Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation

There is a large gap between current AI-based autonomous-driving cars and fully autonomous cars, where the remote control of vehicles can be a unique solution to fill the gap. The remote control enables valuable operational data to be obtained, thus laying the groundwork for gradually increasing aut...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE access 2022, Vol.10, p.64920-64932
Hauptverfasser: Yu, Yang, Lee, Sanghwan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 64932
container_issue
container_start_page 64920
container_title IEEE access
container_volume 10
creator Yu, Yang
Lee, Sanghwan
description There is a large gap between current AI-based autonomous-driving cars and fully autonomous cars, where the remote control of vehicles can be a unique solution to fill the gap. The remote control enables valuable operational data to be obtained, thus laying the groundwork for gradually increasing autonomous driving performance in the future. Moreover, human assistance through remote driving can offer more flexibility and intelligence than a single artificial intelligence. However, the real-time transmission of data and images is particularly crucial for remotely driven vehicles. The latency between a vehicle and the controller depends on the video streaming communication methods and transport protocols. Furthermore, the control or driving performance also depends on the vehicle speed likewise. Therefore, in this paper, we explore the impact of different communication methods of video streaming and vehicle "speed" on the performance of remote driving. We design a vehicle remote driving system based on ROS (Robot Operating System) with ROS as the core communication architecture to realize remote control of vehicles. The video stream is transmitted using three different streaming methods: ROS multi-computer communication, TCP protocol, and UDP protocol. To be specific, we implement a simple remote driving system for a "model" car, drive it at different speeds, and analyze how the drivers perform in terms of whether the vehicle gets off the track while driving. Based on the results, we find that "UDP-based video streaming" achieves 720P video streaming with a latency of less than 50ms, which is helpful for further research on remote driving. The experiment by "directly" observing the vehicle with eyes instead of using video streaming is also conducted to remove the video streaming latency. The experiment results show that the speed of the vehicle and the video streaming methods have a significant impact on the driving performance, and UDP protocol-based video streaming method is better suited for remote driving. The results imply that remote driving should be used in a low-speed environment rather than at high speed.
doi_str_mv 10.1109/ACCESS.2022.3183758
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1109_ACCESS_2022_3183758</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9797698</ieee_id><doaj_id>oai_doaj_org_article_e214c394a095414ab0e8f245a3ee8a44</doaj_id><sourcerecordid>2680397177</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-4dc9cae74e7f10e240910efb6836aa1e3126fd81a34e92f4b8d6ee78c427a1483</originalsourceid><addsrcrecordid>eNpNUV1r20AQFKWBhsS_IC8HeZZ7X9Ld9c0obhowNdhJ-3ispZVzrqxL784u-feRo2C6L7MMM7MLk2U3jE4Zo-brrKrm6_WUU86ngmmhCv0pu-SsNLkoRPn5v_1LNolxR4fRA1Woy6xe4d4nJHfBHV2_JZXvU_Ad-e3SM1khdPmj2yP55Rr0ZJ0Cwv4kWx4xDJqAHcZIfmL658Of-I3cYXTbnkDfkPkRugMk5_vr7KKFLuLkA6-yp-_zx-pHvljeP1SzRV5LqlMum9rUgEqiahlFLqkZoN2UWpQADAXjZdtoBkKi4a3c6KZEVLqWXAGTWlxlD2Nu42FnX4LbQ3i1Hpx9J3zYWgjJ1R1a5EzWwkigppBMwoaibrksQCBqkHLIuh2zXoL_e8CY7M4fQj-8b3mpqTCKKTWoxKiqg48xYHu-yqg9lWPHcuypHPtRzuC6GV0OEc8Oo4wqjRZvezmKcQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2680397177</pqid></control><display><type>article</type><title>Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation</title><source>DOAJ Directory of Open Access Journals</source><source>IEEE Xplore Open Access Journals</source><source>EZB Electronic Journals Library</source><creator>Yu, Yang ; Lee, Sanghwan</creator><creatorcontrib>Yu, Yang ; Lee, Sanghwan</creatorcontrib><description>There is a large gap between current AI-based autonomous-driving cars and fully autonomous cars, where the remote control of vehicles can be a unique solution to fill the gap. The remote control enables valuable operational data to be obtained, thus laying the groundwork for gradually increasing autonomous driving performance in the future. Moreover, human assistance through remote driving can offer more flexibility and intelligence than a single artificial intelligence. However, the real-time transmission of data and images is particularly crucial for remotely driven vehicles. The latency between a vehicle and the controller depends on the video streaming communication methods and transport protocols. Furthermore, the control or driving performance also depends on the vehicle speed likewise. Therefore, in this paper, we explore the impact of different communication methods of video streaming and vehicle "speed" on the performance of remote driving. We design a vehicle remote driving system based on ROS (Robot Operating System) with ROS as the core communication architecture to realize remote control of vehicles. The video stream is transmitted using three different streaming methods: ROS multi-computer communication, TCP protocol, and UDP protocol. To be specific, we implement a simple remote driving system for a "model" car, drive it at different speeds, and analyze how the drivers perform in terms of whether the vehicle gets off the track while driving. Based on the results, we find that "UDP-based video streaming" achieves 720P video streaming with a latency of less than 50ms, which is helpful for further research on remote driving. The experiment by "directly" observing the vehicle with eyes instead of using video streaming is also conducted to remove the video streaming latency. The experiment results show that the speed of the vehicle and the video streaming methods have a significant impact on the driving performance, and UDP protocol-based video streaming method is better suited for remote driving. The results imply that remote driving should be used in a low-speed environment rather than at high speed.