Experiences in teleoperation of land vehicles

Teleoperation of land vehicles allows the removal of the operator from the vehicle to a remote location. This can greatly increase operator safety and comfort in applications such as security patrol or military combat. The cost includes system complexity and reduced system performance. All feedback on vehicle performance and on environmental conditions must pass through sensors, a communications channel, and displays. In particular, this requires vision to be transmitted by close-circuit television with a consequent degradation of information content. Vehicular teleoperation, as a result, places severe demands on the operator. Teleoperated land vehicles have been built and tested by many organizations, including Sandia National Laboratories (SNL). The SNL fleet presently includes eight vehicles of varying capability. These vehicles have been operated using different types of controls, displays, and visual systems. Experimentation studying the effects of vision system characteristics on off-road, remote driving was performed for conditions of fixed camera versus steering-coupled camera and of color versus black and white video display. Additionally, much experience was gained through system demonstrations and hardware development trials. The preliminary experimental findings and the results of the accumulated operational experience are discussed

Design and implementation of a teleoperator’s workstation

Treball desenvolupat en el marc del programa "European Project Semester".The project aims to implement a way for a teleoperator to control an existing self-driving car if the autonomous driving algorithms fail to respond to the encountered situation. The project will rely on the existing code developed by the MechLab Team at the HTW in Dresden, who have converted a BMW i3 into a self-driving car using surround and proximity sensors and a homemade software that controls the vehicle's speed and steering. The car is also able to detect pedestrians and other obstacles thanks to a deep learning algorithm dedicated to this part. Teleoperation systems pose many challenges, such as providing the teleoperator with the same level of situational awareness as a driver in the car. The driver needs to focus more on the surroundings, and therefore teleoperated drivers will have to rest more often and take more breaks. To address this challenge, the teleoperation system will use high information density sensors, including LiDAR, radar, and ultrasonic sensors, to provide the driver with an overlay of detected obstacles and the predicted path, enhancing reality to compensate for latency in communication by taking some workload off the operator. Another big challenge is to switch between the autonomous and teleoperated driving modes, as there are different problems that can appear. Most noticeably, during the time it takes for the operator to get aware of the situation and respond to the call, the car must be able to safely stop and wait for instructions from the operator. The failure to do so could result in dangerous or even deadly situations for the autonomous vehicle’s occupants as well as for the other road users, who do not need to wait for the communication to be established. One of the last great challenges is allow stable and fast communication between the car and the teleoperator. This can be achieved by narrowing the data transmitted for example by reducing video quality in predefined cases, or by ensuring redundancy in the communication media. Nevertheless, a complete loss of communication is not impossible, so a protocol needs to be defined in order to safely halt the vehicle while waiting on the reconnection of the transmission. To fulfil this project, our team will use MATLAB and Simulink in combination with different toolboxes from the MathWorks company. We will try to develop a human-machine interface for the teleoperator, implement a way for the operator to take over control of the vehicle, build scenarios to test and simulate our different programs and much more. All of this is done in order to build safer and more reliable autonomous vehicles for the future.Incomin

Evaluation of off-road terrain with static stereo and monoscopic displays

The National Aeronautics and Space Administration is currently funding research into the design of a Mars rover vehicle. This unmanned rover will be used to explore a number of scientific and geologic sites on the Martian surface. Since the rover can not be driven from Earth in real-time, due to lengthy communication time delays, a locomotion strategy that optimizes vehicle range and minimizes potential risk must be developed. In order to assess the degree of on-board artificial intelligence (AI) required for a rover to carry out its' mission, researchers conducted an experiment to define a no AI baseline. In the experiment 24 subjects, divided into stereo and monoscopic groups, were shown video snapshots of four terrain scenes. The subjects' task was to choose a suitable path for the vehicle through each of the four scenes. Paths were scored based on distance travelled and hazard avoidance. Study results are presented with respect to: (1) risk versus range; (2) stereo versus monocular video; (3) vehicle camera height; and (4) camera field-of-view

A Survey on Remote Operation of Road Vehicles

In recent years, the use of remote operation has been proposed as a bridge towards driverless mobility by providing human assistance remotely when an automated driving system finds a situation that is ambiguous and requires input from a remote operator. The remote operation of road vehicles has also been proposed as a way to enable drivers to operate vehicles from safer and more comfortable locations. While commercial solutions for remote operation exist, remaining challenges are being tackled by the research community, who is continuously testing and validating the feasibility of deploying remote operation of road vehicles on public roads. These tests range from the technological scope to social aspects such as acceptability and usability that affect human performance. This survey presents a compilation of works that approach the remote operation of road vehicles. We start by describing the basic architecture of remote operation systems and classify their modes of operation depending on the level of human intervention. We use this classification to organize and present recent and relevant work on the field from industry and academia. Finally, we identify the challenges in the deployment of remote operation systems in the technological, regulatory, and commercial scopes

Driverless road-marking Machines: Ma(r)king the Way towards the Future of Mobility

Driverless road maintenance could potentially be highly beneficial to all its stakeholders, with the key goals being increased safety for all road participants, more efficient traffic management, and reduced road maintenance costs such that the standard of the road infrastructure is sufficient for it to be used in Automated Driving (AD). This paper addresses how the current state of technology could be expanded to reach those goals. Within the project 'System for Teleoperated Road-marking' (SToRM), using the road-marking machine as the system, different operation modes based on teleoperation were discussed and developed. Furthermore, a functional system overview considering both hardware and software elements was experimentally validated with an actual road-marking machine and should serve as a baseline for future efforts in this and similar areas.Comment: Accepted at 2022 IEEE International Conference on Systems, Man and Cybernetics (SMC

SARSCEST (human factors)

People interact with the processes and products of contemporary technology. Individuals are affected by these in various ways and individuals shape them. Such interactions come under the label 'human factors'. To expand the understanding of those to whom the term is relatively unfamiliar, its domain includes both an applied science and applications of knowledge. It means both research and development, with implications of research both for basic science and for development. It encompasses not only design and testing but also training and personnel requirements, even though some unwisely try to split these apart both by name and institutionally. The territory includes more than performance at work, though concentration on that aspect, epitomized in the derivation of the term ergonomics, has overshadowed human factors interest in interactions between technology and the home, health, safety, consumers, children and later life, the handicapped, sports and recreation education, and travel. Two aspects of technology considered most significant for work performance, systems and automation, and several approaches to these, are discussed

Conception of control paradigms for teleoperated driving tasks in urban environments

Development of concepts and computationally efficient motion planning methods for teleoperated drivingEntwicklung von Konzepten und recheneffizienten Bewegungsplanungsmethoden für teleoperiertes Fahre