Agentic Vehicles for Human-Centered Mobility: Definition, Prospects, and Synergistic Co-Development with Vehicle Autonomy
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Abstract (arXiv)
Autonomy, from the Greek autos (self) and nomos (law), refers to the capacity to operate according to internal rules without external control. Autonomous vehicles (AuVs) are therefore understood as vehicular systems that perceive their environment and execute tasks with minimal human intervention, consistent with the direction indicated by the SAE levels of automated driving. However, recent research and deployments increasingly showcase vehicular capabilities that, while not contradicting autonomy, are not entailed by it, including ambiguous goal handling, purposeful social engagement, external tool use, proactive problem solving, continuous learning, and context-sensitive reasoning in unseen and ethically salient situations, enabled in part by multimodal language models. These developments reveal a gap between technical autonomy and the broader social cognitive functions required for human-centered mobility, which are more precisely captured by the notion of agency. Therefore, rather than adding increasingly elaborate modifiers to "autonomous," we introduce agentic vehicles (AgVs) and suggest that autonomy and agency are intertwined but conceptually distinct: if autonomy concerns what to do and how to do it (task executions under internal rules), agency pertains to why to do it and what else can be done (goal-directed, adaptive actions). We present autonomy and agency as orthogonal yet synergistic dimensions with co-development implications. Vehicle agency marks a novel dimension of mobility service intelligence, heralding vehicles as purposeful actors in society.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 8 of its 61 references that are in the map. First posted on arXiv 7 Jul 2025.
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8 of 61 references.
References · 8
- 2019A Survey of Autonomous Driving: Common Practices and Emerging Technologiescited by 379
- 2023OpenAGI: When LLM Meets Domain Expertscited by 197
- 2025OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Modelcited by 176
- 2023Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videoscited by 17
- 2024Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Drivingcited by 9
- 2024Automating Traffic Model Enhancement with AI Research Agentcited by 8
- 2024Probabilistic Mission Design for Neuro-Symbolic Unmanned Aircraft Systemscited by 4
- 2024Synthetic Participatory Planning of Shard Automated Electric Mobility Systemscited by 3
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- 2022Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modelling
- 2025Self-Interest and Systemic Benefits: Emergence of Collective Rationality in Mixed Autonomy Traffic Through Deep Reinforcement Learning
- 2026A Survey of Reasoning in Autonomous Driving Systems: Open Challenges and Emerging Paradigms
- 2026Multi-Agent Embodied Autonomous Driving (MAEAD): From V2X Information Exchange to Shared World Models
- 2023A Language Agent for Autonomous Driving
- 2026doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving
- 2021Social Coordination and Altruism in Autonomous Driving