Technologies for safe and resilient earthmoving operations: A systematic literature review

Resilience engineering relates to the ability of a system to anticipate, prepare, and respond to predicted and unpredicted disruptions. It necessitates the use of monitoring and object detection technologies to ensure system safety in excavation systems. Given the increased investment and speed of improvement in technologies, it is necessary to review the types of technology available and how they contribute to excavation system safety. A systematic literature review was conducted which identified and classified the existing monitoring and object detection technologies, and introduced essential enablers for reliable and effective monitoring and object detection systems including: 1) the application of multisensory and data fusion approaches, and 2) system-level application of technologies. This study also identified the developed functionalities for accident anticipation, prevention and response to safety hazards during excavation, as well as those that facilitate learning in the system. The existing research gaps and future direction of research have been discussed

Symbolic representation of scenarios in Bologna airport on virtual reality concept

This paper is a part of a big Project named Retina Project, which is focused in reduce the workload of an ATCO. It uses the last technological advances as Virtual Reality concept. The work has consisted in studying the different awareness situations that happens daily in Bologna Airport. It has been analysed one scenario with good visibility where the sun predominates and two other scenarios with poor visibility where the rain and the fog dominate. Due to the study of visibility in the three scenarios computed, the conclusion obtained is that the overlay must be shown with a constant dimension regardless the position of the aircraft to be readable by the ATC and also, the frame and the flight strip should be coloured in a showy colour (like red) for a better control by the ATCO

Building trust in autonomous vehicles: Role of virtual reality driving simulators in HMI design

The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish trust, depends on effective user-vehicle communication; thus, the importance of Human-Machine Interaction (HMI) is poised to increase. In this work, we propose a methodology to validate the user experience in AVs based on continuous, objective information gathered from physiological signals, while the user is immersed in a Virtual Reality-based driving simulation. We applied this methodology to the design of a head-up display interface delivering visual cues about the vehicle' sensory and planning systems. Through this approach, we obtained qualitative and quantitative evidence that a complete picture of the vehicle's surrounding, despite the higher cognitive load, is conducive to a less stressful experience. Moreover, after having been exposed to a more informative interface, users involved in the study were also more willing to test a real AV. The proposed methodology could be extended by adjusting the simulation environment, the HMI and/or the vehicle's Artificial Intelligence modules to dig into other aspects of the user experience

Personalising Vibrotactile Displays through Perceptual Sensitivity Adjustment

Haptic displays are commonly limited to transmitting a discrete set of tactile motives. In this paper, we explore the transmission of real-valued information through vibrotactile displays. We simulate spatial continuity with three perceptual models commonly used to create phantom sensations: the linear, logarithmic and power model. We show that these generic models lead to limited decoding precision, and propose a method for model personalization adjusting to idiosyncratic and spatial variations in perceptual sensitivity. We evaluate this approach using two haptic display layouts: circular, worn around the wrist and the upper arm, and straight, worn along the forearm. Results of a user study measuring continuous value decoding precision show that users were able to decode continuous values with relatively high accuracy (4.4% mean error), circular layouts performed particularly well, and personalisation through sensitivity adjustment increased decoding precision

GROUND VEHICLE DRIVING AIDS: ASSESSING DRIVER WORKLOAD AND PERFORMANCE IN DEGRADED VISUAL ENVIRONMENTS

With degraded visual environments being a current priority to the Army, several research programs have been initiated to develop a complete sensor-to-soldier systems to allow operators to see through DVE conditions while conducting ground vehicle tactical operations. To enable indirect-driving maneuverability and threat detection in degraded visual environments (DVEs), CCDC’s ground DVE program developed and tested a range of sensors and driver aid display systems. Six candidate driving aids were identified and tested in three simulator studies and two field tests to examine the effect of driving aids on driver workload and performance in different visibility conditions. The simulator-based testing revealed human factors issues such as the importance of the symbology of the aids used and how obstacles should be presented when designing individual displays. Soldiers were generally accepting of the overall gDVE system in field testing with no costs or benefits revealed using the driving aids. Before future development of the driving aids, a more human-centered design process must be pursued to optimize the human-system interaction to design driving aids that help performance and lower workload in degraded visual environments

Ehmi: Review and guidelines for deployment on autonomous vehicles

Human-machine interaction is an active area of research due to the rapid development of autonomous systems and the need for communication. This review provides further insight into the specific issue of the information flow between pedestrians and automated vehicles by evaluating recent advances in external human-machine interfaces (eHMI), which enable the transmission of state and intent information from the vehicle to the rest of the traffic participants. Recent developments will be explored and studies analyzing their effectiveness based on pedestrian feedback data will be presented and contextualized. As a result, we aim to draw a broad perspective on the current status and recent techniques for eHMI and some guidelines that will encourage future research and development of these systems