Workshop on Remote Operation of Intelligent Connected and Automated Road Vehicles

Title: Trajectory Guidance: Enhanced Remote Driving of highly-automated Vehicles

Presenter: Frank Diermeyer, Technical University of Munich, Germany

Abstract:

Despite the rapid technological progress, autonomous vehicles still face a wide range of complex driving situations that require human intervention. Teleoperation technology offers a versatile and effective way to address these challenges. The following work puts existing ideas into a modern context and introduces a novel technical implementation of the trajectory guidance teleoperation concept. The presented system was developed within a high-fidelity simulation environment and experimentally validated, demonstrating a realistic ride-hailing mission with prototype autonomous vehicles and onboard passengers. The results indicate that the proposed concept can be a viable alternative to the existing remote driving options, offering a promising way to enhance teleoperation technology and improve overall operation safety.

Title: Enhanced Model-Free Predictor for Latency Compensation in Remote Driving Systems

Presenter: Lin Zhao, KTH Royal Institute of Technology, Sweden

Abstract:

Remote driving plays a vital role in coordinating automated vehicles in challenging situations. Data transmission latency, however, can cause several problems in remote driving. Firstly, it can degrade the performance of remote-controlled vehicles, evident in issues like lane-following deviation and vehicle stability. Additionally, the remote control tower's driving feedback is affected by delayed vehicle signals, leading to delayed driving experience. To address this, a model-free-based predictor is employed to compensate for the delay in remote driving. This approach does not require any dynamic model of the system and only needs tuning of two parameters to reduce communication delay. This study enhances the previous work by mitigating the amplitude of overshoot around peak points. It leverages the principle of the second-order derivative to predict the signal's peak time and uses it to address the predictor's overshoot issue. The effectiveness of the proposed method is validated using real car data from multiple participants in two scenarios, including Slalom and lane-following. Simulation results indicate that the proposed method can reduce prediction error by nearly 25% compared to previous works. Moreover, the solutions in this study are capable of managing not only delays in remote driving vehicles but also in traditional mechanical systems, such as CAN bus delays in conventional cars.

Title: Scalable Remote Operation for Autonomous Vehicles: Integration of Cooperative Perception and Open Source Communication

Presenter: Martin Gontscharow, FZI Research Center for Information Technology, Germany

Abstract:

As autonomous vehicles become increasingly prevalent, robust remote operation systems are imperative to ensure safety and reliability in unpredictable scenarios. Current remote operation systems in research often lack scalability and adaptability, hindering their integration into diverse autonomous driving platforms. This paper addresses these challenges by introducing a scalable remote operation system that leverages cooperative perception and an open-source communication module. Field tests conducted with an SAE Level 3 autonomous shuttle have validated the effectiveness of our system in real-world scenarios. The code for a key component of this system, the communication module, is available online:

The ROS Communication DevContainer (github.com) External link.

Title: Effect of Format of Presentation on Remote Assistance of Automated Vehicles

Presenter: Clare Mutzenich, 7th Sense Research, United Kingdom

Abstract:

Remote operators (ROs) of automated vehicles will be unable to provide remote assistance until they gain necessary situation awareness (SA). A critical question for the industry concerns the optimal format to deliver information to an RO. In this study, we consider remote assistance of automated vehicles using a choice decision task to test the effect of two formats of presentation of 360° driving videos: 1) in a head mounted display (HMD-360) where field of view (FOV) changes were based on head movement and 2) screen-based (SB) mouse-controlled FOV. Participants viewed 60 videos depicting scenarios categorised into seven groups, each representing different types of edge cases commonly encountered in real-world situations by ROs and distributed across various decision choices (left, right, forward, or reverse). Decision time and accuracy of decision were recorded. Analysis revealed significantly quicker decisions and higher accuracy in the HMD-360 condition. We recommend exploring HMD-360 presentation to improve operator SA in remote assistance of AVs, while cautioning against prolonged HMD use to mitigate potential discomfort.

Title: The role of task-switching cost in remote operation of driverless vehicle fleet

Presenter: Yanbin Wu, National Institute of Advanced Industrial Science and Technology, Japan

Abstract:

The remote operation of automated vehicles stands as a pivotal technological solution for bridging the current driving automation technology toward the realization of safe and efficient mobility services. In the context of passenger vehicles, such as driverless buses, a remote operator will need to switch attention among different vehicles and tasks, which can include both driving-related and passenger-service related tasks. The potential cost associated with such switching may impact the operator’s performance in providing effective remote support. This study aimed to investigate the effect of task-switching costs in the remote operation of automated vehicle fleet. In an experiment involving 60 participants spanning three age groups, participants were instructed to perform remote operation tasks under three task-switching conditions. The results revealed that although a constant switch between two tasks did not affect the remote operator’s performance, there was a significant slowdown when participants randomly switched between three different tasks. Furthermore, older participants reacted significantly more slowly than younger and middle-aged participants in performing the remote operation tasks. These findings emphasized the necessity of considering the time required for remote operators to shift their attention when determining an optimal human-to-vehicle ratio. Additionally, although older participants reacted more slowly in performing the operation tasks, their response accuracies were comparable to younger and middle-aged participants, indicating that they remain suited to serve as remote operators as long as their slightly slower pace is accommodated.