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Thesis_MS_Vikhyat_Kalra.pdf (7.24 MB)

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Multi-modal Simulation and Calibration for OSU Campus Mobility

Kalra, Vikhyat
http://rave.ohiolink.edu/etdc/view?acc_num=osu1629712280705021

Abstract Details

2021, Master of Science, Ohio State University, Mechanical Engineering.
With ongoing research in intelligent transport systems and connected and automated vehicles, enabled by advancements in artificial intelligence, the large-scale advanced simulation has become an important part of product/software development for the automotive industry. Nowadays, traffic simulations are used to mimic real-world environment scenarios for connected vehicle technologies. The focus of this thesis lies in the development of microscopic traffic simulation calibration and enhance traffic signal control systems This thesis makes the following major contributions. First, a calibration framework is proposed which harnesses the exiting data set of OSU campus shuttles (CABS) to determine the traffic state and create a microscopic traffic simulation. The traffic simulation is implemented for a section of the OSU campus(“Woody Hayes Drive") which can be extended to the entire OSU campus. The second contribution is an investigation of an intelligent traffic signal control system. The signal control operation is formulated as a decision-making process where each controller or control component is modeled as an intelligent agent. The agents make decisions based on traffic conditions and their past knowledge of the environment. A state estimation method and an adaptive control scheme by reinforcement learning (RL) are introduced to implement such an intelligent system. Simulation experiments ii have been performed to verify the improvements of intelligent traffic control systems and compare them with the existing control policy. The third contribution summarises the initial integration work for the co-simulation framework completed by dSpace ASM and SUMO to create a complete real-time simulation of urban environments for ADAS testing. The demo scenario is the OSU campus with traffic demand generated using the calibrated model from the first part of the thesis.
Punit Tulpule, Dr. (Advisor)
Qadeer Ahmed, Dr. (Committee Member)
Shawn Midlam-Mohler, Dr. (Committee Member)
124 p.
Mechanical Engineering
Calibration; Traffic Simulation; Reinforcement Learning; Traffic Signal Control; Optimization; CAVS; HIL

Recommended Citations

Citations

  • Kalra, V. (2021). Multi-modal Simulation and Calibration for OSU Campus Mobility [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1629712280705021

    APA Style (7th edition)

  • Kalra, Vikhyat. Multi-modal Simulation and Calibration for OSU Campus Mobility. 2021. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1629712280705021.

    MLA Style (8th edition)

  • Kalra, Vikhyat. "Multi-modal Simulation and Calibration for OSU Campus Mobility." Master's thesis, Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1629712280705021

    Chicago Manual of Style (17th edition)

osu1629712280705021
308
© 2021, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.
Release 3.2.12