AR-PED: Augmented Reality Enabled Pedestrian-in-the-Loop Simulation

Pedestrian simulators are in high demand for many research and industry applications, such as evaluating pedestrian safety and testing of autonomous vehicles. A recent trend on the development of pedestrian simulators is to use virtual reality (VR) head-mounted display (HMD) devices, since they offer a highly immersive and realistic view of the virtual environment (VE). However, existing pedestrian simulators that make use of this technology have a set of limitations that make them unsuitable for the simulation of a large virtual scenario. Specifically, the boundaries of the virtual scene set by these simulators encompass a relatively small area (e.g., a single crosswalk). Regarding these issues, this paper aims to develop an augmented reality (AR) enabled pedestrian-in-the-loop simulation (AR-PED) framework that enables the simulation of pedestrians in a large virtual scenario (e.g., a city) with an actual scale. The proposed AR-PED simulation framework is empowered by the latest advances in cloud computing and AR to allow multiple users to access the simulation at the same time. A client-server architecture allows users to act as pedestrians, drive a car or simply visualize the scene simultaneously. Additionally, other vehicles can be artificially generated by a microscopic traffic simulation (MTS) package that acts as the server. A prototype of the proposed framework is implemented and demonstrated by simulating a model of a city. The promising capabilities of the AR-PED framework are attested with the deployable experiments and potential improvements over the present study to further excel the current framework are also discussed.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AND30 Standing Committee on Simulation and Measurement of Vehicle and Operator Performance.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Perez, Daniel
    • Hasan, Mahmud
    • Shen, Yuzhong
    • Yang, Hong
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Photos; References;
  • Pagination: 5p

Subject/Index Terms

Filing Info

  • Accession Number: 01697898
  • Record Type: Publication
  • Report/Paper Numbers: 19-06083
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:41AM