research-article

NERVteh Compact Motion Based Driving Simulator

Authors:

Matej Vengust,

Boštjan Kaluža,

Kristina Stojmenova,

Jaka SodnikAuthors Info & Claims

AutomotiveUI '17: Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Adjunct

Pages 242 - 243

https://doi.org/10.1145/3131726.3132047

Published: 24 September 2017 Publication History

Get Access

Abstract

NERVteh is a Slovenian high-tech R&D company, specialized in vehicle simulation and driver evaluation technologies. Its main product is a compact driving simulator based on a 4DOF motion platform and powerful simulation software. It is modular and customizable software, providing a variety of virtual environments, road and weather conditions, AI-based traffic and realistic vehicle dynamics. The simulator hardware consists mostly of real car components and offers almost real-life driving experience. The simulation can run on three large curved screens or on a VR headset. Additionally, it enables real-time communication and synchronization with a set of external sensors for assessment of drivers' physical and mental states. This technology is mostly used for driver training and education, biometrical evaluation and profiling. It is also a very efficient tool for development and testing of smart traffic infrastructure, road planning and risk assessment of drivers. This demo will provide the opportunity to the conference participants to experience first-hand the latest hardware and software technology advancements for capturing driver behavior in a simulated driving environment.

References

[1]

Empatica E4. Available at: https://www.empatica.com/e4-wristband. Retrieved May 31st 2017.

Google Scholar

[2]

NERVteh simulation technologies. Available at: http://nerv-teh.com/. Retrieved May 31st 2017.

Google Scholar

[3]

Neurosky. Neosky EEG biosensors. Availabe at: http://neurosky.com/biosensors/eeg-sensor/. Retrieved May 31st 2017.

Google Scholar

[4]

Tobii. Wireless Tobii Pro Glasses 2. Available at: https://www.tobiipro.com/product-listing/tobii-proglasses-2/. Retrieved May 31st 2017.

Google Scholar

[5]

Vengust, M., Možina, D., Pušenjak, N., Zevnik, L, Sodnik, J., Kaluža, B., & Tavčar, A. (2014, September). NERVteh 4DOF motion car driving simulator. In Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 1--6). ACM.

Digital Library

Google Scholar

Cited By

View all

Gruden TTomažič SJakus G(2024)Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological SignalsSensors10.3390/s2410319324:10(3193)Online publication date: 17-May-2024
https://doi.org/10.3390/s24103193
Pečečnik KMirnig AMeschtscherjakov ASodnik J(2024)Evaluation of Head-Up Display for Conditionally Automated VehiclesDisruptive Information Technologies for a Smart Society10.1007/978-3-031-50755-7_17(174-182)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-50755-7_17
Strle GKošir ASodnik JPečečnik K(2023)Physiological Signals as Predictors of Cognitive Load Induced by the Type of Automotive Head-Up DisplayIEEE Access10.1109/ACCESS.2023.330538311(87835-87848)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3305383
Show More Cited By

Index Terms

NERVteh Compact Motion Based Driving Simulator
1. Information systems
  1. Information systems applications
    1. Multimedia information systems

Recommendations

NERVteh 4DOF motion car driving simulator
AutomotiveUI '14: Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

This paper describes the basic structure and functionalities of a novel car driving simulator for a realistic simulation of various road and traffic conditions, and realistic car behavior on different terrains. Its main and most innovative component is ...
Numerical Analysis of Tractor Accidents using Driving Simulator for Autonomous Driving Tractor
ICMRE'19: Proceedings of the 5th International Conference on Mechatronics and Robotics Engineering

Autonomous driving of automobiles is a hot research topic in recent years. The autonomous driving tractor also has been studied in the agricultural field as well as an autonomous driving automobile. On the other hand, tractor accidents frequently occur ...
A Full Driving Simulator of Urban Traffic including Traffic Accidents

This paper describes a model for traffic simulation of an urban environment and its implementation in a driving simulator. The simulator is also able to reproduce realistic traffic accidents. In order to attain real-time simulation, the simulation ...

