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Research Article | Open Access

State of data platforms for connected vehicles and infrastructures

Kai Li Lima( )Jake Whiteheada,bDongyao JiabZuduo Zhengb
Dow Centre for Sustainable Engineering Innovation, The University of Queensland, Brisbane, QLD, 4072, Australia
School of Civil Engineering, The University of Queensland, Brisbane, QLD, 4072, Australia
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An erratum to this article is available online at:

Abstract

The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data, leading to a demand for effective data management solutions. This is further catalysed through the need for society to make informed policies and decisions that can properly support their emerging growth. While data systems and platforms exist, they are often proprietary, being only compatible to the products that they are designed for. Given the products and services generate energy and spatial-temporal data that can often correlate, a lack of interoperability between these systems would impede decision making, as data from each system must be considered independently. By studying currently available data platforms and frameworks, this paper weighs the problems that these products address, and identifies necessary gaps for a more cohesive platform to exist. This is performed through a top-down approach, whereby broader vehicle-to-everything approaches are first studied, before moving to the components that could comprise a data platform to integrate and ingest these various data feeds. Finally, potential design considerations for a data platform is presented, along with examples of application benefits that would enable users to make more informed and holistic decisions about current mobility options.

References

 
ActiveMQ (2021). ActiveMQ. URL: https://activemq.apache.org/
 

Adegoke, E., Zidane, J., Kampert, E., Ford, C. R., Birrell, S. A., & Higgins, M. D. (2019). Infrastructure wi-fi for connected autonomous vehicle positioning: A review of the state-of-the-art. Vehicular Communications, 20, 100185. https://doi.org/10.1016/j.vehcom.2019.100185

 

Ali, Y., Sharma, A., Haque, M. M., Zheng, Z., & Saifuzzaman, M. (2020). The impact of the connected environment on driving behavior and safety: A driving simulator study. Accident Analysis & Prevention, 144, 105643. https://doi.org/10.1016/j.aap.2020.105643

 
Amazon Web Services (2021a). Amazon Kinesis - Process & Analyze Streaming Data - Amazon Web Services. URL: https://aws.amazon.com/kinesis/
 
Amazon Web Services (2021b). Amazon RDS | Cloud Relational Database | Amazon Web Services. URL: https://aws.amazon.com/rds/
 
Amazon Web Services (2021c). Amazon SQS | Message Queuing Service | AWS. URL: https://aws.amazon.com/sqs/
 
Amazon Web Services (2021d). Cloud Services - Amazon Web Services (AWS). URL: https://aws.amazon.com/
 
Apache Software Foundation (2021a). Apache Flink: Stateful Computations over Data Streams. URL: https://flink.apache.org/
 
Apache Software Foundation (2021b). Apache Kafka. URL: https://kafka.apache.org/
 
ACSC (2021). Infosec registered assessors program (IRAP). URL: https://www.cyber.gov.au/acsc/view-all-content/programs/irap
 
Balzano, W., & Vitale, F. (2017). DiG-park: A smart parking availability searching method using v2v/v2i and DGP-class problem. In 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA). IEEE. https://doi.org/10.1109/waina.2017.104
 
Berg, A., & Svantesson, F. (2021). Is your electric vehicle plotting against you? : An investigation of the ISO 15118 standard and current security implementations. Masters thesis Halmstad University
 
Botkar, S. P., Godse, S. P., Mahalle, P. N., & Shinde, G. R. (2021). VANET. Taylor & Francis Ltdhttps://doi.org/10.1201/9781003157069
 

Bouchelaghem, S., & Omar, M. (2019). Reliable and secure distributed smart road pricing system for smart cities. IEEE Transactions on Intelligent Transportation Systems, 20, 1592-1603. https://doi.org/10.1109/tits.2018.2842754

 
Cao, Y., Ahmad, N., Kaiwartya, O., Puturs, G., & Khalid, M. (2018). Intelligent transportation systems enabled ICT framework for electric vehicle charging in smart city. In Handbook of Smart Cities (pp. 311-330). Springer International Publishing. https://doi.org/10.1007/978-3-319-97271-8_12
 

