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Service Oriented Computing and Applications
Published in: Service Oriented Computing and Applications 1/2021

26-11-2020 | Editorial

Mobility-as-a-Service research trends of 5G-based vehicle platooning

Authors: Lingling Lv, Yanjun Shi, Weiming Shen

Published in: Service Oriented Computing and Applications | Issue 1/2021

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Excerpt

Mobility-as-a-Service (MaaS) is often described as a travel payment platform that relies on existing means of transportation, including subways, buses, private cars, shared cars, shared bikes, and tailored mobility solutions catered to users' travel needs [1, 2]. The uptake of MaaS will save time and cost, reduce congestion and traffic accidents. Previous studies proposed some services of MaaS: (1) customized solutions for individual travelers; (2) publicly commandeered private cars and shared cars for ridesharing; (3) automated vehicle (truck) platoons for transporting goods. According to an Allied Market Research report [3], the global truck platooning market size is projected to reach 4.59 billion US dollars by 2025. This short article discusses some MaaS research trends of vehicle platooning with 5G technologies. …
next article A deep learning approach for collaborative prediction of Web service QoS

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Literature
1.
Wong YZ, Hensher DA, Mulley C (2020) Mobility as a service (MaaS): charting a future context. Transp Res Part A Policy Pract 131:5–19CrossRef
2.
Smith G, Sochor J, Sarasini S (2018) Mobility as a service: comparing developments in Sweden and Finland. Res Transp Bus Manag 27:36–45CrossRef
3.
4.
Jia D, Lu K, Wang J et al (2016) A survey on platoon-based vehicular cyber-physical systems. IEEE Commun Surv Tutor 18(1):263–284CrossRef
5.
Campolo C, Molinaro A, Iera A et al (2018) 5G network slicing for vehicle-to-everything services. IEEE Wirel Commun 24(6):38–45CrossRef
6.
Molina-Masegosa R, Gozalvez J (2017) LTE-V for sidelink 5G V2X vehicular communications: a new 5G technology for short-range vehicle-to-everything communications. IEEE Veh Technol Mag 12:30–39CrossRef
7.
Ren J, Yu G, He Y et al (2019) Collaborative cloud and edge computing for latency minimization. IEEE Trans Veh Technol 68(5):5031–5044CrossRef
8.
Sharma V, Jayakody DNK, Qaraqe M (2020) Osmotic computing-based service migration and resource scheduling in Mobile Augmented Reality Networks (MARN). Future Gener Comput Syst 102:723–737CrossRef
Metadata
Title
Mobility-as-a-Service research trends of 5G-based vehicle platooning
Authors
Lingling Lv
Yanjun Shi
Weiming Shen
Publication date
26-11-2020
Publisher
Springer London
Published in
Service Oriented Computing and Applications / Issue 1/2021
Print ISSN: 1863-2386
Electronic ISSN: 1863-2394
DOI
https://doi.org/10.1007/s11761-020-00309-7

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