Adaptive Traffic Control
Led by Aleksandar Stevanovic, Ph.D.
This REU project is focused on establishing communication between virtual vehicle and traffic signal controller in a Connected Vehicle framework.
The participant will learn how exchange of the data between controller and virtual vehicle works in a simulated lab environment. A significant part of the project will be directed towards exploratory research to assemble all of the necessary hardware and software components to establish this communication. The tasks will include hardware integration, development of necessary logics and protocols to establish necessary interfaces between various system’s components. This effort will require development of multiple data streams to mimic/replace missing true-world data which will be then interchanged between system’s components. Once the data from the wireless Direct Short Range Communications is transferred and recorded it will be used to develop various Connected vehicle applications such as Green Light Optimized Speed Advisory (GLOSA) systems, Collision Avoidance systems and similar. The participant will learn how to develop these additional CV applications by utilizing examples from the Software Developer Kit provided with the necessary hardware (On-Board Unit (OBU) and Road-Side Unit (RSU)). The REU participant will investigate use of other open-source applications, from other relevant research projects, and how such applications can be implemented, tested and modified to achieve specific objectives in urban Connected Vehicle applications. The results of this experimentation will be used to guide further design and evaluation of new features of vehicle-controller communications and exchange information in Connected Vehicle environment. The project will provide a meaningful experience for a participant eager to learn about the latest achievements in Connected Vehicle framework while contributing to Stevanovic’s current research efforts in this area.
This REU project is focused on enabling integration of a physical driving simulator with a mathematical simulation model representing urban network operations. A driving simulator will be assembled from a gaming-like platform and peripherals, computer and three flat-screen monitors.
The participant will work on development of a driving simulator virtual reality (either presented on the three monitors or on Oculus-Rift VR device) within an urban network environment which will mimic the network from the mathematical modeling simulation network (to be executed in PTV proprietary VISSIM software). The driving simulator reality will be developed by using an open-source gaming platform (e.g. Unreal Engine or similar) with the 3-D model which will comply with VISSIM’s 3-D model. The two platforms will interface in such a way that a driver operating the driving simulator will be one of the many vehicles in the urban network of the mathematical simulation model. Other vehicles in the mathematical (VISSIM) model will react to the driving simulator-vehicle as it is one of their own cars and will thus accelerate and decelerate accordingly to avoid any conflicts. Similarly, operator of the driving simulator will perceive vehicles on the screen as if they are real vehicles driving around his/her virtual vehicle. The participant will be the main software developer and integrator of the necessary software and hardware (PCs, monitors, etc.). The participant will extensively use available documentation on a similar project developed by the others. Important component of the project will be emulation of the Connected Vehicle environment where basic characteristics of the driving-simulator- vehicle will be transferred both to other simulated vehicles (through software applications) and to hardware road infrastructure (through wireless communication). The project will provide a meaningful experience for the participant, while contributing to Aleksandar Stevanovic’s current research in this area.