Chen, N., Wang, M., Zhang, N., & Shen, X. (2020). Energy and information management of electric vehicular network: A survey. IEEE Communications Surveys & Tutorials, 22, 967-997. https://doi.org/10.1109/comst.2020.2982118

 
Connexion Telematics (2021). Connexion Telematics. URL: https://connexionltd.com/
 
Continental (2021). Continental mobility services: Vehicle data services. URL: https://www.continental-mobility-services.com/en-en/products/vehicle-data-services/
 
Deka, L. (2018). Transportation Cyber-Physical Systems. Amsterdam, Netherlands: Elsevier
 
Dotson, C. (2019). Practical Cloud Security. O’Reilly Media, Inc, USA
 
Edwertz, O. (2017). Performance Evaluation of 5G Vehicle-to-Network Use Cases: A study of site configuration and network impact. mathesis Chalmers University of Technology Gothenburg, Sweden
 
Emami, A., Sarvi, M., Bagloee, S.A.A review of the critical elements and development of real-world connected vehicle testbeds around the worldTransport. Lett.202012610.1080/19427867.2020.1759852

Emami, A., Sarvi, M., & Bagloee, S. A. (2020). A review of the critical elements and development of real-world connected vehicle testbeds around the world. Transportation Letters, (pp. 1-26). https://doi.org/10.1080/19427867.2020.1759852

 
ENX Association (2021). Tisax. URL: https://enx.com/en-US/TISAX/
 

Fan, S.-K. S., Su, C.-J., Nien, H.-T., Tsai, P.-F., & Cheng, C.-Y. (2017). Using machine learning and big data approaches to predict travel time based on historical and real-time data from taiwan electronic toll collection. Soft Computing, 22, 5707-5718. https://doi.org/10.1007/s00500-017-2610-y

 

Fu, X., Guo, C., Qu, Y., & Lin, X.-H. (2021). Resource allocation and blocklength selection for low-latency vehicular communications. IEEE Wireless Communications Letters, 10, 914-918. https://doi.org/10.1109/lwc.2020.3046507

 
Giordani, M., Zanella, A., Higuchi, T., Altintas, O., & Zorzi, M. (2018). Performance study of LTE and mmWave in vehicle-to-network communications. In 2018 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net). IEEE. https://doi.org/10.23919/medhocnet.2018.8407093
 
Giordani, M., Zanella, A., & Zorzi, M. (2019). LTE and millimeter waves for v2i communications: An end-to-end performance comparison. In 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring). IEEE. https://doi.org/10.1109/vtcspring.2019.8746487
 
Google (2021). Cloud Computing Services. URL: https://cloud.google.com/
 

Gupta, M., Benson, J., Patwa, F., & Sandhu, R. (2020). Secure v2v and v2i communication in intelligent transportation using cloudlets. IEEE Transactions on Services Computing, (pp. 1-1). https://doi.org/10.1109/tsc.2020.3025993

 

Halili, R., Weyn, M., & Berkvens, R. (2021). Comparing localization performance of IEEE 802.11p and LTE-v v2i communications. Sensors, 21, 2031. https://doi.org/10.3390/s21062031

 
Hamdi, M. M., Audah, L., Rashid, S. A., Mohammed, A. H., Alani, S., & Mustafa, A. S. (2020). A review of applications, characteristics and challenges in vehicular ad hoc networks (VANETs). In 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE. https://doi.org/10.1109/hora49412.2020.9152928
 

Havers, B., Duvignau, R., Najdataei, H., Gulisano, V., Papatriantafilou, M., & Koppisetty, A. C. (2020). DRIVEN: A framework for efficient data retrieval and clustering in vehicular networks. Future Generation Computer Systems, 107, 1-17. https://doi.org/10.1016/j.future.2020.01.050

 
Hilmani, A., Maizate, A., Hassouni, L.Designing and managing a smart parking system using wireless sensor networksJ. Sens. Actuator Netw.201872410.3390/jsan7020024

Hilmani, A., Maizate, A., & Hassouni, L. (2018). Designing and managing a smart parking system using wireless sensor networks. Journal of Sensor and Actuator Networks, 7, 24. https://doi.org/10.3390/jsan7020024

