自駕車資料法制之比較研究

自駕車技術需要眾多的感測器取代人類眼睛之工作，並配合上人工智慧演算法，利用感測器所回報之數據計算出正確的操作。此些感測器所蒐集之資料具有不可或缺之地位，然而其中完整的資料蒐集問題卻僅有零星的討論，更遑論法規層面能有全面的規範。各國目前響應自駕車產業的發展多有相對應的政策、指南或是已訂立出法律，然而其中針對資料蒐集議題之規範不僅屈指可數，且在自駕車資料蒐集議題未被完整的瞭解與討論之前亦容易有所缺漏。有鑑於我國於2018年通過《無人載具科技創新實驗條例》，目前自駕車已進入測試之階段，因此本文擬透過相關文獻先行定義出自駕車資料蒐集之議題，包括資料的蒐集與否及範圍、儲存的時間、蒐集後的處理以及使用等。其後透過分析與比較美國與歐盟的相關討論、指南、法規等，針對自駕車資料蒐集議題提出管制之利與弊，以期未來在我國自駕車資料蒐集議題之立法上能夠有所貢獻。

關鍵字

自駕車；無人車；聯網車；先進駕駛輔助系統；資料保護；資料蒐集；隱私權；車輛資料

並列摘要

Autonomous vehicles rely on numerous sensors to gather real-time data which are fed into artificial intelligent algorithms to produce accurate manipulations that have been made through human sensations. As a result, data collected from the sensors play an essential role in autonomous driving. However, there has only been very few discussions on the data collection problem in autonomous driving and its legitimate regulations are far from complete. Despite the existing policies on guidelines and regulations in different countries in response to the prospering industrial development of autonomous vehicles, few of them have addressed the issue of data collection, and these regulations could be very likely be incomprehensive without detailed investigations and disputes. Given that Taiwan has newly added the Unmanned Vehicles Technology Innovative Experiment Act, autonomous vehicles have already entered their testing phase in the country. This thesis first outlines the data collection issue in autonomous vehicles from existing literature, including whether and what to collect, when to store the observed data, and their processing and usage post-collection. Second, this thesis compares discussions, guidelines and regulations from Europe and America regarding data collection in autonomous driving technology. It also analyzes their strengths and weaknesses with a view to contributing to Taiwan's forthcoming legislation on the focal data collection issue.

並列關鍵字

Autonomous Vehicle ； Self-Driving Car ； Connected Vehicle ； Advanced Driver Assistance System (ADAS) ； Data Protection ； Data Collection ； Privacy ； Vehicle Information