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Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation
| Title: | Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation. |
 72 views 48 downloads |
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| Name(s): |
Jamialahmadi, Ahmad, Author Pourmohammadi Fallah, Yaser, Committee Chair Rahnavard, Nazanin, Committee Member Chatterjee, Mainak, Committee Member University of Central Florida, Degree Grantor |
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| Type of Resource: | text | |
| Date Issued: | 2018 | |
| Publisher: | University of Central Florida | |
| Language(s): | English | |
| Abstract/Description: | A critical aspect of connected vehicle safety analysis is understanding the impact of human behavior on the overall performance of the safety system. Given the variation in human driving behavior and the expectancy for high levels of performance, it is crucial for these systems to be flexible to various driving characteristics. However, design, testing, and evaluation of these active safety systems remain a challenging task, exacerbated by the lack of behavioral data and practical test platforms. Additionally, the need for the operation of these systems in critical and dangerous situations makes the burden of their evaluation very costly and time-consuming. As an alternative option, researchers attempt to use simulation platforms to study and evaluate their algorithms. In this work, we introduce a high fidelity simulation platform, designed for a hybrid transportation system involving both human-driven and automated vehicles. We decompose the human driving task and offer a modular approach in simulating a large-scale traffic scenario, making it feasible for extensive studying of automated and active safety systems. Furthermore, we propose a human-interpretable driver model represented as a closed-loop feedback controller. For this model, we analyze a large driving dataset to extract expressive parameters that would best describe different driving characteristics. Finally, we recreate a similarly dense traffic scenario within our simulator and conduct a thorough analysis of different human-specific and system-specific factors and study their effect on the performance and safety of the traffic network. | |
| Identifier: | CFE0007573 (IID), ucf:52578 (fedora) | |
| Note(s): |
2018-08-01 M.S. Engineering and Computer Science, Computer Science Masters This record was generated from author submitted information. |
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| Subject(s): | Intelligent Transportation Systems -- Connected and Automated Vehicles -- Traffic Simulation -- Vehicular Safety Simulation -- Driver Behavior -- Driver Reaction | |
| Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0007573 | |
| Restrictions on Access: | campus 2020-02-15 | |
| Host Institution: | UCF |
