Smart City Gnosys
Smart city article details
| Title | A Research And Educational Robotic Testbed For Real-Time Control Of Emerging Mobility Systems: From Theory To Scaled Experiments |
|---|---|
| ID_Doc | 4069 |
| Authors | Chalaki B.; Beaver L.E.; Mahbub A.M.I.; Bang H.; Malikopoulos A.A. |
| Year | 2022 |
| Published | IEEE Control Systems, 42, 6 |
| DOI | http://dx.doi.org/10.1109/MCS.2022.3209056 |
| Abstract | Emerging mobility systems, for example, connected and automated vehicles (CAVs), shared mobility, and electric vehicles, provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better decisions for improving safety and transportation efficiency. However, before connectivity and automation are deployed en masse, a thorough evaluation of CAVs is required, ranging from numerical simulation to real- world public roads. The assessment of the performance of CAVs in scaled testbeds has recently gained momentum due to the flexibility they offer to conduct quick repeatable experiments that could go one step beyond simulation. This article introduces the Information and Decision Science Lab Scaled Smart City (IDS3C), a 1:25 research and educational scaled robotic testbed that is capable of replicating different real-world urban traffic scenarios. IDS3C was designed to investigate the effect of emerging mobility systems on safety and transportation efficiency. On the educational front, IDS3C can be used for 1) training and educating graduate students by exposing them to a balanced mix of theory and practice, 2) integrating research outcomes into existing courses, 3) involving undergraduate students in research, 4) creating interactive educational demos, and 5) reaching out to high-school students. IDS3C has become a research and educational catalyst for motivating interest in undergraduate and high-school students in science, technology, engineering, and mathematics. In our exposition, we also present a real-time control framework that can be used to coordinate CAVs in traffic scenarios such as crossing signal-free intersections, merging at roadways and roundabouts, cruising in congested traffic, passing through speed reduction zones, and lane-merging and passing maneuvers. Finally, we provide a tutorial for applying our framework in coordinating robotic CAVs in a multilane roundabout scenario and a transportation corridor in IDS3C. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. |
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