Design and Evaluation of Remote Driving Architecture on 4G and 5G Mobile Networks
Despite the progress in the development of automated vehicles in the last decade, reaching the level of reliability required at large-scale deployment at an economical price and combined with safety requirements is still a long road ahead. In certain use cases, such as automated shuttles and taxis,...
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Published in | Frontiers in future transportation Vol. 2 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Frontiers Media S.A
11.01.2022
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Abstract | Despite the progress in the development of automated vehicles in the last decade, reaching the level of reliability required at large-scale deployment at an economical price and combined with safety requirements is still a long road ahead. In certain use cases, such as automated shuttles and taxis, where there is no longer even a steering wheel and pedals required, remote driving could be implemented to bridge this gap; a remote operator can take control of the vehicle in situations where it is too difficult for an automated system to determine the next actions. In logistics, it could even be implemented to solve already more pressing issues such as shortage of truck drivers, by providing more flexible working conditions and less standstill time of the truck. An important aspect of remote driving is the connection between the remote station and the vehicle. With the current roll-out of 5G mobile technology in many countries throughout the world, the implementation of remote driving comes closer to large-scale deployment. 5G could be a potential game-changer in the deployment of this technology. In this work, we examine the remote driving application and network-level performance of remote driving on a recently deployed sub-6-GHz commercial 5G stand-alone (SA) mobile network. It evaluates the influence of the 5G architecture, such as mobile edge computing (MEC) integration, local breakout, and latency on the application performance of remote driving. We describe the design, development (based on Hardware-in-the-Loop simulations), and performance evaluation of a remote driving solution, tested on both 5G and 4G mobile SA networks using two different vehicles and two different remote stations. Two test cases have been defined to evaluate the application and network performance and are evaluated based on position accuracy, relative reaction times, and distance perception. Results show the performance of the network to be sufficient for remote driving applications at relatively low speeds (<40 km/h). Network latencies compared with 4G have dropped to half. A strong correlation between latency and remote driving performance is not clearly seen and requires further evaluation taking into account the influence of the user interface. |
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AbstractList | Despite the progress in the development of automated vehicles in the last decade, reaching the level of reliability required at large-scale deployment at an economical price and combined with safety requirements is still a long road ahead. In certain use cases, such as automated shuttles and taxis, where there is no longer even a steering wheel and pedals required, remote driving could be implemented to bridge this gap; a remote operator can take control of the vehicle in situations where it is too difficult for an automated system to determine the next actions. In logistics, it could even be implemented to solve already more pressing issues such as shortage of truck drivers, by providing more flexible working conditions and less standstill time of the truck. An important aspect of remote driving is the connection between the remote station and the vehicle. With the current roll-out of 5G mobile technology in many countries throughout the world, the implementation of remote driving comes closer to large-scale deployment. 5G could be a potential game-changer in the deployment of this technology. In this work, we examine the remote driving application and network-level performance of remote driving on a recently deployed sub-6-GHz commercial 5G stand-alone (SA) mobile network. It evaluates the influence of the 5G architecture, such as mobile edge computing (MEC) integration, local breakout, and latency on the application performance of remote driving. We describe the design, development (based on Hardware-in-the-Loop simulations), and performance evaluation of a remote driving solution, tested on both 5G and 4G mobile SA networks using two different vehicles and two different remote stations. Two test cases have been defined to evaluate the application and network performance and are evaluated based on position accuracy, relative reaction times, and distance perception. Results show the performance of the network to be sufficient for remote driving applications at relatively low speeds (<40 km/h). Network latencies compared with 4G have dropped to half. A strong correlation between latency and remote driving performance is not clearly seen and requires further evaluation taking into account the influence of the user interface. |
