Understanding User Requirements for Creating Sensor-Powered Smart Car Cabins Through Retrofitting

2026-03-07

AI Summary

This study addresses the limited functionality of factory-installed intelligent cockpit sensors in current vehicles, which often fails to meet users’ diverse needs. To bridge this gap, the research employs a two-phase user-centered investigation combining semi-structured interviews with probe-based participatory design methods to uncover authentic user behaviors and expectations in real-world driving contexts. Building on these insights, the work presents the first systematic framework of user requirements and design principles specifically tailored for aftermarket intelligent cockpit sensor retrofits. The findings not only compensate for the perceptual limitations of original equipment but also yield a set of actionable design recommendations, offering both theoretical grounding and practical guidance for the development of human–vehicle interaction systems in the aftermarket automotive domain.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Activity and Plan Recognition

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

In this paper, we explore a novel approach that leverages retrofitting to create sensor-powered smart car cabins. We propose that retrofitting offers a promising way to complement and extend the capabilities of built-in smart cabin sensors provided by car manufacturers. To understand how retrofitting solutions should be designed, we conducted a two-phase study. First, through semi-structured interviews with 18 participants, we examined challenges with built-in smart cabin sensors and identified opportunities where retrofitting could address these limitations. Second, through probe-based participatory design sessions with 15 participants, we identified user requirements and expectations for effective retrofit solutions. Based on our findings, we present a set of design recommendations to guide the future development of retrofit methods for smart car cabins.

Problem

• smart car cabins
• retrofitting
• user requirements
• sensor limitations
• in-vehicle sensing

Innovation

• retrofitting
• smart car cabin
• sensor-powered
• user requirements
• participatory design