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The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections [article]

Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein
2019 arXiv   pre-print
Therefore, we propose the creation of a comprehensive, large-scale urban intersection dataset with naturalistic road user behavior using camera-equipped drones as successor of the highD dataset.  ...  Compared to driving studies or ground-level infrastructure sensors, one major advantage of using a drone is the possibility to record naturalistic behavior, as road users do not notice measurements taking  ...  For example, recent road user behaviour models, which are used for prediction or simulation, use probabilistic approaches based on large scale datasets [2] , [11] .  ... 
arXiv:1911.07602v1 fatcat:icipstdlyne2jljufsfsnl3mke

Personalized Highway Pilot Assist Considering Leading Vehicle's Lateral Behaviours [article]

Daofei Li, Ao Liu
2021 arXiv   pre-print
Inspired by a finding on drivers' car-following preferences on lateral direction, a personalized highway pilot assist algorithm is proposed, which consists of an Intelligent Driver Model (IDM) based speed  ...  The proposed algorithm is validated through driver-in-the-loop experiment based on a moving-base simulator.  ...  Motivation: driving behaviour in car-following Findings from naturalistic driving The Highway Drone Dataset (highD) is a large-scale naturalistic vehicle trajectories dataset recorded at German highways  ... 
arXiv:2112.05913v1 fatcat:cig7ral5vjaa7p3zagvubw4qta

Identification of Driver Distraction Based on SHRP2 Naturalistic Driving Study

Zhiqiang Liu, Shiheng Ren, Mancai Peng
2021 Mathematical Problems in Engineering  
Firstly, some car following segments are obtained from the naturalistic driving database, and typical distracted segments are extracted by using situation awareness.  ...  The study provides a method for vehicle distraction warning system and driving risk propensity assessment.  ...  Acknowledgments is research was supported by the National Natural Science Foundation of China (61403172). e authors thank all the participants, school administrators, and local government who helped facilitate  ... 
doi:10.1155/2021/6699327 doaj:f422c0306f634fc4a798ff60aa6d4b9e fatcat:rjcs7imzqjdnxpfvozee7sv5ue

The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information

Matthias Beggiato, Josef F. Krems
2013 Transportation Research Part F: Traffic Psychology and Behaviour  
The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information.  ...  Effect of ADAS use on drivers' information processing and Situation Awareness. In A. Stevens, C. Brusque & J. Krems (Eds.) Driver adaptation to information and assistance systems (pp. 57-80).  ...  Realistic settings can be divided into four types: 1) Naturalistic driving studies (NDS): Participants usually drive an instrumented car for a certain period of time on their usual routes without any limiting  ... 
doi:10.1016/j.trf.2012.12.006 fatcat:sz6odsm5mfgrvc64aorsc6nogi

Autonomous Vehicle Evaluation: A Comprehensive Survey on Modeling and Simulation Approaches

Hesham Alghodhaifi, Sridhar Lakshmanan
2021 IEEE Access  
methods in some of the car-following, and lane-change studies when using specific models.  ...  Unfortunately, this approach is time-consuming and costly because one needs to drive thousands of miles to experience a police-reported collision and nearly millions of miles for a fatal crash.  ...  The integration of the two models provides a comprehensive car-following model that incorporates multiple leading vehicles [321] .  ... 
doi:10.1109/access.2021.3125620 fatcat:z4uj4riyorhu7hliv4sqvnz6n4

Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Model [article]

Tianyu Shi, Yifei Ai, Omar ElSamadisy, Baher Abdulhai
2022 arXiv   pre-print
Car following based on reinforcement learning has received attention in recent years with the goal of learning and achieving performance levels comparable to humans.  ...  Car following is a prime function in autonomous driving.  ...  In traffic flow theory, classic car-following models (CFMs) are based on physical knowledge and human behaviors, etc.  ... 
arXiv:2203.04749v2 fatcat:nhpv2vfzkna5hkfcyjtqfd2njq

Scanning the Issue

Azim Eskandarian
2019 IEEE transactions on intelligent transportation systems (Print)  
As demonstrated via the experiments, the proposed framework can predict unmet demand for on-demand services effectively and flexibly. Electric rail transit systems are the large consumers of energy.  ...  They propose a new evaluation protocol that evaluates the rain removal algorithms on their ability to improve the performance of subsequent segmentation, instance segmentation, and feature tracking algorithms  ...  Results from the author's comprehensive experimental studies show the efficiency of Vehdoop.  ... 
doi:10.1109/tits.2019.2926819 fatcat:oodbtsyfvjhsbpc2nmbulgeqda

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
Also, one of the main mechanisms to adapt autonomous driving systems to any driving condition is to be able to learn and generalize from representative scenarios.  ...  both targeted dataset collection and the proposal of novel driveability metrics that enhance the robustness of autonomous cars in adverse environments.  ...  ACKNOWLEDGEMENT The authors would like to thank Prof. Maxim Likhachev from Carnegie Mellon University for his invaluable comments that improved the manuscript.  ... 
arXiv:1811.11277v1 fatcat:ztrxyydtuveijizfn6a2dmt5ui

