1,244 research outputs found
A Testing and Experimenting Environment for Microscopic Traffic Simulation Utilizing Virtual Reality and Augmented Reality
Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual environment with various traffic entities. Typically, the movements of the vehicles in MTS follow some predefined algorithms, e.g., car-following models, lane changing models, etc. Moreover, existing MTS models only provide a limited capability of two- and/or three-dimensional displays that often restrict the userâs viewpoint to a flat screen. Their downscaled scenes neither provide a realistic representation of the environment nor allow different users to simultaneously experience or interact with the simulation model from different perspectives. These limitations neither allow the traffic engineers to effectively disseminate their ideas to various stakeholders of different backgrounds nor allow the analysts to have realistic data about the vehicle or pedestrian movements. This dissertation intends to alleviate those issues by creating a framework and a prototype for a testing environment where MTS can have inputs from user-controlled vehicles and pedestrians to improve their traffic entity movement algorithms as well as have an immersive M3 (multi-mode, multi-perspective, multi-user) visualization of the simulation using Virtual Reality (VR) and Augmented Reality (AR) technologies. VR environments are created using highly realistic 3D models and environments. With modern game engines and hardware available on the market, these VR applications can provide a highly realistic and immersive experience for a user. Different experiments performed by real users in this study prove that utilizing VR technology for different traffic related experiments generated much more favorable results than the traditional displays. Moreover, using AR technologies for pedestrian studies is a novel approach that allows a user to walk in the real world and the simulation world at a one-to-one scale. This capability opens a whole new avenue of user experiment possibilities. On top of that, the in-environment communication chat system will allow researchers to perform different Advanced Driver Assistance System (ADAS) studies without ever needing to leave the simulation environment. Last but not least, the distributed nature of the framework enables users to participate from different geographic locations with their choice of display device (desktop, smartphone, VR, or AR). The prototype developed for this dissertation is readily available on a test webpage, and a user can easily download the prototype application without needing to install anything. The user also can run the remote MTS server and then connect their client application to the server
Realistic pedestrian behaviour in the CARLA simulator using VR and mocap
Simulations are gaining increasingly significance in the field of autonomous
driving due to the demand for rapid prototyping and extensive testing.
Employing physics-based simulation brings several benefits at an affordable
cost, while mitigating potential risks to prototypes, drivers, and vulnerable
road users. However, there exit two primary limitations. Firstly, the reality
gap which refers to the disparity between reality and simulation and prevents
the simulated autonomous driving systems from having the same performance in
the real world. Secondly, the lack of empirical understanding regarding the
behavior of real agents, such as backup drivers or passengers, as well as other
road users such as vehicles, pedestrians, or cyclists. Agent simulation is
commonly implemented through deterministic or randomized probabilistic
pre-programmed models, or generated from real-world data; but it fails to
accurately represent the behaviors adopted by real agents while interacting
within a specific simulated scenario. This paper extends the description of our
proposed framework to enable real-time interaction between real agents and
simulated environments, by means immersive virtual reality and human motion
capture systems within the CARLA simulator for autonomous driving. We have
designed a set of usability examples that allow the analysis of the
interactions between real pedestrians and simulated autonomous vehicles and we
provide a first measure of the user's sensation of presence in the virtual
environment.Comment: This is a pre-print of the following work: Communications in Computer
and Information Science (CCIS, volume 1882), 2023, Computer-Human Interaction
Research and Applications reproduced with permission of Springer Nature. The
final authenticated version is available online at:
https://link.springer.com/chapter/10.1007/978-3-031-41962-1_5. arXiv admin
note: substantial text overlap with arXiv:2206.0033
Development of a mechanical maintenance training simulator in OpenSimulator for F-16 aircraft engines
Mechanical maintenance of F-16 engines is carried out as a team effort involving 3â4 skilled engine technicians, but the details of its procedures and requisites change constantly, to improve safety, optimize resources, and respond to knowledge learned from field outcomes. This provides a challenge for development of training simulators, since simulated actions risk becoming obsolete rapidly and require costly reimplementation. This paper presents the development of a 3D mechanical maintenance training simulator for this context, using a low-cost simulation platform and a software architecture that separates simulation control from simulation visualization, in view of enabling more agile adaptation of simulators. This specific simulator aims to enable technician training to be enhanced with cooperation and context prior to the training phase with actual physical engines. We provide data in support of the feasibility of this approach, describing the requirements that were identified with the Portuguese Air Force, the overall software architecture of the system, the current stage of the prototype, and the outcomes of the first field tests with users
Towards Design Principles for Experimental Simulations in Virtual Reality â Learning from Driving Simulators
Experiments play an important role in Information Systems research. In this area, Virtual Reality (VR) technologies can serve as a tool for enabling and conducting research. e.g., to investigate human behavior in specific situations. A prime example is VR-supported driving simulators that allow researchers in the automotive domain to gather knowledge while reducing cost and complexity compared to field studies with real cars. We argue that the use of carefully designed VR-supported experiments might allow researchers to get deeper insights into human behavior. Thus, we derive design principles for VR Experiments as an artifact from the literature about VR-supported driving simulations that have been accepted as a useful tool for research in their domain
Engaging Human-in-the-Loop for Autonomous Vehicle Simulation
Many autonomous vehicles are still in the development phase due to limited research and testing and will take a considerable amount of time to further develop before they are ready for public release. The main objective of this study is to introduce a human-in-the-loop simulation framework for supporting autonomous vehicle research. Our proposed simulation framework aims to facilitate AV assessment by providing a safer and more efficient way. Functionally, it is focused on the understanding of AVsâ operations in the presence of pedestrian users. The developed simulation framework allows a human pedestrian avatar to be integrated into the high-fidelity 3D virtual environment and interact with simulated autonomous vehicles via standard keyboard input methods or virtual reality (VR) methods. This enables safer pedestrian-AV integration research and testing, and the ability to implement a series of risky edge-case scenarios in less time and cost than would be feasible in a real-world setting
Towards Next Generation of Pedestrian and Connected Vehicle In-the-loop Research: A Digital Twin Simulation Framework
Digital Twin is an emerging technology that replicates real-world entities
into a digital space. It has attracted increasing attention in the
transportation field and many researchers are exploring its future applications
in the development of Intelligent Transportation System (ITS) technologies.
Connected vehicles (CVs) and pedestrians are among the major traffic
participants in ITS. However, the usage of Digital Twin in research involving
both CV and pedestrian remains largely unexplored. In this study, a Digital
Twin framework for CV and pedestrian in-the-loop simulation is proposed. The
proposed framework consists of the physical world, the digital world, and data
transmission in between. The features for the entities (CV and pedestrian) that
need digital twined are divided into external state and internal state, and the
attributes in each state are described. We also demonstrate a sample
architecture under the proposed Digital Twin framework, which is based on
Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). The
proposed framework is expected to provide guidance to the future Digital Twin
research, and the architecture we build can serve as the testbed for further
research and development of ITS applications on CV and pedestrian
A Large-Scale SUMO-Based Emulation Platform
A hardware-in-the-loop simulation platform for emulating large-scale intelligent transportation systems is presented. The platform embeds a real vehicle into SUMO, a microscopic road traffic simulation package. Emulations, consisting of the real vehicle, and potentially thousands of simulated vehicles, are run in real time. The platform provides an opportunity for real drivers to gain a feel of being in a large-scale, connected vehicle scenario. Various applications of the platform are presented
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