 
Hou, J., Song, Z.A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivityAppl. Energy202025711390010.1016/j.apenergy.2019.113900

Hou, J., & Song, Z. (2020). A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity. Applied Energy, 257, 113900. https://doi.org/10.1016/j.apenergy.2019.113900

 

Hunter, J. D. (2007). Matplotlib: A 2d graphics environment. Computing in Science & Engineering, 9, 90-95. https://doi.org/10.1109/mcse.2007.55

 
Ihaka, R., Gentleman, R.R: a language for data analysis and graphicsJ. Comput. Graph Stat.1996529931410.1080/10618600.1996.10474713

Ihaka, R., & Gentleman, R. (1996). R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5, 299-314. https://doi.org/10.1080/10618600.1996.10474713

 
International Organization for Standardization (2019). ISO 15118-1:2019. techreport 15118-20 International Organization for Standardization Geneva, Switzerland. URL: https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/06/91/69113.html
 
Jiang, D., & Delgrossi, L. (2008). IEEE 802.11p: Towards an international standard for wireless access in vehicular environments. In VTC Spring 2008 - IEEE Vehicular Technology Conference. IEEE. https://doi.org/10.1109/vetecs.2008.458
 
Khan, S.M., Chowdhury, M., Morris, E.A., Deka, L.Synergizing roadway infrastructure investment with digital infrastructure for infrastructure-based connected vehicle applications: review of current status and future directionsJ. Infrastruct. Syst.2019250311900110.1061/(asce)is.1943-555x.0000507

Khan, S. M., Chowdhury, M., Morris, E. A., & Deka, L. (2019). Synergizing roadway infrastructure investment with digital infrastructure for infrastructure-based connected vehicle applications: Review of current status and future directions. Journal of Infrastructure Systems, 25, 03119001. https://doi.org/10.1061/(asce)is.1943-555x.0000507

 
Lamothe, M., Guéhéneuc, Y.-G., Shang, W.A systematic review of api evolution literatureACM Comput. Surv.20215410.1145/347013310.1145/3470133

Lamothe, M., Gueheneuc, Y.-G., & Shang, W. (2021). A systematic review of api evolution literature. ACM Comput. Surv., 54. https://doi.org/10.1145/3470133

 

Lan, H., Cheng, B., Gou, Z., & Yu, R. (2020). An evaluation of feed-in tariffs for promoting household solar energy adoption in southeast queensland, australia. Sustainable Cities and Society, 53, 101942. https://doi.org/10.1016/j.scs.2019.101942

 
Lauser, T., Zelle, D., & Krauss, C. (2020). Security analysis of automotive protocols. In Computer Science in Cars Symposium. ACM. https://doi.org/10.1145/3385958.3430482
 

Li, C., Dong, Z., Chen, G., Zhou, B., Zhang, J., & Yu, X. (2021). Data-driven planning of electric vehicle charging infrastructure: A case study of sydney, australia. IEEE Transactions on Smart Grid, 12, 3289-3304. https://doi.org/10.1109/tsg.2021.3054763

 
Li, G., Deng, X., Zhou, M., Zhu, Q., Lan, J., Xia, H., & Mitrouchev, P. (2020). Research on data monitoring system for intelligent ship. In Lecture Notes in Electrical Engineering (pp. 234-241). Springer Singapore. https://doi.org/10.1007/978-981-15-2341-0_29
 
Li, S., Yang, Y., Yang, L., Su, H., Zhang, G., & Wang, J. (2017). Civil aircraft big data platform. In 2017 IEEE 11th International Conference on Semantic Computing (ICSC). IEEE. https://doi.org/10.1109/icsc.2017.51
 
Lim, K. L., Speidel, S., & Braunl, T. (2020). REView: A unified telemetry platform for electric vehicles and charging infrastructure. In Connected Vehicles in the Internet of Things (pp. 167-219). Springer International Publishing. https://doi.org/10.1007/978-3-030-36167-9_8
 

