当前位置: X-MOL 学术 › Journal of Environmental and Public Health › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Accident Liability Determination of Autonomous Driving Systems Based on Artificial Intelligence Technology and Its Impact on Public Mental Health
Journal of Environmental and Public Health Pub Date : 2022-08-31 , DOI: 10.1155/2022/2671968
Yineng Xiao 1 , Zhao Liu 2
Affiliation  

With the rise of self-driving technology research, the establishment of a scientific and perfect legal restraint and supervision system for self-driving vehicles has been gradually paid attention to. The determination of tort liability subject of traffic accidents of self-driving cars is different from that of ordinary motor vehicle traffic accident tort, which challenges the application of traditional fault liability and product liability. The tort issue of self-driving cars should be discussed by distinguishing two kinds of situations: assisted driving cars and highly automated driving, and typological analysis of each situation is needed. When the car is in the assisted driving mode, the accident occurs due to the quality defect or product damage of the self-driving car, and there is no other fault cause; then, the producer and seller of the car should bear the product liability according to the no-fault principle; if the driver has a subjective fault and fails to exercise a high degree of care; the owner and user of the car should bear the fault liability. This paper analyzes the study of the impact of autonomous driving public on public psychological health, summarizes the key factors affecting the public acceptance of autonomous driving, and dissects its impact on public psychological acceptance. In order to fully study the responsibility determination of autonomous driving system accidents and their impact on public psychological health, this paper proposes an autonomous driving risk prediction model based on artificial intelligence technology, combined with a complex intelligent traffic environment vehicle autonomous driving risk prediction method, to complete the risk target detection. The experimental results in the relevant dataset demonstrate the effectiveness of the proposed method.

中文翻译:

基于人工智能技术的自动驾驶系统事故责任认定及其对公众心理健康的影响

随着自动驾驶技术研究的兴起,建立科学、完善的自动驾驶车辆法律约束和监管体系逐渐受到重视。自动驾驶汽车交通事故侵权责任主体的认定不同于普通机动车交通事故侵权,这对传统过错责任和产品责任的适用提出了挑战。自动驾驶汽车的侵权问题应区分辅助驾驶汽车和高度自动驾驶两种情况进行讨论,并对每种情况进行类型分析。汽车处于辅助驾驶模式时,因自动驾驶汽车质量缺陷或产品损坏而发生事故,且无其他故障原因的;那么,汽车生产者、销售者应当按照无过错原则承担产品责任;驾驶人有主观过错且未高度注意的;汽车所有人、使用人应当承担过错责任。本文分析了自动驾驶公众对公众心理健康影响的研究,总结了影响自动驾驶公众接受度的关键因素,并剖析了其对公众心理接受度的影响。为了充分研究自动驾驶系统事故的责任认定及其对公众心理健康的影响,提出一种基于人工智能技术的自动驾驶风险预测模型,结合复杂智能交通环境车辆自动驾驶风险预测方法,完成风险目标检测。相关数据集中的实验结果证明了该方法的有效性。
更新日期:2022-08-31
down
wechat
bug