Comments

Information & Contributors

Information

Published In

AutomotiveUI '17: Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Adjunct

September 2017

270 pages

ISBN:9781450351515

DOI:10.1145/3131726

General Chair:
Susanne Boll
University of Oldenburg, Germany
,
Program Chairs:
Andreas Löcken
University of Oldenburg, Germany
,
Ronald Schroeter
Queensland University of Technology, Australia
,
Martin Baumann
Ulm University, Germany
,
Ignacio Alvarez
Intel Corporation, USA
,
Lewis Chuang
Max Planck Institute for Biological Cybernetics Tübingen, Germany
,
Sebastian Feuerstack
Institute for Information Technology, Germany
,
Myounghoon Jeon
Michigan Tech, USA
,
Nora Broy
BMW Group, Germany
,
Hanneke Hooft van Huysduynen
Eindhoven University of Technology, The Netherlands
,
Sebastian Osswald
BMW Group, Germany
,
Publications Chairs:
Ioannis Politis
University of Cambridge, UK
,
David Large
The University of Nottingham, UK

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 September 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

AutomotiveUI '17

Sponsor:

SIGCHI

AutomotiveUI '17: ACM 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 24 - 27, 2017

Oldenburg, Germany

Acceptance Rates

AutomotiveUI '17 Paper Acceptance Rate 31 of 51 submissions, 61%;

Overall Acceptance Rate 248 of 566 submissions, 44%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
135
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Gruden TTomažič SJakus G(2024)Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological SignalsSensors10.3390/s2410319324:10(3193)Online publication date: 17-May-2024
https://doi.org/10.3390/s24103193
Pečečnik KMirnig AMeschtscherjakov ASodnik J(2024)Evaluation of Head-Up Display for Conditionally Automated VehiclesDisruptive Information Technologies for a Smart Society10.1007/978-3-031-50755-7_17(174-182)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-50755-7_17
Strle GKošir ASodnik JPečečnik K(2023)Physiological Signals as Predictors of Cognitive Load Induced by the Type of Automotive Head-Up DisplayIEEE Access10.1109/ACCESS.2023.330538311(87835-87848)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3305383
Stojmenova KThomopoulos NSodnik JJi YJeon M(2022)Ready2Drive – Interactive Online Video-Based Driving Tasks for Assessment of Driving-Related Skills of Older DriversAdjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3544999.3551345(196-198)Online publication date: 17-Sep-2022
https://dl.acm.org/doi/10.1145/3544999.3551345
Schartmüller CRiener A(2021)The Driving Experience Lab: Simulating the Automotive Future in a Trailer13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3473682.3481877(225-228)Online publication date: 9-Sep-2021
https://dl.acm.org/doi/10.1145/3473682.3481877
Sanghavi HJeon MNadri CKo SSodnik JStojmenova K(2021)Multimodal Takeover Request Displays for Semi-automated Vehicles: Focused on Spatiality and Lead TimeHCI in Mobility, Transport, and Automotive Systems10.1007/978-3-030-78358-7_22(315-334)Online publication date: 3-Jul-2021
https://doi.org/10.1007/978-3-030-78358-7_22
Riegler ARiener AHolzmann C(2020)A Research Agenda for Mixed Reality in Automated VehiclesProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3428390(119-131)Online publication date: 22-Nov-2020
https://dl.acm.org/doi/10.1145/3428361.3428390
Cizman Staba UKlun TStojmenova KJakus GSodnik J(2020)Consistency of neuropsychological and driving simulator assessment after neurological impairmentApplied Neuropsychology: Adult10.1080/23279095.2020.181574729:4(829-838)Online publication date: 8-Sep-2020
https://doi.org/10.1080/23279095.2020.1815747
Motnikar LStojmenova KŠtaba UKlun TRobida KSodnik J(2020)Exploring driving characteristics of fit- and unfit-to-drive neurological patients: a driving simulator studyTraffic Injury Prevention10.1080/15389588.2020.1764547(1-6)Online publication date: 18-May-2020
https://doi.org/10.1080/15389588.2020.1764547

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

NERVteh 4DOF motion car driving simulator

Numerical Analysis of Tractor Accidents using Driving Simulator for Autonomous Driving Tractor

A Full Driving Simulator of Urban Traffic including Traffic Accidents