Liu, X., Liu, Y., Chen, Y., & Hanzo, L. (2020). Enhancing the fuel-economy of v2i-assisted autonomous driving: A reinforcement learning approach. IEEE Transactions on Vehicular Technology, 69, 8329-8342. https://doi.org/10.1109/tvt.2020.2996187

 
Luoto, P., Bennis, M., Pirinen, P., Samarakoon, S., Horneman, K., & Latva-aho, M. (2017). Vehicle clustering for improving enhanced LTE-v2x network performance. In 2017 European Conference on Networks and Communications (EuCNC). IEEE. https://doi.org/10.1109/eucnc.2017.7980735
 
Microsoft (2021a). Azure Cosmos DB - Non-Relational Database | Microsoft Azure. URL: https://azure.microsoft.com/en-us/services/cosmos-db/
 
Microsoft (2021b). Azure Service Bus-Cloud Messaging Service | Microsoft Azure. URL: https://azure.microsoft.com/en-us/services/service-bus/
 
Microsoft (2021c). Cloud Computing Services | Microsoft Azure. URL: https://azure.microsoft.com/en-gb/
 
Microsoft (2021d). Data Visualisation | Microsoft Power BI. URL: https://powerbi.microsoft.com/en-au/
 
Microsoft (2021e). Event Hubs-Real-Time Data Ingestion | Microsoft Azure. URL: https://azure.microsoft.com/en-us/services/event-hubs/
 

Mitchell, L. E., Crosman, E. T., Jacques, A. A., Fasoli, B., Leclair-Marzolf, L., Horel, J., Bowling, D. R., Ehleringer, J. R., & Lin, J. C. (2018). Monitoring of greenhouse gases and pollutants across an urban area using a light-rail public transit platform. Atmospheric Environment, 187, 9-23. https://doi.org/10.1016/j.atmosenv.2018.05.044

 
Mohyuddin, S., & Prehofer, C. (2021). A scalable data analytics framework for connected vehicles using apache spark. In 2021 International Symposium on Electrical, Electronics and Information Engineering. ACM. https://doi.org/10.1145/3459104.3459156
 

Molina-Masegosa, R., Gozalvez, J., & Sepulcre, M. (2020). Comparison of IEEE 802.11p and LTE-v2x: An evaluation with periodic and aperiodic messages of constant and variable size. IEEE Access, 8, 121526-121548. https://doi.org/10.1109/access.2020.3007115

 
MongoDB (2021). Mongodb. URL: https://www.mongodb.com
 
Moto, K., Mikami, M., Serizawa, K., & Yoshino, H. (2019). Field experimental evaluation on 5g v2n low latency communication for application to truck platooning. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall). IEEE. https://doi.org/10.1109/vtcfall.2019.8891450
 

Mozaffari, S., Al-Jarrah, O. Y., Dianati, M., Jennings, P., & Mouzakitis, A. (2020). Deep learning-based vehicle behavior prediction for autonomous driving applications: A review. IEEE Transactions on Intelligent Transportation Systems, (pp. 1-15). https://doi.org/10.1109/tits.2020.3012034

 
Muratore, G., Rincon, J. A., Julian, V., Carrascosa, C., Greco, G., & Fortino, G. (2020). Towards a dynamic edge AI framework applied to autonomous driving cars. In Communications in Computer and Information Science (pp. 406-415). Springer International Publishing. https://doi.org/10.1007/978-3-030-51999-5_34
 
MySQL (2021). MySQL. URL: https://www.mysql.com/
 

Neilson, A., Indratmo, Daniel, B., & Tjandra, S. (2019). Systematic review of the literature on big data in the transportation domain: Concepts and applications. Big Data Research, 17, 35-44. https://doi.org/10.1016/j.bdr.2019.03.001

 
Olaverri-Monreal, C., Errea-Moreno, J., Díaz-Álvarez, A.Implementation and evaluation of a traffic light assistance system based on v2i communication in a simulation frameworkJ. Adv. Transport. 2018201811110.1155/2018/3785957

Olaverri-Monreal, C., Errea-Moreno, J., & Diaz-Alvarez, A. (2018). Implementation and evaluation of a traffic light assistance system based on v2i communication in a simulation framework. Journal of Advanced Transportation, 2018, 1-11. https://doi.org/10.1155/2018/3785957

