Active Safety System for Semi-Autonomous Teleoperated Vehicles

TL;DR

This paper introduces an Active Safety System for teleoperated vehicles that uses model predictive control to enhance safety, reduce collisions, and improve operator trust in complex urban environments with latency.

Contribution

It presents a novel MPC-based safety system that manages vehicle dynamics and incorporates a predictive display to handle latency in teleoperation.

Findings

Effective collision avoidance in complex environments

Improved operator trust through visual feedback

Robust performance under latency conditions

Abstract

Autonomous cars can reduce road traffic accidents and provide a safer mode of transport. However, key technical challenges, such as safe navigation in complex urban environments, need to be addressed before deploying these vehicles on the market. Teleoperation can help smooth the transition from human operated to fully autonomous vehicles since it still has human in the loop providing the scope of fallback on driver. This paper presents an Active Safety System (ASS) approach for teleoperated driving. The proposed approach helps the operator ensure the safety of the vehicle in complex environments, that is, avoid collisions with static or dynamic obstacles. Our ASS relies on a model predictive control (MPC) formulation to control both the lateral and longitudinal dynamics of the vehicle. By exploiting the ability of the MPC framework to deal with constraints, our ASS restricts the controller's authority to intervene for lateral correction of the human operator's commands, avoiding counter-intuitive driving experience for the human operator. Further, we design a visual feedback to enhance the operator's trust over the ASS. In addition, we propose an MPC's prediction horizon data based novel predictive display to mitigate the effects of large latency in the teleoperation system. We tested the performance of the proposed approach on a high-fidelity vehicle simulator in the presence of dynamic obstacles and latency.