Vehicle-in-Virtual-Environment (VVE) Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving with Focus on Bicyclist Safety

TL;DR

This paper introduces a Vehicle-in-Virtual-Environment (VVE) method to develop and evaluate safety functions for vulnerable road users, especially bicyclists, in autonomous driving through simulated testing and automated control strategies.

Contribution

It presents a novel VVE testing framework for VRU safety, addressing gaps in planning, collision avoidance, and standardized testing in autonomous vehicle research.

Findings

Enhanced safety functions for bicyclists demonstrated in VVE simulations

Improved automated steering and braking strategies for VRUs

Validated VVE as an effective testing methodology for VRU safety

Abstract

Extensive research has already been conducted in the autonomous driving field to help vehicles navigate safely and efficiently. At the same time, plenty of current research on vulnerable road user (VRU) safety is performed which largely concentrates on perception, localization, or trajectory prediction of VRUs. However, existing research still exhibits several gaps, including the lack of a unified planning and collision avoidance system for autonomous vehicles, limited investigation into delay tolerant control strategies, and the absence of an efficient and standardized testing methodology. Ensuring VRU safety remains one of the most pressing challenges in autonomous driving, particularly in dynamic and unpredictable environments. In this two year project, we focused on applying the Vehicle in Virtual Environment (VVE) method to develop, evaluate, and demonstrate safety functions for Vulnerable Road Users (VRUs) using automated steering and braking of ADS. In this current second year project report, our primary focus was on enhancing the previous year results while also considering bicyclist safety.