Please note

Due to active NDAs, this section only vaguely outlines the visual and manual attention methods I have used to evaluate new designs and features within Google Maps. This page provides a high-level outline of the methods I have employed, the reasoning behind my decisions, and the impact the resulting data have had on the product space.

Driver Safety & Attention

Google Maps

2021 - current

I utilized a range of cognitive attention methods to evaluate new navigation features while driving based on standardized safety criteria.

Problem

In the driving space, ensuring all navigation app features minimize distraction and meet the standards for safe interactions is critical. Organizations such as the National Highway Traffic Safety Association (NHTSA) and the International Standardization Organization (ISO) have set guidelines to test the amount of cognitive effort it takes to interact with a product while also operating a vehicle. One of the most important factors to consider is the idea of cognitive load: how much attention a person can give to a task or while multi-tasking before the person starts failing tasks because too much is going on at once. As driving already incurs a heavy cognitive load, we employ rigorous testing procedures to ensure new navigation features will be safe to use on the road.

Role

I have planned, executed, and reported on safety research on a range of new driving related features in Google Maps.

Question

Does this new feature meet all visual and manual attention requirements set forth by the automative industry as well as our own product standards?

Tools + Methods

Detection Response Task (DRT)

Eye-tracking glance metrics (via Tobii)

Driving Performance (via Silab Sim)

Performance and Perception Metrics

Study SettingS

Small scale simulator

Full driving simulator

On-road in-vehicle studies