Plenty of blame to go around: Attributions of responsibility in a fatal autonomous vehicle accident

Copp, Christopher J.; Cabell, Jean J.; Kemmelmeier, Markus

doi:10.1007/s12144-021-01956-5

Cited by 16 publications

(11 citation statements)

References 18 publications

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“…Berdasarkan laporan Wolrd Health Organization (WHO), bahwa tercatat dari data 50.000 warga Indonesia yang mengalami kecelakaan, jumlah korban yang meninggal dunia sebanyak 22.000 jiwa. Peyebab utama sebuah kecelakaan lalu lintas adalah dipengaruhi oleh faktor kelalaian manusia seperti, tidak berhati-hati saat berkendaraan di tempat umum atau tidak menaati peraturan lalu lintas yang ada (Copp, 2023). Karena peristiwa kecelakaan lalu lintas tidak bisa di prediksi, dimana dan kapan akan terjadi.…”

Section: Pendahuluanunclassified

Analisis Yuridis Putusan Pengadilan Nomor 251/Pid.Sus/2015/PN.Sda tentang Kasus Kecelakaan yang Mengakibatkan Matinya Orang di Pengadilan Sidoarjo

Wulayana,

Rosnawati

2023

ResearchJet

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This study aims to determine whether the court’s decision number 251/Pid.Sus/2015/PN.Sda is a traffic accident that occurs due to negligence of the vehicle driver. Factors that cause traffic accidents come from drivers who are sleepy and less careful. Driver negligence which results in the death of people in traffic accidents is regulated in article 359 of the criminal code and can also be given sanctions or fines as regulated in Article 310 of Law No 22 of 2009. Therefore, the author uses the method Normative juridical as a from of implementation. The formulation of the promblem studied is to analyze the juridical court decision Number 251/Pid.Sus/2015/PN.Sda regarding negligence which resulted in the death of a person, finally legally resulted in the defendant being sentenced to 1 year in prison.

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Section: Pendahuluanunclassified

Analisis Yuridis Putusan Pengadilan Nomor 251/Pid.Sus/2015/PN.Sda tentang Kasus Kecelakaan yang Mengakibatkan Matinya Orang di Pengadilan Sidoarjo

Wulayana,

Rosnawati

2023

ResearchJet

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“…Using text vignettes, previous research identified a range of stakeholders in the road environment that could be assigned blame for collisions (Bennett et al, 2020). Generally, as the level of automation increases, the proportion of blame for a collision is shifted towards the vehicle system (Copp et al, 2021;Liu & Du, 2021;Pöllänen et al, 2020). However, as the previous studies utilized text vignettes, participants may have had different understandings of the imagined autonomous vehicle.…”

Section: Overall Objectivesmentioning

confidence: 99%

“…Using open ended questions, Bennett et al (2020) found that participants identified six stakeholders in the road environment responsible for some level of blame including the driver, pedestrian, vehicle system itself, government, manufacturer, and programmers. As control shifted away from the human, the proportion of blame shifted to a mixture of the driver, vehicle system, and the manufacturer (Copp et al, 2021;Pöllänen et al, 2020). That is, when considering the human driver and the vehicle system, individuals tend to assign more blame to the automation system as well as judge automation-caused crashes more negatively, known as Blame Attribution Asymmetry (Liu & Du, 2021).…”

Section: Introductionmentioning

confidence: 99%

Impact of Monitoring Requests on Trust, Acceptance, Blame, and Praise of Autonomous Vehicles

Kettle

Lee

2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Vehicles with autonomous features are more prevalent in today’s society, though as the level of autonomation increases, so does the vehicle system’s control of the vehicle. As the driving control shifts from human to the vehicle system, concerns arise regarding the attribution of responsibility and blame following critical events (e.g., collisions or near-misses). In this work-in-progress study, we aim to understand how the public attributes blame and praise to both humans and autonomous vehicles (AVs) following critical events. In addition, we examine how an AI driving assistant that administers Monitoring Requests influences blame and praise attributions. Furthermore, we examine differences in acceptance, trust, and perceived anthropomorphism between an AV with and without an AI driving assistant. Preliminary results are provided followed by a discussion of the expected results and potential impact for research and legal issues.

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“…Bennet et al (2020) identified six stakeholders in the road environment that participants found responsible for some level of blame including the driver, pedestrian, vehicle system itself, government, manufacturer, and programmers. Generally, as the levels of automation increased, and driving control shifts away from the human, participants placed less blame on the human driver and more blame on the vehicle system and the manufacturers (Copp et al, 2021; Pöllänen et al, 2020). This shift in blame from the human to the ADS as well as judging automation-caused crashes more negatively is known as the Blame Attribution Asymmetry (Liu & Du, 2021).…”

Section: Introductionmentioning

confidence: 99%

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

Kettle,

Lee

2023

Proceedings of the Human Factors and Ergonomics Society Annual

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Numerous collisions have occurred since integrating vehicles with automated driving system (ADS) features. Attributed responsibility following collisions differ dependent on level of automation or anthropomorphism. However, gender differences are yet to be examined. Thus, the current study examined gender differences in responsibility assignment following collisions involving an ADS-equipped vehicle and the influence of a driving assistant (DA) that administered monitoring requests. Participants read hypothetical scenarios and watched corresponding simulated videos with or without the DA present before assigning blame to the human or the ADS. Hypotheses included gender differences in overall blame assignment, and interaction effects between gender and DA presence; gender and agent; and gender, DA presence, and agent. Results indicated gender differences when assigning responsibility to the human agent only. No other significant differences were supported indicating that men and women generally attribute blame similarly. However, further demographic differences (e.g., age, socio-economic status) should be explored.

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Plenty of blame to go around: Attributions of responsibility in a fatal autonomous vehicle accident

Cited by 16 publications

References 18 publications

Analisis Yuridis Putusan Pengadilan Nomor 251/Pid.Sus/2015/PN.Sda tentang Kasus Kecelakaan yang Mengakibatkan Matinya Orang di Pengadilan Sidoarjo

Analisis Yuridis Putusan Pengadilan Nomor 251/Pid.Sus/2015/PN.Sda tentang Kasus Kecelakaan yang Mengakibatkan Matinya Orang di Pengadilan Sidoarjo

Impact of Monitoring Requests on Trust, Acceptance, Blame, and Praise of Autonomous Vehicles

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

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