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2022.3183758</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Artificial intelligence ; Automobiles ; Autonomous cars ; Autonomous driving ; Autonomous vehicles ; Communication ; Delays ; Driver behavior ; Driving ; feedback delay ; human-vehicle interaction ; Image transmission ; live streaming ; Low speed ; Network latency ; Protocols ; Real time ; Remote control ; remote driving ; Remote observing ; ROS ; round trip time ; Streaming media ; Traffic speed ; Vehicles ; Video communication ; Video data ; video streaming ; Video transmission ; Wireless networks</subject><ispartof>IEEE access, 2022, Vol.10, p.64920-64932</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-4dc9cae74e7f10e240910efb6836aa1e3126fd81a34e92f4b8d6ee78c427a1483</citedby><cites>FETCH-LOGICAL-c408t-4dc9cae74e7f10e240910efb6836aa1e3126fd81a34e92f4b8d6ee78c427a1483</cites><orcidid>0000-0002-0970-1634 ; 0000-0001-8431-0097</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9797698$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,4010,27610,27900,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Yu, Yang</creatorcontrib><creatorcontrib>Lee, Sanghwan</creatorcontrib><title>Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation</title><title>IEEE access</title><addtitle>Access</addtitle><description>There is a large gap between current AI-based autonomous-driving cars and fully autonomous cars, where the remote control of vehicles can be a unique solution to fill the gap. The remote control enables valuable operational data to be obtained, thus laying the groundwork for gradually increasing autonomous driving performance in the future. Moreover, human assistance through remote driving can offer more flexibility and intelligence than a single artificial intelligence. However, the real-time transmission of data and images is particularly crucial for remotely driven vehicles. The latency between a vehicle and the controller depends on the video streaming communication methods and transport protocols. Furthermore, the control or driving performance also depends on the vehicle speed likewise. Therefore, in this paper, we explore the impact of different communication methods of video streaming and vehicle "speed" on the performance of remote driving. We design a vehicle remote driving system based on ROS (Robot Operating System) with ROS as the core communication architecture to realize remote control of vehicles. The video stream is transmitted using three different streaming methods: ROS multi-computer communication, TCP protocol, and UDP protocol. To be specific, we implement a simple remote driving system for a "model" car, drive it at different speeds, and analyze how the drivers perform in terms of whether the vehicle gets off the track while driving. Based on the results, we find that "UDP-based video streaming" achieves 720P video streaming with a latency of less than 50ms, which is helpful for further research on remote driving. The experiment by "directly" observing the vehicle with eyes instead of using video streaming is also conducted to remove the video streaming latency. The experiment results show that the speed of the vehicle and the video streaming methods have a significant impact on the driving performance, and UDP protocol-based video streaming method is better suited for remote driving. The results imply that remote driving should be used in a low-speed environment rather than at high speed.</description><subject>Artificial intelligence</subject><subject>Automobiles</subject><subject>Autonomous cars</subject><subject>Autonomous driving</subject><subject>Autonomous vehicles</subject><subject>Communication</subject><subject>Delays</subject><subject>Driver behavior</subject><subject>Driving</subject><subject>feedback delay</subject><subject>human-vehicle interaction</subject><subject>Image transmission</subject><subject>live streaming</subject><subject>Low speed</subject><subject>Network latency</subject><subject>Protocols</subject><subject>Real time</subject><subject>Remote control</subject><subject>remote driving</subject><subject>Remote observing</subject><subject>ROS</subject><subject>round trip time</subject><subject>Streaming media</subject><subject>Traffic speed</subject><subject>Vehicles</subject><subject>Video communication</subject><subject>Video data</subject><subject>video streaming</subject><subject>Video transmission</subject><subject>Wireless networks</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUV1r20AQFKWBhsS_IC8HeZZ7X9Ld9c0obhowNdhJ-3ispZVzrqxL784u-feRo2C6L7MMM7MLk2U3jE4Zo-brrKrm6_WUU86ngmmhCv0pu-SsNLkoRPn5v_1LNolxR4fRA1Woy6xe4d4nJHfBHV2_JZXvU_Ad-e3SM1khdPmj2yP55Rr0ZJ0Cwv4kWx4xDJqAHcZIfmL658Of-I3cYXTbnkDfkPkRugMk5_vr7KKFLuLkA6-yp-_zx-pHvljeP1SzRV5LqlMum9rUgEqiahlFLqkZoN2UWpQADAXjZdtoBkKi4a3c6KZEVLqWXAGTWlxlD2Nu42FnX4LbQ3i1Hpx9J3zYWgjJ1R1a5EzWwkigppBMwoaibrksQCBqkHLIuh2zXoL_e8CY7M4fQj-8b3mpqTCKKTWoxKiqg48xYHu-yqg9lWPHcuypHPtRzuC6GV0OEc8Oo4wqjRZvezmKcQ</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Yu, Yang</creator><creator>Lee, Sanghwan</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-0970-1634</orcidid><orcidid>https://orcid.org/0000-0001-8431-0097</orcidid></search><sort><creationdate>2022</creationdate><title>Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation</title><author>Yu, Yang ; Lee, Sanghwan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-4dc9cae74e7f10e240910efb6836aa1e3126fd81a34e92f4b8d6ee78c427a1483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial intelligence</topic><topic>Automobiles</topic><topic>Autonomous cars</topic><topic>Autonomous driving</topic><topic>Autonomous vehicles</topic><topic>Communication</topic><topic>Delays</topic><topic>Driver behavior</topic><topic>Driving</topic><topic>feedback delay</topic><topic>human-vehicle interaction</topic><topic>Image transmission</topic><topic>live streaming</topic><topic>Low speed</topic><topic>Network latency</topic><topic>Protocols</topic><topic>Real time</topic><topic>Remote control</topic><topic>remote driving</topic><topic>Remote observing</topic><topic>ROS</topic><topic>round trip time</topic><topic>Streaming media</topic><topic>Traffic speed</topic><topic>Vehicles</topic><topic>Video communication</topic><topic>Video data</topic><topic>video streaming</topic><topic>Video transmission</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Yang</creatorcontrib><creatorcontrib>Lee, Sanghwan</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Yang</au><au>Lee, Sanghwan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2022</date><risdate>2022</risdate><volume>10</volume><spage>64920</spage><epage>64932</epage><pages>64920-64932</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>There is a large gap between current AI-based autonomous-driving cars and fully autonomous cars, where the remote control of vehicles can be a unique solution to fill the gap. The remote control enables valuable operational data to be obtained, thus laying the groundwork for gradually increasing autonomous driving performance in the future. Moreover, human assistance through remote driving can offer more flexibility and intelligence than a single artificial intelligence. However, the real-time transmission of data and images is particularly crucial for remotely driven vehicles. The latency between a vehicle and the controller depends on the video streaming communication methods and transport protocols. Furthermore, the control or driving performance also depends on the vehicle speed likewise. Therefore, in this paper, we explore the impact of different communication methods of video streaming and vehicle "speed" on the performance of remote driving. We design a vehicle remote driving system based on ROS (Robot Operating System) with ROS as the core communication architecture to realize remote control of vehicles. The video stream is transmitted using three different streaming methods: ROS multi-computer communication, TCP protocol, and UDP protocol. To be specific, we implement a simple remote driving system for a "model" car, drive it at different speeds, and analyze how the drivers perform in terms of whether the vehicle gets off the track while driving. Based on the results, we find that "UDP-based video streaming" achieves 720P video streaming with a latency of less than 50ms, which is helpful for further research on remote driving. The experiment by "directly" observing the vehicle with eyes instead of using video streaming is also conducted to remove the video streaming latency. The experiment results show that the speed of the vehicle and the video streaming methods have a significant impact on the driving performance, and UDP protocol-based video streaming method is better suited for remote driving. The results imply that remote driving should be used in a low-speed environment rather than at high speed.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2022.3183758</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-0970-1634</orcidid><orcidid>https://orcid.org/0000-0001-8431-0097</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2169-3536
ispartof IEEE access, 2022, Vol.10, p.64920-64932
issn 2169-3536
2169-3536
language eng
recordid cdi_crossref_primary_10_1109_ACCESS_2022_3183758
source DOAJ Directory of Open Access Journals; IEEE Xplore Open Access Journals; EZB Electronic Journals Library
subjects Artificial intelligence
Automobiles
Autonomous cars
Autonomous driving
Autonomous vehicles
Communication
Delays
Driver behavior
Driving
feedback delay
human-vehicle interaction
Image transmission
live streaming
Low speed
Network latency
Protocols
Real time
Remote control
remote driving
Remote observing
ROS
round trip time
Streaming media
Traffic speed
Vehicles
Video communication
Video data
video streaming
Video transmission
Wireless networks
title Remote Driving Control With Real-Time Video Streaming Over Wireless Networks: Design and Evaluation
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-04T14%3A19%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Remote%20Driving%20Control%20With%20Real-Time%20Video%20Streaming%20Over%20Wireless%20Networks:%20Design%20and%20Evaluation&rft.jtitle=IEEE%20access&rft.au=Yu,%20Yang&rft.date=2022&rft.volume=10&rft.spage=64920&rft.epage=64932&rft.pages=64920-64932&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2022.3183758&rft_dat=%3Cproquest_cross%3E2680397177%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2680397177&rft_id=info:pmid/&rft_ieee_id=9797698&rft_doaj_id=oai_doaj_org_article_e214c394a095414ab0e8f245a3ee8a44&rfr_iscdi=true