Evidence map›Paper›PMID 39853674›Full record

ArticleScience and engineering ethics2025

Moral Complexity in Traffic: Advancing the ADC Model for Automated Driving Systems.

Dario Cecchini, Veljko Dubljević

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science and engineering ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dario CecchiniDepartment of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC, USA.ORCID 0000-0003-0943-5898
Veljko DubljevićDepartment of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC, USA. veljko_dubljevic@ncsu.edu.ORCID 0000-0003-3606-587X

Funding

Directorate for Social, Behavioral and Economic Sciences 2043612
6 · The paper itself

Abstract

The incorporation of ethical settings in Automated Driving Systems (ADSs) has been extensively discussed in recent years with the goal of enhancing potential stakeholders' trust in the new technology. However, a comprehensive ethical framework for ADS decision-making, capable of merging multiple ethical considerations and investigating their consistency is currently missing. This paper addresses this gap by providing a taxonomy of ADS decision-making based on the Agent-Deed-Consequences (ADC) model of moral judgment. Specifically, we identify three main components of traffic moral judgment: driving style, traffic rules compliance, and risk distribution. Then, we suggest distinguishable ethical settings for each traffic component.

Indexed as

AutomationAutomobile DrivingDecision MakingJudgmentMoralsAccidents, TrafficAutomobilesHumansModels, TheoreticalTrustADC Model of moral judgmentAutonomous vehicle decision-makingAutonomous vehicle ethicsTraffic moral judgment

Identifiers

PMID39853674
PMCPMC11761772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.