Augmented Reality-Based Advanced Driver-Assistance System for Connected Vehicles
This work addresses the problem of driver guidance visualization for connected vehicles, which is an incremental improvement focusing on human-machine cooperation in a specific domain.
The study tackled the lack of human-machine interface research in connected vehicles by proposing an augmented reality-based advanced driver-assistance system that visualizes cooperative guidance information, resulting in reduced travel time and energy consumption in unsignalized intersection scenarios as validated through human-in-the-loop simulations.
With the development of advanced communication technology, connected vehicles become increasingly popular in our transportation systems, which can conduct cooperative maneuvers with each other as well as road entities through vehicle-to-everything communication. A lot of research interests have been drawn to other building blocks of a connected vehicle system, such as communication, planning, and control. However, less research studies were focused on the human-machine cooperation and interface, namely how to visualize the guidance information to the driver as an advanced driver-assistance system (ADAS). In this study, we propose an augmented reality (AR)-based ADAS, which visualizes the guidance information calculated cooperatively by multiple connected vehicles. An unsignalized intersection scenario is adopted as the use case of this system, where the driver can drive the connected vehicle crossing the intersection under the AR guidance, without any full stop at the intersection. A simulation environment is built in Unity game engine based on the road network of San Francisco, and human-in-the-loop (HITL) simulation is conducted to validate the effectiveness of our proposed system regarding travel time and energy consumption.