Park4U Mate: Context-Aware Digital Assistant for Personalized Autonomous Parking
Antonyo Musabini, Evin Bozbayir, Herv\'e Marcasuzaa, Omar Adair Islas, Ram\'irez

TL;DR
This paper introduces Park4U Mate, a context-aware voice-based digital assistant for autonomous parking that adapts to interior and exterior vehicle contexts, demonstrating effective decision-making and user-friendly interaction.
Contribution
The paper presents a novel voice-based assistant integrated with a smart parking strategy that considers vehicle context, enhancing autonomous parking and human-machine interaction.
Findings
The optimization algorithm efficiently determines optimal parking strategies.
Users find voice interaction clear and effective for autonomous parking.
Multi-modal interaction is preferred over voice-only methods.
Abstract
People park their vehicle depending on interior and exterior contexts. They do it naturally, even unconsciously. For instance, with a baby seat on the rear, the driver might leave more space on one side to be able to get the baby out easily; or when grocery shopping, s/he may position the vehicle to remain the trunk accessible. Autonomous vehicles are becoming technically effective at driving from A to B and parking in a proper spot, with a default way. However, in order to satisfy users' expectations and to become trustworthy, they will also need to park or make a temporary stop, appropriate to the given situation. In addition, users want to understand better the capabilities of their driving assistance features, such as automated parking systems. A voice-based interface can help with this and even ease the adoption of these features. Therefore, we developed a voice-based in-car…
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