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Record STMT-W9E73B1Aspirational

Autonomous delivery robots: a legal framework for infliction of game-theoretic small penalties on pedestrians

Autonomous delivery robots: a legal framework for infliction of game-theoretic small penalties on pedestrians

Position paper State lawEurope · GBin force

This academic article explores the legal, ethical, and game-theoretic framework for operating autonomous delivery robots (ADRs) in pedestrian areas. It addresses the 'freezing robot problem' by proposing that ADRs be legally classified as pedestrians and permitted to make credible threats of inflicting small penalties (such as personal space invasion) based on principles of robot self-defence and the defence of property. The authors examine existing UK traffic regulations, product liability, negligence laws, and data protection implications under the GDPR.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

Informa UK Limited (Taylor & Francis Group)Industry · GB
Publisher
Legal forceAspirational
Under whose authorityState law
Judged fromfull text

Who it governs

Researchers and academicsNational governmentRegulatorsCompanies

Researchers, regulators, and legal scholars examining the intersection of autonomous systems, tort law, and urban mobility governance.

Sectors
Transport and mobility · autonomous delivery robotsResearch and science · law and technology research

What the document contains

What's covered

This document addresses the game-theoretic navigation models of autonomous delivery robots, their legal classification on shared pavements, the justification of small penalties through robot self-defence and property rights, and the resulting liability and data protection frameworks under UK law.

What's missing

The text does not provide formal binding regulatory mandates or enacted statutory text, but rather offers legal academic arguments and policy recommendations.

Key takeaways
  • Autonomous delivery robots must be able to make credible threats of inflicting small penalties to overcome the freezing robot problem during interactions with pedestrians.
  • ADRs could potentially be classified as pedestrians or mobility scooters under existing UK legal frameworks without requiring wholesale legislative overhauls.
  • Robot self-defence and the defence of property serve as conceptual legal bases for justifying the infliction of minor negative utilities or penalties.
  • Accidents resulting from failed control attempts during negotiations can be addressed via the tort of negligence, product liability laws, and the Automated and Electric Vehicles Act 2018.
  • The collection and processing of personal data for interaction control and profiling raise significant compliance challenges under the UK GDPR.
Outline
1. Introduction
2. Engineering background
3. Legal status of ADR
4. Wrongful interferences and justification for 'small penalties'
5. Liability framework for ADR accidents
6. Interaction control using personal information
7. Conclusions
Issued20 August 2024
Length15,071 words · 33 pages
FormatNot recorded
Scopenational

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

4/5

Clear responsibility for AI outcomes

The Law Commission proposes an approach that could remedy the lack of legal personhood for robots by distinguishing between user-in-charge and no-user-in-charge (NUIC) vehicles.

4.1.3. Robot personhood

screening score · 2026-10-23

Privacy

3/5

Protection of personal data and private life

During their decision-making processes, ADRs will inevitably collect data, some of which may be personal. The management and protection of this data are paramount.

6. Interaction control using personal information

screening score · 2026-10-23

Impact Assessment

0/5

Required assessment of an AI system's risks/impacts before or during use

screening score · 2026-10-23

Topics

autonomous_delivery_robots game_theory robot_self_defence data_protection liability_framework