Master thesis - Intelligent and Adaptive Driver Interaction

Background


Being a truck driver is a demanding work with many tasks and responsibilities. During driving, the truck driver has to manage the primary task of driving the heavy vehicle safely in complex traffic situations. Furthermore, performing secondary tasks will be needed, such as interacting with different truck systems, navigation aids, media, communication, and more.
It is an ongoing challenge for a truck manufacturer to design a safe, efficient, and satisfactory driver interaction. New technologies such as automation, electromobility, and connectivity will create new possibilities for the transport industry. However, at the same time, the amount of information will increase in the whole system. A particular challenge is to support the truck driver with the right information at the right time, to make sure the driver can perform the given tasks without information overload and risk of distraction.


Description of thesis work


One solution to this challenge could be to use the combined information (or data) related to the driver, to the vehicle, and to the traffic situation in order to adapt the interaction dynamically. This adaptivity can potentially be created by using simple rules connected to a specific user, or, by using a more advanced approach applying AI / machine learning algorithms. However, the potential of intelligent and adaptive interaction using AI / machine learning needs to be investigated; where does it add value for a user, what are the limitations, when is it not suitable? What other solutions do you see?


The goal of the thesis is to explore and develop concepts that support intelligent and adaptive interaction between the truck driver and the vehicle. The chosen concept(s) will be developed and evaluated using a user-centered design approach.


Steps to follow for a successful thesis work:
Create an overview and background of existing intelligent and adaptive interactive systems/products
Understand truck functions, and drivers’ tasks and needs
Identify potential use-cases that add user value
Create one or more concept(s)
Design an experiment to evaluate the concept(s)
Perform a user evaluation
Analyze the data and report



The following skills would be highly valuable:
Human factors
Interaction design
Prototyping – digital and physical
Experiment design
Statistical analysis
Knowledge in AI / machine learning



Thesis Level: Master

Language: English


Starting date: Beginning 2023


Number of students:
This thesis proposal is for 1 or 2 students
Tutor
Dennis Saluäär, +46-31-3229512, dennis.saluaar@volvo.com


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