Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes

2020 ◽  
Author(s):  
Mohsen Khalkhali ◽  
◽  
Yaser Khalighi
Keyword(s):  
Data Sharing ◽  
Verification And Validation ◽  
Automated Vehicle ◽  
Vehicle Data

scholarly journals Towards a Privacy-Preserving Way of Vehicle Data Sharing – A Case for Blockchain Technology?

2018 ◽  
pp. 111-122 ◽  
Author(s):  
Christian Kaiser ◽  
Marco Steger ◽  
Ali Dorri ◽  
Andreas Festl ◽  
Alexander Stocker ◽  
...  
Keyword(s):  
Data Sharing ◽  
Privacy Preserving ◽  
Blockchain Technology ◽  
Vehicle Data

scholarly journals Blockchain-Based Data Sharing and Trading Model for the Connected Car

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3141
Author(s):  
Byeong-Gyu Jeong ◽  
Taek-Young Youn ◽  
Nam-Su Jho ◽  
Sang Uk Shin
Keyword(s):  
Data Sharing ◽  
Video Data ◽  
Vehicle Data ◽  
Attribute Based Encryption ◽  
Data Owner ◽  
Proposed Model ◽  
Trading Model ◽  
Efficient Data ◽  
Vehicle Networks ◽  
Smart Cars

Currently, “connected cars” are being actively designed over smart cars and autonomous cars, to establish a two-way communication network between the vehicle and all infrastructure. Additionally, because vehicle black boxes are becoming more common, specific processes for secure and efficient data sharing and transaction via vehicle networks must be developed. In this paper, we propose a Blockchain-based vehicle data marketplace platform model, along with a data sharing scheme, using Blockchain-based data-owner-based attribute-based encryption (DO-ABE). The proposed model achieves the basic requirements such as data confidentiality, integrity, and privacy. The proposed system securely and effectively handles large-capacity and privacy-sensitive black box video data by storing the metadata on Blockchain (on-chain) and encrypted raw data on off-chain (external) storage, and adopting consortium Blockchain. Furthermore, the data owners of the proposed model can control their own data by applying the Blockchain-based DO-ABE and owner-defined access control lists.

Data as infrastructure? A study of data sharing legal regimes

2019 ◽  
Vol 21 (2) ◽  
pp. 124-142 ◽  
Author(s):  
Charlotte Ducuing
Keyword(s):  
Data Sharing ◽  
Network Industries ◽  
Data Governance ◽  
The Public ◽  
Vehicle Data ◽  
Essential Facility ◽  
Physical Infrastructure ◽  
Legal Regimes ◽  
Context Specific ◽  
Different Sources

The article discusses the concept of infrastructure in the digital environment, through a study of three data sharing legal regimes: the Public Sector Information Directive (PSI Directive), the discussions on in-vehicle data governance and the freshly adopted data sharing legal regime in the Electricity Directive. While aiming to contribute to the scholarship on data governance, the article deliberately focuses on network industries. Characterised by the existence of physical infrastructure, they have a special relationship to digitisation and ‘platformisation’ and are exposed to specific risks. Adopting an explanatory methodology, the article exposes that these regimes are based on two close but different sources of inspiration, yet intertwined and left unclear. By targeting entities deemed ‘monopolist’ with regard to the data they create and hold, data sharing obligations are inspired from competition law and especially the essential facility doctrine. On the other hand, beneficiaries appear to include both operators in related markets needing data to conduct their business (except for the PSI Directive), and third parties at large to foster innovation. The latter rationale illustrates what is called here a purposive view of data as infrastructure. The underlying understanding of ‘raw’ data (management) as infrastructure for all to use may run counter the ability for the regulated entities to get a fair remuneration for ‘their’ data. Finally, the article pleads for more granularity when mandating data sharing obligations depending upon the purpose. Shifting away from a ‘one-size-fits-all’ solution, the regulation of data could also extend to the ensuing context-specific data governance regime, subject to further research.

Inside Vehicle Inspection System Utilizing a Mobile Robot with LRF Sensor

2014 ◽  
Vol 26 (1) ◽  
pp. 59-67
Author(s):  
Sanngoen Wanayuth ◽  
◽  
Akihisa Ohya ◽  
Takashi Tsubouchi
Keyword(s):  
Inspection System ◽  
Average Height ◽  
Laser Range Finder ◽  
Icp Algorithm ◽  
Laser Range ◽  
Automated Vehicle ◽  
Data Comparison ◽  
Data Alignment ◽  
Vehicle Data ◽  
Vehicle Inspection

Automated vehicle inspection is utilized to inspect vehicles in a parking lots. This paper presents an approach for inspecting vehicle inside through car windows to determine any changes since the last inspection using a Laser Range Finder (LRF) sensor. Features of the approach include the detection inside vehicles method, data alignment using an ICP algorithm, inside vehicle data comparison to find any differences since the last inspection. An item identification method has been used to obtain the average height and size of objects inside vehicles to identify such changes. Our approach was shown to successfully detect typical simple items, i.e., bags, notebook PCs, and wallets, used to test the proposed method. Experiments are conducted to demonstrate the efficiency of our approach for inspecting and recognizing objects inside vehicles.

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