Charting the Future of Mobility
Visualizing Autonomous Electric Vehicle Fleets
By Dan McCarey
In a groundbreaking project with Marain, an AI startup later acquired by BrightDrop, I had the opportunity to delve into the forefront of autonomous mobility. My role was to translate complex models of autonomous electric vehicle fleets into a dynamic, interactive visualization.
The project showcased the transformative impact of combining AI, data visualization, and user-centric design in advancing the future of mobility.
This tool was designed to interpret and animate various scenarios, such as the number of vehicles, the placement of charging stations, and vehicle coordinates, presenting them in an engaging and informative manner.
The main challenge was transforming intricate, multi-dimensional data into a visually intuitive and insightful narrative. The objective was to create an application that could accurately depict the modeled scenarios, while being user-friendly and visually appealing.
This visualization was crucial for clients integrating autonomous vehicle technologies into their operations, aiding in strategic decision-making.
Utilizing Deck GL's trips layer, I animated the movement of vehicles, providing a real-time portrayal of the fleet dynamics. This geospatial visualization offered an overarching view of the operational flow. To complement this, I used D3.js for rendering detailed data metrics like charge levels, adding a deeper analytical dimension to the map.
A distinctive feature of the application was its ability to aggregate data not just in the conventional animated vehicle view but also by neighborhood. This functionality provided users with multiple perspectives on the data, allowing for a comprehensive understanding of patterns and trends at both a granular and a broader community level. This multi-layered approach to data aggregation offered valuable insights into the efficiency and distribution of the fleet across different urban landscapes.
In designing the interface, I prioritized both functionality and aesthetics, ensuring the map was aligned with the brand's visual identity. The result was a beautiful, branded map that was not only rich in data but also visually engaging, enhancing its integration into client dashboards.
Seamlessly integrated into client dashboards, the application became an essential tool for analyzing and managing autonomous electric vehicle fleets. It enabled clients to interact with the data dynamically, exploring various scenarios and deriving actionable insights from both real-time and modeled data.
This collaboration highlighted the potential of effectively visualizing complex AI models for practical applications. The project showcased the transformative impact of combining AI, data visualization, and user-centric design in advancing the future of mobility.