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Determination Of The Driver's Criminal Liability Of A Traffic Accident In Self-driving Mode

Posted on:2021-02-13Degree:MasterType:Thesis
Country:ChinaCandidate:Q LiFull Text:PDF
GTID:2416330623480777Subject:legal
Abstract/Summary:PDF Full Text Request
Automatic driving technology is becoming more and more mature,and the corresponding legal problems are also revealed.A series of problems such as how to determine the driver's criminal responsibility and how to perfect the criminal law imputation system should be studied more carefully.Due to the complexity of the technology and the self-control of the behavior of the self-driving system,there will be legal infringement caused by the failure of the artificial intelligence system in reality,and there is a blank area where the responsibility can not be attributed.Criminal law plays an important role in this blank area.This paper will study the legal system from the aspects of liability determination and causality,and considers the characteristics of the new artificial intelligence such as self-driving mode,and make clear how the driver should bear the criminal responsibility in the traffic accident under the self-driving mode.According to the typical domestic and foreign cases of traffic accident in the current self-driving mode,the following problems exist in the determination of the criminal responsibility of the driver in the self-driving mode: the scope of the responsibility subject is expanded and the content of the specific responsibility is different in each case;the responsibility of various subjects is not clear;the determination of the subjective aspects of the driver;and the definition of the driver's obligation is not clear.This paper analyzes the influencing factors involved in each responsibility subject in the traffic accident under the self-driving mode,and focuses on the classification of the self-driving mode and the influence of the intervention factors of other subjects on the driver's criminal responsibility determination at all levels.In this paper,the significant differences between the self-driving mode and the traditional driving mode are compared and analyzed.In the self-driving mode driver traffic accident,in terms of how to determine their criminal responsibility,the author analyzes the criminal ability and the ability to be punished of the subject,and introduces the involved legal theory,which provides a theoretical basis for the study of this problem.On the basis of this research,it is concluded that the driver is the most important subject of criminal responsibility,but the self-driving mode has added new artificial intelligence,so there are some differences compared with the traditional driving mode,which need to be discussed separately.These factors will have a certain impact on the conclusion of the driver's criminal responsibility determination.The first is the prior preventive responsibility of the car R & D and the producer.If they fail to fulfill their obligations and cause a major failure of the production vehicle or the developed system,resulting in a traffic accident causing casualties,then the producer and the system R & D will bear the corresponding offence of negligence or constitute omission,or may reduce the criminal responsibility of the driver;the second is a traffic accident in the event of a failure of the driving system,and the driver will not be held criminally intentional or negligent.But this kind of situation is more complicated,the author still needs to carry on the analysis research to the self-driving system imputation.It is also important to note that when a driver sets a self-driving mode to drive a vehicle in a traffic accident,the chosen level will also have a certain impact on the level of criminal responsibility of the driver,because the different responsibility of the driver in different levels need to be determined in combination with the CarLog in the vehicle to determine the criminal responsibility of the driver.
Keywords/Search Tags:self-driving mode, traffic accident, driver, criminal liability
PDF Full Text Request
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