Analytical Study on the Visibility of Potential Positions for External Human-Machine Interfaces

TL;DR

This study tackles determining where external signaling on autonomous vehicles should be placed to maximize pedestrian visibility. It introduces a Unity-based simulation that ray-casts visibility from sidewalks across 15 vehicle types and many occlusion scenarios, producing heatmaps of visible surface points. Key findings identify frontal fenders and headlights as the most visible regions, with visibility patterns varying by distance, vehicle position, and occlusion, supporting a distributed eHMI design approach. The work provides open-source software and heatmaps to guide designers in selecting multi-surface signaling configurations that enhance pedestrian safety in diverse road contexts.

Abstract

As we move towards a future of autonomous vehicles, questions regarding their method of communication have arisen. One of the common questions concerns the placement of the signaling used to communicate with pedestrians and road users, but little work has been published fully dedicated to exploring this. This paper uses a simulation made in the Unity game engine to record the visibility of fifteen different vehicles, specifically regarding the visibility of frontal elements by a pedestrian on the sidewalk. Variables include the vehicle position, number of vehicles on the road, and minimum and maximum distance of the recorded points. It was concluded that the areas of the vehicle most often seen by pedestrians on the sidewalk attempting to cross the road were the frontal frontal fenders and the headlights, with the frontal wheels, frontal doors, bumper, and side mirrors are less visible alternatives. These findings are valuable in the future design of signaling for autonomous vehicles, in order to ensure pedestrians are able to see them on approaching vehicles. The software used provides a platform for similar works in the future to be conducted.

Figures (12)

• Figure 2: Screenshot of the simulation running. Red lines indicate the trajectory of the ray-casts that have hit the Target Vehicle.
• Figure 3: Top-Down View of the Virtual Street Layout.
• Figure 4: Top-Down View of the fifteen vehicles used in the simulations. Color denotes the category of each vehicle: (a) Small (b) Medium (c) Large (d) Extra Large
• Figure 5: Diagram illustrating the ten possible sidewalk camera positions, and the eight possible vehicle positions, based on the size categories of the target vehicle. (a) Small vehicles (b) Medium vehicles (c) Large vehicles (d) Extra large vehicles.
• Figure 6: Diagram illustrating the eight Camera Directions that a camera may take at any given Camera Position, each identified by a the cardinal or ordinal direction relative to the overhead camera: East (1), North-East (2), North (3), North-West (4), West (5), South-West (6), South (7), and South-East (8).