# The Interface of Privacy and Data Security in Automated City Shuttles: The GDPR Analysis
## 3 GDPR Implications
### Data Processing Principles  
Any processing of personal data should occur in the light of the legal principles as set in the body of the GDPR subsequently illustrated in Figure 2. According to Article 83 Section 4 [7] of GDPR, any failure of the entities involved in the processing to comply with the data processing principles may result in administrative fines and other sanctions. Certainly, the adherence to these principles by the controllers seems to be a fundamental requirement for the assessment of their compliance to the GDPR. To that end, data should be processed with respect to the following principles [7]:  
1. Lawfulness, transparency, and fairness: where data collection practices are conducted based on a thorough understanding of the GDPR law and without hiding the type of collected data and the reason for its processing from the data subjects (Article 5, Sections 1.a and 6).
2. Purpose limitation: where the processing is approached based on the specified, explicit, and legitimate purposes with no further processing in a manner that is incompatible with those agreed on purposes (Article 5 Section 1.d).
3. Storage limitation: calling for data storage no longer than it is necessary for the purpose for which the personal data is processed (Article 5 Section 1.e).
4. Accuracy: where controllers should take necessary measures to process only correct data (Article 5 Section 1.b).
5. Data minimization: aiming to limit the amount of processed data to the lowest level and requiring data destruction once the purpose of the processing is completed (Article 5 Section 1.e).
6. Security: requiring data controllers to employ the appropriate technical and organizational measures designed to effectively implement integrity and confidentiality through PbD and PbDf principles (Article 25 Sections 1 & 2).
7. Accountability: requiring data controllers to put in place appropriate privacy-preserving measures that are able to demonstrate compliance to the regulation at any stage (Article 5 Section 2).  
To support continuous automated navigation of ACS, data are used permanently. This perpetual data usage poses multiple challenges to the aforementioned principles. First of all, collecting large datasets of personal data to train the AI models jeopardizes the data minimization principle [21]. Secondly, further collection, use, transmission, or storage of personal data may exceed the purpose limitation principle from the beginning of these data processing operations. Additionally, innovative autonomous and connected technologies applied in the ACS complicate the implementation and monitoring of the proper security measures in line with as the data protection by PbD and PbDf principles. Finally, while being part of the public transport system, the ACS have multiple stakeholders involved in data processing. These stakeholders act as data controllers or data processors or theirroles change. For this reason, they have to provide personal data guarantees and mitigate potential privacy-related risks [2; 18] based on the accountability principle.  
The subsequent sections are the result of our research to find the answers to the target research questions. Section 3.2 sets the basis for understanding the scope of RQ1 and provides the relevant findings. Then, Section 3.3 outlines our analysis in the form of a comprehensive study focused on the ACS's environment to address the RQ2.