Vol. 3 No. 1 (2023): Journal of AI-Assisted Scientific Discovery
Articles

Privacy-Aware Data Sharing Policies for Autonomous Vehicle Collaboration

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  • Dr. Lena Nilsson
Dr. Lena Nilsson
Associate Professor of Information Technology, Linköping University, Sweden
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Published 30-06-2023

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Lena Nilsson, “Privacy-Aware Data Sharing Policies for Autonomous Vehicle Collaboration”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, pp. 69–89, Jun. 2023, Accessed: Aug. 10, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/92

Abstract

In recent years, privacy concerns have become a major obstacle to the widespread adoption of data sharing technologies. To address this, the ride-sharing fleet owners and operators will want to be able to put privacy preservation technologies in place as protection against these threats. In addition, legislators and government entities are enacting privacy laws and regulations aimed at the collection and processing of personal data. These laws are designing data sharing frameworks based on a number of principles related to data subjects’ trust and the data life-cycle, such as the right to be forgotten and tight access rights to personally identifiable information (PII), also for third-party services accessing the PII under user consent [1].

ADVANCES in sensor technology, data storage and processing capacities, communication systems and artificial intelligence (AI) have lead to major renaissance in the use of autonomous vehicles (AVs) [2]. Among different AV environments, AV ride-sharing fleets are regarded as the most promising application in terms of energy efficiency, reduction in CO2 emissions, transportation cost, and improvement of traffic flow. However, transportation-related data, such as personally identifiable information (e.g., origin-destination locations and arrival times for every trip) is being collected by AVs in large quantities, and may be used for services such as location-based advertising. Furthermore, data of this nature could be vulnerable to a variety of attacks and privacy risks.

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