Dynamic Collaborative Path Planning for Remote Assistance of Highly-Automated Vehicles

TL;DR

This paper introduces a novel hybrid approach for remote assistance of highly-automated vehicles in urban settings, combining automated systems and human reasoning to enhance safety and user experience.

Contribution

It proposes a hybrid algorithm utilizing ODD modification and cognitive reasoning to improve collaborative path planning in remote vehicle assistance.

Findings

Enhanced collaboration between automation and human operators.

Potential for improved safety and efficiency in urban autonomous driving.

Framework adaptable to complex driving scenarios.

Abstract

Given its increasing popularity in recent years, teleoperation technology is now recognized as a robust fallback solution for Automated Driving (AD). Remote Assistance (RA) represents an event-driven class of teleoperation with a distinct division of tasks between the Autonomous Vehicle (AV) and the remote human operator. This paper presents a novel approach for RA of AVs in urban environments. The concept draws inspiration from the potential synergy between highly-automated systems and human operators to collaboratively solve complex driving situations. Utilizing a hybrid algorithm that makes use of the Operational Design Domain (ODD) modification idea, it considers actions that go beyond the nominal operational space. Combined with the advanced cognitive reasoning of the human remote operator, the concept offers features that hold the potential to significantly improve both RA and AD user experiences.