A comparative study of color and depth features for hand gesture recognition in naturalistic driving settings

Eshed Ohn-Bar, Mohan M. Trivedi
2015 2015 IEEE Intelligent Vehicles Symposium (IV)  
In order to provide a common experimental setup for previously proposed space-time features, we study a color and depth naturalistic hand gesture benchmark.  ...  Their effectiveness is validated on our dataset, as well as on the Cambridge hand gesture dataset, improving state-of-the-art. Finally, fusion of the modalities and various cues is studied.  ...  Therefore, there is a need for comprehensive study of space-time features in common experimental settings. This work aims to benchmark The middle frame of each video is visualized.  ... 
doi:10.1109/ivs.2015.7225790 dblp:conf/ivs/Ohn-BarT15a fatcat:uaqer5yeanhpzjpnkfu5zx5jbq

Hierarchical quantitative analysis to evaluate unsafe driving behavior from massive trajectory data

Bijun Chen, Lyuchao Liao, Fumin Zou, Shengbo Li, Jierui Liu, Xinke Wu, Ni Dong
2020 IET Intelligent Transport Systems  
However, limited effort has been paid to the study on the evaluation of unsafe driving behaviour (UDB) based on trajectory data.  ...  The large-scale trajectory data provide the potential opportunity to a better understanding of driving behaviour for transportation applications and research.  ...  Acknowledgments This work was supported in part by Projects of the National Science Foundation of China (41971340, 41471333, 61304199), project 2017A13025 of Science and Technology Development Center,  ... 
doi:10.1049/iet-its.2019.0643 fatcat:zovyehemzbdxxmrnvis6qlv4e4

Understanding user attitudes and economic aspects in a corporate multimodal mobility system: results from a field study in Germany

Madlen Günther, Benjamin Jacobsen, Marco Rehme, Uwe Götze, Josef F. Krems
2020 European Transport Research Review  
Ninety-three participants took part in the 22 months long naturalistic driving study and used the corporate multimodal mobility sharing system for their business travel.  ...  AbstractThe present study aims to investigate user attitudes and behaviour when users interact with a corporate multimodal mobility sharing system, consisting of battery electric vehicles (BEVs), pedelecs  ...  Acknowledgements A previous version of this article [13] was presented at the International Conference on Mobility as a Service (ICoMaaS) 2019 and has been selected from the ICoMaaS 2019 papers for the  ... 
doi:10.1186/s12544-020-00456-0 fatcat:ztztwe2zuzdmjhqyqlnkwxgjiy

Behavioral Research and Practical Models of Drivers' Attention [article]

Iuliia Kotseruba, John K. Tsotsos
2021 arXiv   pre-print
This report is based on over 175 behavioral studies, nearly 100 practical papers, 20 datasets, and over 70 surveys published since 2010. A curated list of papers used for this report is available at .  ...  Nevertheless, the problem of driver inattention has remained one of the primary causes of accidents.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
arXiv:2104.05677v3 fatcat:db5yxgk72ng5rdywxwdaalvpsa

A survey of deep learning techniques for autonomous driving

Sorin Grigorescu, Bogdan Trasnea, Tiberiu Cocias, Gigel Macesanu
2019 Journal of Field Robotics  
The objective of this paper is to survey the current state-of-the-art on deep learning technologies used in autonomous driving.  ...  These methodologies form a base for the surveyed driving scene perception, path planning, behavior arbitration and motion control algorithms.  ...  Acknowledgment The authors would like to thank Elektrobit Automotive for the infrastructure and research support.  ... 
doi:10.1002/rob.21918 fatcat:pjyk4lwjavf63jz4pmc3mnuqe4

Scanning the Issue

Azim Eskandarian
2022 IEEE transactions on intelligent transportation systems (Print)  
In total, 90 subjects from China, South Korea, and the USA assume a pedestrian's role in a virtual reality-based pedestrian simulator and experience three encounter scenarios with an automated vehicle.  ...  This article investigates the influence of an external humanmachine interface (eHMI) for automated vehicles on pedestrian behavior in a parking lot.  ...  Extensive experiments demonstrate that PGAN achieves new state-ofthe-art vehicle IR performance on four large-scale vehicle benchmarks.  ... 
doi:10.1109/tits.2022.3160062 fatcat:4gklzaonfzcehnvps6oge35fwe

Combining accelerometer data and contextual variables to evaluate the risk of driver behaviour

Johan W. Joubert, Dirk de Beer, Nico de Koker
2016 Transportation Research Part F: Traffic Psychology and Behaviour  
This novel methodology allows us to track both acceptable and non-acceptable driving behaviour, and calculate a more comprehensive risk model using the envelope of the data, and not a priori thresholds  ...  We demonstrate the model using accelerometer data from 124 vehicles over a one month period.  ...  In the United States, the 100-car naturalistic driving study is an ongoing instrumented-vehicle study undertaken with the primary purpose of collecting large-scale (100 vehicles), naturalistic driving  ... 
doi:10.1016/j.trf.2016.06.006 fatcat:bzd4ycayijekzg75jxyyywsjdq
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