Real-time Visualization & Virtual Reality & Augmented Reality
Explores the interactive virtual reality (VR) and Augmented Reality (AR) system, and real time rendering for architectural visualization, Human Computer Interaction, spatial behavioral and way-finding studies.
Edited By Frank Melendez, Nancy Diniz, Marcella Del Signore.
ISBN 9780367369095
Published September 30, 2020 by Routledge
308 Pages 224 Color Illustrations
https://i2.wp.com/ming3d.com/new/wp-content/uploads/2021/01/datamatter.jpg?fit=494%2C648648494Ming Tanghttp://ming3d.com/new/wp-content/uploads/2022/01/TY_logo-300x300-new.pngMing Tang2021-01-10 16:39:392022-09-28 01:01:29project featured in Data ,Matter, Design
Develop and Assess Active Shooter Virtual Reality Training for Ohio Law Enforcement. PI: J.C Barnes. Co-PI: Tang Office of Criminal Justice Services. $50,000. 09. 2020-09.2021 ( $29,608)
Development of a Virtual Reality Augmented Violence Reduction Training System for Active and Mass Shooting incidents. PI: Ed Latessa. Co-PIs: J.C. Barnes, Ming Tang, Cory Haberman, Dan Gerard, Tim Sabransky. $10,000. Start-up fund. UC Digital Futures anchor tenant cohort.
Shimmer GSR sensor is used to test Physiological stress.
Checklist
Using Checklists and Virtual Reality to Improve Police Investigations. Collaborative Research Advancement Grants. UC. $25,000. PI: Haberman. Co-PI: Tang, Barnes. Period: 07.2020-01.2022.
To create simulated human behavior, either during the active shooting, or the casual human dialogue, the team designed a A.I system to simulate the decision trees. Please watch the technique breakdown demo.
https://i1.wp.com/ming3d.com/new/wp-content/uploads/2020/08/police.jpg?fit=1560%2C182518251560Ming Tanghttp://ming3d.com/new/wp-content/uploads/2022/01/TY_logo-300x300-new.pngMing Tang2020-08-03 22:13:332023-02-07 13:18:55VR for Police Training
Grant: Assess the effectiveness of Type 2 and Type 3 safety vests for day and night use-Phase. Ohio Department of Transportation. PI: John Ash. Co-PI: Ming Tang. Julian Wang. $337,366.31. ($191,458.16 in FY2020 and $145,908.15 in FY2021) Period: 02.2020-02.2022.
Ming Tang leads the modeling team constructed the virtual reality driving simulation, and conducted eye-tracking data collection to measure driver’s perception on the construction zone and various vest, signage and vehicles.
Work zones are an essential component of any state transportation agency’s construction and maintenance operations. As such, agencies apply numerous practices to keep their workers safe during construction operations. The Ohio Department of Transportation (ODOT) recently invested in several more advanced items to improve worker safety (and traveler safety, by hopefully reducing the number of crashes overall). Specifically, ODOT invested in Type 2 and 3 safety vests, halo lights, and reflectors on the back of dump trucks. In 2020, a team of researchers from the University of Cincinnati (UC) worked with the Ohio Department of Transportation to assess the effectiveness of safety vests for day and night use.
The simulation-based evaluation used measurements to create realistic retroreflective vests, lights, and other safety equipment in virtual scenarios. These items were then placed in different virtual work zone environments, each of which had different work zone setup conditions, traffic control, vests worn by workers, time of day/ambient lighting, etc. Through an eye-tracking experiment measuring participants’ gaze on workers in different virtual work zone scenarios and a driving simulator experiment in which participants drove through virtual work zones and were asked follow-up questions on worker conspicuity, subjective and objective measures of worker visibility were obtained.
Use Virtual Reality and Eye-tracking to evaluate the safety of vest on the highway construction site.
Ming Tang led the team that constructed six large-scale Ohio highway digital twins for snowplow drivers. The road models, which are 70 miles long and span three Ohio counties, were based on real-site GIS and TOPO data.
“Evaluate Opportunities to Provide Training Simulation for ODOT Snow and Ice Drivers”. Phase 2. Ohio Department of Transportation. PI: John Ash. Co-PI: Ming Tang, Frank Zhou, Mehdi Norouzi, $952,938. Grant #: 1014440. ODOT 32391 / FHWA Period: 01.2019-03.2022.
“Evaluate Opportunities to Provide Training Simulation for ODOT Snow and Ice Drivers”. Phase-1. Ohio Department of Transportation. PI: Jiaqi Ma. Co-PI: Ming Tang, Julian Wang. $39,249. ODOT 32391 / FHWA. Period: 01.2018- 01.2019.
https://i1.wp.com/ming3d.com/new/wp-content/uploads/2019/12/ae65fc41-3d67-44f3-9ae4-32eba00d2f98.jpg?fit=1200%2C9419411200Ming Tanghttp://ming3d.com/new/wp-content/uploads/2022/01/TY_logo-300x300-new.pngMing Tang2019-12-17 23:45:362024-04-11 14:59:26Digital Twin of Ohio Highway. Training Simulation for snowplow
Conventionally, architects have relied on qualities of elements such as materiality, light, solids and voids, etc. to break out of the static nature of space, and enhance the way users experience and perceive architecture. Even though some of these elements and methods helped create more dynamic spaces, architecture is still bound by conventional constraints of the discipline. With the introduction of technologies such as augmented reality(AR), it is becoming easier to blend digital, and physical realities, and create new types of spatial qualities and experiences, especially when it is combined with virtual reality(VR) early in the design process. Even though these emerging technologies cannot replace the primary and conventional qualitative elements in architecture, they can be used to supplement and enhance the experience and qualities architecture provides.
To explore how AR can enhance the way architecture is experienced and perceived, and how VR can be used to enhance the effects of these AR additions, the authors proposed a hybrid museum which integrated AR with conventional analog methods(e.g., materiality, light, etc.) to mediate spatial experiences. To evaluate the proposed space, the authors also created a VR walkthrough and collected quantifiable data on the spatial effects of these AR additions.