Distributed Microscopic Traffic Simulation with Human-in-the-Loop Enabled by Virtual Reality Technologies. (April 2021)
- Record Type:
- Journal Article
- Title:
- Distributed Microscopic Traffic Simulation with Human-in-the-Loop Enabled by Virtual Reality Technologies. (April 2021)
- Main Title:
- Distributed Microscopic Traffic Simulation with Human-in-the-Loop Enabled by Virtual Reality Technologies
- Authors:
- Hasan, Mahmud
Perez, Daniel
Shen, Yuzhong
Yang, Hong - Abstract:
- Abstract: Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual world with various traffic entities (e.g., vehicles and pedestrians). Typically, the movements of these entities in the simulation are governed by some pre-defined algorithms (e.g., car-following models and lane-changing models). Modelers may develop customized algorithms through an application programming interface (API). In comparison to the human-controlled vehicles, however, any algorithm will fall short. Other than the configuration of some simplified behavioral parameters (e.g., reaction time), most of the existing MTS models have limited human-in-the-loop simulation abilities to capture the interactions among simulated entities. Besides, most existing MTS models do not provide a realistic virtual environment that enables high-fidelity simulations of the driver behavior in response to various driving conditions, such as road and weather conditions. This paper aims to develop a framework for improving MTS models and extending their capabilities by incorporating distributed vehicles controlled by human-in-the-loop with virtual reality (VR) technologies. This framework supports not only multiple/many users from geographically distributed locations but also interactive visualizations with VR devices from the perspective of a driver and other users (e.g., pedestrians). Data collected from the user-controlled vehicles can be used to calibrate different algorithms likeAbstract: Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual world with various traffic entities (e.g., vehicles and pedestrians). Typically, the movements of these entities in the simulation are governed by some pre-defined algorithms (e.g., car-following models and lane-changing models). Modelers may develop customized algorithms through an application programming interface (API). In comparison to the human-controlled vehicles, however, any algorithm will fall short. Other than the configuration of some simplified behavioral parameters (e.g., reaction time), most of the existing MTS models have limited human-in-the-loop simulation abilities to capture the interactions among simulated entities. Besides, most existing MTS models do not provide a realistic virtual environment that enables high-fidelity simulations of the driver behavior in response to various driving conditions, such as road and weather conditions. This paper aims to develop a framework for improving MTS models and extending their capabilities by incorporating distributed vehicles controlled by human-in-the-loop with virtual reality (VR) technologies. This framework supports not only multiple/many users from geographically distributed locations but also interactive visualizations with VR devices from the perspective of a driver and other users (e.g., pedestrians). Data collected from the user-controlled vehicles can be used to calibrate different algorithms like car following, lane changing, etc., or to explore the virtual world from different perspectives for design investigation by potential stakeholders. This paper describes the overall framework, the significant challenges in the proposed approach, and our solutions to these challenges. Highlights: A framework that incorporates distributed vehicles controlled by humans into a microscopic traffic simulation is proposed. The vehicles are controlled by human-in-the-loop with virtual reality technologies. The framework supports multiple users from geographically distributed locations, as well as interactive visualizations with VR devices from different perspectives. The effectiveness of the framework is evaluated through a series of experiments with five different participants. … (more)
- Is Part Of:
- Advances in engineering software. Volume 154(2021)
- Journal:
- Advances in engineering software
- Issue:
- Volume 154(2021)
- Issue Display:
- Volume 154, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 154
- Issue:
- 2021
- Issue Sort Value:
- 2021-0154-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Traffic simulation -- Virtual reality -- Driving simulation -- Human-in-the-loop
Computer-aided engineering -- Periodicals
Engineering -- Computer programs -- Periodicals
Engineering -- Software -- Periodicals
Periodicals
620.0028553 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09659978 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.advengsoft.2021.102985 ↗
- Languages:
- English
- ISSNs:
- 0965-9978
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0705.450000
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British Library HMNTS - ELD Digital store - Ingest File:
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