Park4U Mate: Context-Aware Digital Assistant for Personalized Autonomous Parking

by   Antonyo Musabini, et al.

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 assistant (Park4U Mate), that is aware of interior and exterior contexts (thanks to a variety of sensors), and that is able to park autonomously in a smart way (with a constraints minimization strategy). The solution was demonstrated to thirty-five users in test-drives and their feedback was collected on the system's decision-making capability as well as on the human-machine-interaction. The results show that: (1) the proposed optimization algorithm is efficient at deciding the best parking strategy; hence, autonomous vehicles can adopt it; (2) a voice-based digital assistant for autonomous parking is perceived as a clear and effective interaction method. However, the interaction speed remained the most important criterion for users. In addition, they clearly wish not to be limited on only voice-interaction, to use the automated parking function and rather appreciate a multi-modal interaction.


page 1

page 3

page 4


Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehicles

This paper issues an integrated control system of self-driving autonomou...

Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles

The future of autonomous vehicles lies in the convergence of human-centr...

MIRIAM: A Multimodal Chat-Based Interface for Autonomous Systems

We present MIRIAM (Multimodal Intelligent inteRactIon for Autonomous sys...

Providentia -- A Large Scale Sensing System for the Assistance of Autonomous Vehicles

The environmental perception of autonomous vehicles is not only limited ...

Rapidly-exploring Random Trees-based Test Generation for Autonomous Vehicles

Autonomous vehicles are in an intensive research and development stage, ...

Navigating in the Dark – Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments

Age-related macular degeneration is a leading cause of blindness worldwi...

Designing an Automated Vehicle: Strategies for Handling Tasks of a Previously Required Accompanying Person

When using a conventional passenger car, several groups of people are re...

Please sign up or login with your details

Forgot password? Click here to reset