skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: DReyeVR: Democratizing Virtual Reality Driving Simulation for Behavioural & Interaction Research
Simulators are an essential tool for behavioural and interaction research on driving, due to the safety, cost, and experimental control issues of on-road driving experiments. The most advanced simulators use expensive 360 degree projections systems to ensure visual fidelity, full field of view, and immersion. However, similar visual fidelity can be achieved affordably using a virtual reality (VR) based visual interface. We present DReyeVR, an open-source VR based driving simulator platform designed with behavioural and interaction research priorities in mind. DReyeVR (read ''driver'') is based on Unreal Engine and the CARLA autonomous vehicle simulator and has features such as eye tracking, a functional driving heads-up display (HUD) and vehicle audio, custom definable routes and traffic scenarios, experimental logging, replay capabilities, and compatibility with ROS. We describe the hardware required to deploy this simulator for under 5000 USD, much cheaper than commercially available simulators. Finally, we describe how DReyeVR may be leveraged to answer an interaction research question in an example scenario. DReyeVR is open-source at this url: https://github.com/HARPLab/DReyeVR  more » « less
Award ID(s):
1900821
PAR ID:
10395103
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
ACM/IEEE International Conference on Human-Robot Interaction
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, ACM)
    Driving simulators are vital for human-centered automotive research, offering safe, replicable environments for studying human interaction with transportation technology interfaces and behaviors. However, traditional driving simulators are not well-suited to studying traffic interactions with various degrees of freedom in a way that allows for the capture of nuances in implicit and explicit interactions, e.g. gestures, body language, and movement. We developed a multi-participant virtual reality (VR) driving simulation platform to study these interactions. This portable system supports cross-cultural experiments by modeling diverse scenarios, generating analyzable data, and capturing human behaviors in traffic. Our interactive demo allows participants to experience roles as drivers or pedestrians in a shared virtual environment, with the goal of providing a hands-on experience with this open-source VR simulator and demonstrating its affordability and scalability for traffic interaction studies to researchers and practitioners. 
    more » « less
  2. ; ; ; (, IEEE Systems Journal)
    The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this article presents an open-source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations. 
    more » « less
  3. ; ; ; (, IEEE systems journal)
    The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this paper presents an open- source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations. 
    more » « less
  4. ; ; ; (, 6th gem5 Users Workshop)
    Computer systems research heavily relies on simulation tools like gem5 to effectively prototype and validate new ideas. However, publicly available simulators struggle to accurately model systems as architectures evolve rapidly. This is a major issue because incorrect simulator models may lead researchers to draw misleading or even incorrect conclusions about their research prototypes from these simulators. Although this challenge pertains to many open source simulators, we focus on the widely used, open source gem5 simulator. In GAP we showed that gem5’s GPGPU models have significant correlation issues versus real hardware. GAP also improved the fidelity of gem5’s AMDGPU model, particularly for cache access latencies and bandwidths. However, one critical issue remains: our microbenchmarks reveal 88% error in memory bandwidth between gem5’s current model and corresponding real AMD GPUs. To narrow this gap, we examined recent patents and gem5’s memory system bottlenecks, then made several improvements including: utilizing a redesigned HBM memory controller, enhancing TLB request coalescing, adding support for multiple page sizes, adding a page walk cache, and improving network bandwidth modeling. Collectively, these optimizations significantly improve gem5’s GPU memory bandwidth by 3.8x: from 153 GB/s to 583 GB/s. Moreover, our address translation enhancements can be ported to other ISAs where similar support is also needed, improving gem5’s MMU support. 
    more » « less
  5. ; ; ; ; (, ASCE Computing in Civil Engineering Conference 2019)
    Fire simulator training is a very effective way to reduce firefighter injuries and improve their mission performance. However, the usability of existing fire simulators remains an issue as most of these simulators require users to set up hundreds or even thousands of parameters to initiate the simulation. In this paper, we present a participatory and evolutionary fire simulation method that balances the accuracy and fidelity of the fire simulation and the usability. The base parameters for accurate and usable fire simulation can be selected by a combination of the evolutionary algorithm and the knowledge of domain experts via the virtual reality (VR) fire simulator. These base parameters are expected to expedite the use of fire simulators and reduce the adoption threshold. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email