CurrentJesper Kapteijns (2022) coached by Pavlo Bazilinskyy
Implicit communication plays a vital role in everyday traffic negotiations. Rather than through explicit communication, for example hand gestures and direct eye contact, vulnerable road users get a sense of the intentions of a vehicle by looking at its kinetic motion patterns. An increasing amount of driving tasks being taken over by automation results in even fewer possibilities for explicit communication with human drivers and an increased need for clear implicit communication in traffic.
Current aims to improve the implicit communication of kinetic motion patterns of vehicles. It does so with a light-based eHMI with a fluid motion visualization that responds to the amount of acceleration of a vehicle. When driving at a constant speed, the visualization appears to be at rest. When accelerating, the ‘fluid’ moves backwards, similar to how an actual fluid would respond to acceleration. When decelerating, it moves forwards. In situations where a vehicle is driving in an automated fashion, these visualizations can be displayed upfront to show prospective changes in kinetic motion patterns, which further improves anticipation in traffic
You may find the source code for the project at a repository on GitHub.