This paper presents a comprehensive examination of two driver interface systems within the context of Ultra-Efficient Lightweight Electric Vehicles (ULEV) aimed at enhancing energy efficiency and optimizing driver focus. The vehicle employs two interface systems: a 10.1-inch touchscreen tablet with a custom Graphical User interface (GUI) that offers comprehensive data management, diagnostics, and control functionalities and a 5.5-inch wide, passive OLED display designed for ultra-low energy consumption. The tablet's advanced features come with the potential for driver distraction. In contrast, the OLED display takes a minimalist approach by presenting only critical information. This enhances driving focus and efficiency. This research utilizes a wearable eye-tracking device to measure drivers' focus and distraction levels while also logging driving performance and energy consumption data. The aim is to determine the most effective interface for promoting efficient driving practices. The study achieved significant insights into the balancing of information accessibility and cognitive load in driving while also optimizing energy efficiency. The results demonstrate the advantages of assistant systems, which reduce energy consumption by 11-15%, provide concentrated information projection, and minimize driver distraction.

In this paper, the application of an advanced telemetry system is introduced, which is used to monitor an electric, energy-efficient experimental urban vehicle. The system enables real-time observation of both the pilot's actions and vehicle parameters. The vehicle's pilot drives according to a predetermined driving strategy, optimized for minimizing energy consumption during vehicle operation. The telemetry system aims to provide real-time information about the pilot's driving and deviations from the predetermined strategy, offering additional opportunities for correction during operation. Additionally, it facilitates real-time observation of all vehicle and sensor data on the vehicle's CAN network. The paper discusses the determination of the driving strategy and presents its graphical representation for the pilot. A detailed description of the telemetry system's operation through wireless connection is provided in the paper. In terms of implementation, the driving strategy was formulated using MATLAB through optimization, while graphical display, data collection, and telemetry system development were implemented in the LabVIEW environment. The functionality of the created energy-efficient driving support framework was examined under real driving conditions. The application of the telemetry system and proposed hybrid optimization approach helped to further reduce the energy consumption by 8.54%.