Car for Wellbeing

Collaborative project with Ford Mobility

Car for Wellbeing

Brief

An in-car system aimed at reducing driving anxiety and improving the overall safety and well-being of drivers

Duration

Feb - May, 2024

Collaboration

Ford UK

Find Report ↗

My Role and Core Product

This project is jointly supervised by Daniel from Ford UK and Dr Anze from Loughborough University. Our core product is an in-car system designed to address driving anxiety, with specific regards to Vehicle Health, Anxiety Intervention, and Safety Response. The application is compatible with a full range of connected vehicles, including plug-in hybrid electric vehicles (PHEVs) and fully electric vehicles (EVs).

Allowing users to interact in multiple ways - from vehicle safety assessments, real-time anxiety data analysis, and emergency safety stops; all aimed at optimising vehicle performance.

As a User Experience Researcher, I am responsible for investigating user needs in specific contexts, analysing the strengths and weaknesses of different data sources and processing methods, ensuring the solution's comprehensiveness and feasibility.

Methodology and Process

  • Sketch, Miro - project management
  • Figma, Adobe AI - user interface design
  • Excel - data visualisation
  • Arduino - prototyping

Background

How can we reduce the likelihood and consequences of driving anxiety?

background introduction of this project

User Research

Personas and journey maps have been developed and continuously refined throughout the product's lifecycle, to better understand and address the needs of core user group. Here are a few examples:

persona and user journey map

Idea Iteration

Our journey through idea iteration was marked by exploration and refinement

User Interface for the system

Many aspects of the system may seem simple, but the integration of hardware, data, and software is very complex. Mistakes are not an option due to the importance of passenger health and safety.

Core Functions

  • Real-Time Anxiety Level Monitoring: Data sourced from sensors embedded in driver's seat and wearables, divide the anxiety-level into normal-mild-moderate-severe.
  • Personalised Settings: Quickly access and adjust personalised settings, like sensory preferences and avoiding certain road triggers.
  • Emergency Assistance: Includes safety parking and live roadside assistance.
  • Dynamic Information Hierarchy: Adjusts to different vehicle types and onboard technologies.
user interface of this complex system