 

Papadoulis, A., Quddus, M., & Imprialou, M. (2019). Evaluating the safety impact of connected and autonomous vehicles on motorways. Accident Analysis & Prevention, 124, 12-22. https://doi.org/10.1016/j.aap.2018.12.019

 
Papathanassiou, A., & Khoryaev, A. (2017). Cellular V2X as the Essential Enabler of Superior Global Connected Transportation Services. IEEE 5G Tech Focus, 1. URL: https://futurenetworks.ieee.org/tech-focus/june-2017/cellular-v2x
 
Petratos, A., Ting, A., Padmanabhan, S., Zhou, K., Hageman, D., Pisel, J. R., & Pyrcz, M. J. (2021). Optimal placement of public electric vehicle charging stations using deep reinforcement learning, . arXiv:2108.07772
 
PostgreSQL Global Development Group (2021). PostgreSQL. URL: https://www.postgresql.org/
 
Prajapati, P., Shah, P.A review on secure data deduplication: cloud storage security issueJ. King Saud Univ. Comput. Inf. Sci.202010.1016/j.jksuci.2020.10.02110.1016/j.jksuci.2020.10.021

Prajapati, P., & Shah, P. (2020). A review on secure data deduplication: Cloud storage security issue. Journal of King Saud University - Computer and Information Sciences, . doi:https://doi.org/10.1016/j.jksuci.2020.10.021

 
Preibisch, S. (2018). API Development. Apresshttps://doi.org/10.1007/978-1-4842-4140-0
 
RabbitMQ (2021). Messaging that just works - RabbitMQ. URL: https://www.rabbitmq.com/
 
Rangarajan, S., Verma, M., Kannan, A., Sharma, A., & Schoen, I. (2012). V2c: a secure vehicle to cloud framework for virtualized and on-demand service provisioning. In Proceedings of the International Conference on Advances in Computing, Communications and Informatics - ICACCI’12. ACM Press. https://doi.org/10.1145/2345396.2345422
 
Raviglione, F., Malinverno, M., & Casetti, C. (2019). Open source testbed for vehicular communication. In Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM. https://doi.org/10.1145/3323679.3326623
 
Rezgui, J., Gagne, E., Blain, G., St-Pierre, O., & Harvey, M. (2020). Platooning of autonomous vehicles with artificial intelligence v2i communications and navigation algorithm. In 2020 Global Information Infrastructure and Networking Symposium (GIIS). IEEE. https://doi.org/10.1109/giis50753.2020.9248490
 
Robert Bosch GmbH (2021). Connected mobility. URL: https://www.bosch-mobility-solutions.com/en/mobility-topics/connected-mobility/
 

Saadoon, M., Ab. Hamid, S. H., Sofian, H., Altarturi, H. H., Azizul, Z. H., & Nasuha, N. (2021). Fault tolerance in big data storage and processing systems: A review on challenges and solutions. Ain Shams Engineering Journal, . doi:https://doi.org/10.1016/j.asej.2021.06.024

 
SAE International (2016). J1962B: Diagnostic Connector - SAE International. URL: https://www.sae.org/standards/content/j1962_201607/
 

Saqib, M., Hussain, M. M., Alam, M. S., Beg, M. M. S., & Sawant, A. (2017). Smart electric vehicle charging through cloud monitoring and management. Technology and Economics of Smart Grids and Sustainable Energy, 2. https://doi.org/10.1007/s40866-017-0035-4

 
Sarvi, M., Asadi, S., & Uytsel, S. V. (2020). New fixes for old traffic problems: Connected transport systems and AIMES. In Autonomous Vehicles (pp. 185-196). Springer Singapore. https://doi.org/10.1007/978-981-15-9255-3_9
 
Scholer, R. A., Mepham, D., Girimonte, S., Oliver, D., Gowri, K., Tenney, N., Lawlis, J., Taha, E., & Halliwell, J. (2011). Communication Requirements for Plug-In Electric Vehicles. techreport 2011-01-0866 SAE International. https://doi.org/10.4271/2011-01-0866
 

