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

arXiv: https://arxiv.org/abs/2308.15167 · HTML: https://mlsanity.com/paper/2308.15167/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2023.

## Built on by (most cited first, 1 of 1)

- [Generation of Training Data from HD Maps in the Lanelet2 Framework](https://mlsanity.com/paper/2407.17409/) (2024)

## Abstract (arXiv)

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.