Author | Passchier, Igor Juza, Jakub Kakes, Geerd Ho, Victor Tafur Monroy, Idelfonso den Ouden, Jos van der Smagt, Tijs Rommel, Simon |
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Cites_doi | 10.1016/j.autcon.2016.05.009 10.1002/9781119247111 10.13140/RG.2.2.18037.88803 10.1016/j.ijtst.2017.07.008 10.5220/0004475802310238 10.1109/jiot.2020.3028766 |
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References | Dadhich (B8) 2016; 68 Passchier (B15) 2021 Georg (B10) 2020 Lane (B13) 2002 (B1) 2020 (B17) 2021 Gnatzig (B11) 2013 Khastgir (B12) 2021 Zhang (B18) 2020; 7 Chandramouli (B6) 2019 Baraniuk (B3) 2020 Ploeg (B16) 2011 Chan (B5) 2017; 6 Neumeier (B14) 2019 Al-N’awashi (B2) 2014 Gardner (B9) 2021 (B4) 2020 Czarnecki (B7) 2018 |
References_xml | – volume: 68 start-page: 212 year: 2016 ident: B8 article-title: Key Challenges in Automation of Earth-Moving Machines publication-title: Automation in Construction doi: 10.1016/j.autcon.2016.05.009 contributor: fullname: Dadhich – year: 2021 ident: B9 article-title: Want to Drive Your Truck by Remote Control? Einride Is Hiring contributor: fullname: Gardner – volume-title: PAS 1883:2020 Operational Design Domain (ODD) Taxonomy for an Automated Driving System (ADS) – Specification year: 2020 ident: B4 – volume-title: A Guideline to Video Codecs Delay year: 2014 ident: B2 contributor: fullname: Al-N’awashi – volume-title: 5G for the Connected World – year: 2019 ident: B6 doi: 10.1002/9781119247111 contributor: fullname: Chandramouli – start-page: 260 year: 2011 ident: B16 article-title: Design and Experimental Evaluation of Cooperative Adaptive Cruise Control contributor: fullname: Ploeg – year: 2018 ident: B7 article-title: Operational Design Domain for Automated Driving Systems - Taxonomy of Basic Terms publication-title: Tech. Rep. doi: 10.13140/RG.2.2.18037.88803 contributor: fullname: Czarnecki – start-page: 186 year: 2019 ident: B14 article-title: Teleoperation: The Holy Grail to Solve Problems of Automated Driving? Sure, but Latency Matters contributor: fullname: Neumeier – volume-title: C-V2X Use Cases Volume II: Examples and Service Level Requirements – 5G Automotive Association year: 2020 ident: B1 – volume: 6 start-page: 208 year: 2017 ident: B5 article-title: Advancements, Prospects, and Impacts of Automated Driving Systems publication-title: Int. J. Transportation Sci. Tech. doi: 10.1016/j.ijtst.2017.07.008 contributor: fullname: Chan – volume-title: The Forklift Truck Drivers Who Never Leave Their Desks year: 2020 ident: B3 contributor: fullname: Baraniuk – year: 2021 ident: B12 article-title: The Curious Case of Operational Design Domain: What it Is and Is Not? publication-title: Medium contributor: fullname: Khastgir – start-page: 231 year: 2013 ident: B11 article-title: A System Design for Teleoperated Road Vehicles publication-title: ICINCO doi: 10.5220/0004475802310238 contributor: fullname: Gnatzig – start-page: 11 volume-title: 27th ITS World Congress year: 2021 ident: B15 article-title: Remote Operation of Automated Vehicles via 5G Networks contributor: fullname: Passchier – start-page: 2874 year: 2002 ident: B13 article-title: Effects of Time Delay on Telerobotic Control of Neutral Buoyancy Vehicles contributor: fullname: Lane – start-page: 760 year: 2020 ident: B10 article-title: Sensor and Actuator Latency during Teleoperation of Automated Vehicles contributor: fullname: Georg – volume-title: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles - J3016_202104 year: 2021 ident: B17 – volume: 7 start-page: 11347 year: 2020 ident: B18 article-title: Toward Automated Vehicle Teleoperation: Vision, Opportunities, and Challenges publication-title: IEEE Internet Things J. doi: 10.1109/jiot.2020.3028766 contributor: fullname: Zhang |
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Title | Design and Evaluation of Remote Driving Architecture on 4G and 5G Mobile Networks |
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