2017-dec-8
fatcat:hznccjl5b5fefjh6zftxaxfdoy
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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To achieve systems that can operate in a complex physical and social environment, they need to understand and learn how humans drive and interact with traffic scenes. ...
A novel annotation methodology is introduced to enable research on driver behavior understanding from untrimmed data sequences. ...
Learning how humans drive and interact with traffic scenes is a step toward intelligent transportation systems. In this paper, we start from a driver-centric view to describe driver behaviors. ...
doi:10.1109/cvpr.2018.00803
dblp:conf/cvpr/RamanishkaCMS18
fatcat:fry4tklws5agho6kk2gl5ynhym
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