A Quantitative Legal Support System for Transnational Autonomous Vehicle Design
One of the key expectations of AI product manufacturers for their products is the ability to scale to larger markets, especially across legal systems, with fewer prototypes and lower adaptation costs. This paper focuses on the increasingly dynamic legal compliance challenges faced by designers of AI...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/4/316 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850183501040582656 |
|---|---|
| author | Zhe Yu Yiwei Lu Hao Zhan Yang Yu Zongshun Wang |
| author_facet | Zhe Yu Yiwei Lu Hao Zhan Yang Yu Zongshun Wang |
| author_sort | Zhe Yu |
| collection | DOAJ |
| description | One of the key expectations of AI product manufacturers for their products is the ability to scale to larger markets, especially across legal systems, with fewer prototypes and lower adaptation costs. This paper focuses on the increasingly dynamic legal compliance challenges faced by designers of AI products in achieving this goal. Based on non-monotonic reasoning, we design an automated reasoning tool to help them better understand the legal implications of their designs in a transnational context and, ultimately, adjust the design of AI products more flexibly. This tool supports the quantitative representation of the strength of legal significance to help designers better understand the reasons for their decisions from their own perspective. To illustrate this functionality, a case study on traffic regulations across the UK, France, and Japan demonstrates the system’s ability to resolve legal conflicts—such as driving-side mandates and speed radar detector prohibitions—through quantitative evaluation. |
| format | Article |
| id | doaj-art-007b20201c9b4c39aa65a582bd2eab1a |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-007b20201c9b4c39aa65a582bd2eab1a2025-08-20T02:17:20ZengMDPI AGDrones2504-446X2025-04-019431610.3390/drones9040316A Quantitative Legal Support System for Transnational Autonomous Vehicle DesignZhe Yu0Yiwei Lu1Hao Zhan2Yang Yu3Zongshun Wang4Institute of Logic and Cognition, Department of Philosophy, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Law, Old College, University of Edinburgh, Edinburgh EH8 9YL, UKDepartment of Philosophy, Xiamen University, Xiamen 361005, ChinaInformation Systems Department, Institute of Data Science and Intelligent Decision Support, Beijing Jiaotong University, Beijing 100044, ChinaInstitute of Logic and Cognition, Department of Philosophy, Sun Yat-sen University, Guangzhou 510275, ChinaOne of the key expectations of AI product manufacturers for their products is the ability to scale to larger markets, especially across legal systems, with fewer prototypes and lower adaptation costs. This paper focuses on the increasingly dynamic legal compliance challenges faced by designers of AI products in achieving this goal. Based on non-monotonic reasoning, we design an automated reasoning tool to help them better understand the legal implications of their designs in a transnational context and, ultimately, adjust the design of AI products more flexibly. This tool supports the quantitative representation of the strength of legal significance to help designers better understand the reasons for their decisions from their own perspective. To illustrate this functionality, a case study on traffic regulations across the UK, France, and Japan demonstrates the system’s ability to resolve legal conflicts—such as driving-side mandates and speed radar detector prohibitions—through quantitative evaluation.https://www.mdpi.com/2504-446X/9/4/316autonomous vehiclesregulatory compliancecross-national drivingcomputational argumentation |
| spellingShingle | Zhe Yu Yiwei Lu Hao Zhan Yang Yu Zongshun Wang A Quantitative Legal Support System for Transnational Autonomous Vehicle Design Drones autonomous vehicles regulatory compliance cross-national driving computational argumentation |
| title | A Quantitative Legal Support System for Transnational Autonomous Vehicle Design |
| title_full | A Quantitative Legal Support System for Transnational Autonomous Vehicle Design |
| title_fullStr | A Quantitative Legal Support System for Transnational Autonomous Vehicle Design |
| title_full_unstemmed | A Quantitative Legal Support System for Transnational Autonomous Vehicle Design |
| title_short | A Quantitative Legal Support System for Transnational Autonomous Vehicle Design |
| title_sort | quantitative legal support system for transnational autonomous vehicle design |
| topic | autonomous vehicles regulatory compliance cross-national driving computational argumentation |
| url | https://www.mdpi.com/2504-446X/9/4/316 |
| work_keys_str_mv | AT zheyu aquantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT yiweilu aquantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT haozhan aquantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT yangyu aquantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT zongshunwang aquantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT zheyu quantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT yiweilu quantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT haozhan quantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT yangyu quantitativelegalsupportsystemfortransnationalautonomousvehicledesign AT zongshunwang quantitativelegalsupportsystemfortransnationalautonomousvehicledesign |