Sharma, A., Zheng, Z., Kim, J., Bhaskar, A., & Haque, M. M. (2021). Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors. Transportation Research Part C: Emerging Technologies, 124, 102934. https://doi.org/10.1016/j.trc.2020.102934

 

Sharma, V., You, I., & Guizani, N. (2020). Security of 5g-v2x: Technologies, standardization, and research directions. IEEE Network, 34, 306-314. https://doi.org/10.1109/mnet.001.1900662

 

Sliwa, B., Falkenberg, R., Liebig, T., Piatkowski, N., & Wietfeld, C. (2020). Boosting vehicle-to-cloud communication by machine learning-enabled context prediction. IEEE Transactions on Intelligent Transportation Systems, 21, 3497-3512. https://doi.org/10.1109/tits.2019.2930109

 
Sliwa, B., & Wietfeld, C. (2020). A reinforcement learning approach for efficient opportunistic vehicle-to-cloud data transfer. In 2020 IEEE Wireless Communications and Networking Conference (WCNC). IEEE. https://doi.org/10.1109/wcnc45663.2020.9120681
 
Smartcar (2021). Smartcar ⋅ API platform for connected car data. URL: https://smartcar.com/
 

Sovacool, B. K., Kester, J., Noel, L., & de Rubens, G. Z. (2020). Actors, business models, and innovation activity systems for vehicle-to-grid (v2g) technology: A comprehensive review. Renewable and Sustainable Energy Reviews, 131, 109963. https://doi.org/10.1016/j.rser.2020.109963

 
Stallings, W. (1987). Handbook of computer-communications standards. New York London: Macmillan Collier Macmillan
 

Sun, J., Zheng, Z., & Sun, J. (2020). The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller. Transportation Research Part B: Methodological, 142, 58-83. https://doi.org/10.1016/j.trb.2020.10.004

 
Tableau (2021). Tableau: Business Intelligence and Analytics Software. URL: https://www.tableau.com/
 
Taiebat, M., Brown, A.L., Safford, H.R., Qu, S., Xu, M.A review on energy, environmental, and sustainability implications of connected and automated vehiclesEnviron. Sci. Technol.201810.1021/acs.est.8b0012710.1021/acs.est.8b00127

Taiebat, M., Brown, A. L., Safford, H. R., Qu, S., & Xu, M. (2018). A review on energy, environmental, and sustainability implications of connected and automated vehicles. Environmental Science & Technology, . https://doi.org/10.1021/acs.est.8b00127

 
 
Tesla API (2021). Tesla API. URL: https://www.teslaapi.io/
 

Tian, D., Zhou, J., Wang, Y., Sheng, Z., Duan, X., & Leung, V. C. (2020). Channel access optimization with adaptive congestion pricing for cognitive vehicular networks: An evolutionary game approach. IEEE Transactions on Mobile Computing, 19, 803-820. https://doi.org/10.1109/tmc.2019.2901471

 
Tokarz, K. (2019). A review on the vehicle to vehicle and vehicle to infrastructure communication. In Advances in Intelligent Systems and Computing (pp. 44-52). Springer International Publishing. https://doi.org/10.1007/978-3-030-31964-9_5
 
van der Kam, M., & Bekkers, R. (2020). Achieving interoperability for EV roaming: Pathways to harmonization: Report D6.2 for the evRoaming4EU project. Netherlands Knowledge Platform for Public Charging Infrastructure (NKL). Publication of the evRoaming4EU project, grant number EME-31.EME (Electric Mobility Europe) is an ERA-NET Cofund under the EU Horizon 2020 program
 
Verizon Connect (2021). Verizon connect. URL: https://www.verizonconnect.com/
 
Vrbanic, F., Cakija, D., Kusic, K., & Ivanjko, E. (2021). Traffic flow simulators with connected and autonomous vehicles: A short review. In EcoProduction (pp. 15-30). Springer International Publishing. https://doi.org/10.1007/978-3-030-66464-0_2
 

