Zoox

At Zoox, on the Rider Experience team, the project explored how autonomous vehicles communicate with passengers in the absence of a human driver. The work focused on high-fidelity prototyping and the development of spatial interaction systems that translated complex rider needs into testable vehicle behaviors. I contributed to the architecture of the hardware and software pipelines required to evaluate in-cabin experiences and seamless device handoff, including early research into how riders locate and approach the vehicle in public space, later reflected in Find My Zoox.

To facilitate these evaluations, I built a multimodal sensing and feedback architecture that allowed the design team to iterate on complex behaviors in real time. This system integrated custom embedded hardware with the vehicle’s communication networks to orchestrate coordinated sequences of light and sound. I developed a unified animation pipeline and remote orchestration tools that enabled designers to tune interaction parameters directly on the vehicle, significantly accelerating the validation of production-intent features and ensuring consistent feedback across the passenger journey.

A primary challenge involved ensuring reliable system performance within the unique physical constraints of the vehicle environment. I led the development of filtering and triangulation methodologies to manage sensor noise and optimize proximity-based interactions. This included prototyping specialized wireless networks to estimate rider position with high precision, work that informed a broader strategy for wayfinding using a direct wireless interface and helped define how the vehicle identifies and welcomes its passengers.

The resulting prototypes were deployed in internal testing environments, providing a standardized platform for the research team to conduct quantitative studies on passenger trust and interaction ergonomics. This work became an integral part of the UX validation pipeline, allowing the team to bridge the gap between digital concepts and physical manufacturing. By scaling these high-fidelity systems, we were able to validate the architectural impact of the rider experience before final vehicle deployment.