Designing Infotainment Interfaces to Enhance Electric Taxi Drivers Charging Understanding

Abstract

As the shift toward battery electric vehicles (BEVs) accelerates, electric taxi drivers are facing new challenges, with long operating hours having a direct impact on the number of times the vehicle needs to be charged. The achievement of optimal charging is influenced by a variety of factors, such as the state of charge of the battery, the temperature, and the charging capacity, which are not necessarily common knowledge for many drivers. This thesis investigates how in-car user interfaces can better support electric taxi drivers in understanding and managing the charging process to achieve efficient fast charging.

A user-centered research approach was used to explore the barriers to efficient fast BEV charging. The process involved literature reviews, interviews with taxi drivers and technical experts, surveys, and benchmarking of existing vehicle interfaces. Personas, user journey maps, and a requirement list were developed to ground the design process in real world needs. Based on this foundation, initial concepts were conceived through collaborative brainstorming and their feasibility was evaluated with experts. These concepts were further developed into low-fidelity prototypes and refined in three design iterations, incorporating user feedback from both electric taxi drivers and regular BEV drivers.

Through the findings, eight design recommendations were formulated aimed at guiding the development of user interfaces designed for BEV charging. These include principles such as providing contextual and transparent information, reducing cognitive load by unifying and prioritizing key charging metrics, and ensuring interface flexibility. Although the proposed solutions were tailored for electric taxi drivers, the insights reflect broader challenges relevant to the larger BEV user base.

This thesis contributes to research on the user experience of electric vehicles, highlighting how interface design can enable drivers to make informed charging decisions. The resulting recommendations can serve as a foundation for future infotainment interface development, both in commercial and private BEV contexts.