Vukadinovic, V., Bakowski, K., Marsch, P., Garcia, I. D., Xu, H., Sybis, M., Sroka, P., Wesolowski, K., Lister, D., & Thibault, I. (2018). 3gpp c-v2x and IEEE 802.11p for vehicle-to-vehicle communications in highway platooning scenarios. Ad Hoc Networks, 74, 17-29. https://doi.org/10.1016/j.adhoc.2018.03.004

 

Wang, H., Liu, T., Kim, B., Lin, C.-W., Shiraishi, S., Xie, J., & Han, Z. (2020a). Architectural design alternatives based on cloud/edge/fog computing for connected vehicles. IEEE Communications Surveys & Tutorials, 22, 2349-2377. https://doi.org/10.1109/comst.2020.3020854

 

Wang, M., & Zhang, Q. (2020). Optimized data storage algorithm of iot based on cloud computing in distributed system. Computer Communications, 157, 124-131. doi:https://doi.org/10.1016/j.comcom.2020.04.023

 

Wang, X., Shen, S., Bezzina, D., Sayer, J. R., Liu, H. X., & Feng, Y. (2020b). Data infrastructure for connected vehicle applications. Transportation Research Record: Journal of the Transportation Research Board, 2674, 85-96. https://doi.org/10.1177/0361198120912424

 
Wang, Z., Liao, X., Zhao, X., Han, K., Tiwari, P., Barth, M. J., & Wu, G. (2020c). A digital twin paradigm: Vehicle-to-cloud based advanced driver assistance systems. In 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring). IEEE. https://doi.org/10.1109/vtc2020-spring48590.2020.9128938
 

Wei, L., Cui, J., Zhong, H., Xu, Y., & Liu, L. (2021). Proven secure tree-based authenticated key agreement for securing v2v and v2i communications in VANETs. IEEE Transactions on Mobile Computing, (pp. 1-1). https://doi.org/10.1109/tmc.2021.3056712

 

Won, M. (2020). Intelligent traffic monitoring systems for vehicle classification: A survey. IEEE Access, 8, 73340-73358. https://doi.org/10.1109/access.2020.2987634

 
Yoshizawa, T., & Preneel, B. (2019). Survey of security aspect of v2x standards and related issues. In 2019 IEEE Conference on Standards for Communications and Networking (CSCN). IEEE. https://doi.org/10.1109/cscn.2019.8931311
 
ZeroMQ (2021). ZeroMQ. URL: https://zeromq.org/
 
Zhang, Q., Wang, Y., Zhang, X., Liu, L., Wu, X., Shi, W., & Zhong, H. (2018). OpenVDAP: An open vehicular data analytics platform for CAVs. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)IEEE. https://doi.org/10.1109/icdcs.2018.00131
 

Zhao, P., Haitao, H., Li, A., & Mansourian, A. (2021). Impact of data processing on deriving micro-mobility patterns from vehicle availability data. Transportation Research Part D: Transport and Environment, 97, 102913. https://doi.org/10.1016/j.trd.2021.102913

 
Zhong, S., Xiao, X., Bushell, M., Sun, H.Optimal road congestion pricing for both traffic efficiency and safety under demand uncertaintyJ. Transport. Eng., Part A: Systems20171430401700410.1061/jtepbs.0000025

Zhong, S., Xiao, X., Bushell, M., & Sun, H. (2017). Optimal road congestion pricing for both traffic efficiency and safety under demand uncertainty. Journal of Transportation Engineering, Part A: Systems, 143, 04017004. https://doi.org/10.1061/jtepbs.0000025

 

Zhu, Q., Ji, S., Shen, J., & Ren, Y. (2021). Privacy-preserving smart road-pricing system with trustworthiness evaluation in VANETs. Sensors, 21, 3658. https://doi.org/10.3390/s21113658

Communications in Transportation Research
Article number: 100013
Cite this article:
Lim KL, Whitehead J, Jia D, et al. State of data platforms for connected vehicles and infrastructures. Communications in Transportation Research, 2021, 1(1): 100013. https://doi.org/10.1016/j.commtr.2021.100013

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Received: 29 September 2021
Revised: 15 November 2021
Accepted: 15 November 2021
Published: 26 November 2021
© 2021 The Authors. Published by Elsevier Ltd on behalf of Tsinghua University Press.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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