VC-VANET: A Sustainable Vehicle-Crowd Based Vehicular Ad Hoc Network Supporting Mobile Cloudlet Computing (National Science Foundation Award No. 1719062)*

 

Synopsis

 

 

 

 

 

Not long from now, we will see more autonomous vehicles and connected vehicles on the road systems in each state.  It is predicted that by 2020 there will be approximately 250 million connected vehicles on the road. Such a vehicular environment, with communication capabilities from the moving vehicles and the transportation systems, presents an extremely large and complex mobile networking scenario where multiple communication technologies are available.  The goal of this research is to investigate a vehicle-crowd centered, networked system that has the capability to support high-demand mobile edge computing applications. This project envisions the capability to support these applications through harvesting the computing and storage resources by collaborations among grouped vehicles which are knitted together via the vehicular networking protocols. Such a network architecture is hierarchical as these groups of connected vehicles are an additional layer on top of vehicle ad hoc networks and vehicle delay tolerant networks of individual vehicles.  The benefits could range from more prompt and accurate data inputs and result outputs, to being an alternative for infrastructure-based systems. The unique emphasis of this research will be finding the interdependent relationships between the physical vehicle-crowd system and the traffic signal control among other factors and developing adaptive vehicle-crowd schemes in reacting to adverse conditions using data collected from local city transportation systems. 

 

Personnel / Collaborators

 Computer Science: Dr. Xiaoyan Hong and Dr. Travis Atkison; Civil Engineering: Dr. Alexander Hainen

 

Publications

 

 

 

 

 

Lee, Michael and Atkison, Travis. (2021). VANET applications: Past, Present, and Future. Vehicular communications. 28 (2021)  (April). 

Subedi, Pawan and Yang, Beichen and Hong, Xiaoyan. (2021). A Fog-based IOV for Distributed Learning in Autonomous Vehicles.  EAI MONAMI 2021 – 11th EAI International Conference on Mobile Networks and Management, Chiba, Japan (online), October 27-29, 2021.

Yang, Beichen; Sun, Min; Hong, Xiaoyan; Guo, Xiaoming, "A Deadline-Aware Offloading Scheme for Vehicular Fog Computing at Signalized Intersection", PerVehicle 2020, Mar 27, 2020, Austin, USA. 

Meng Kuai, Xiaoyan Hong, "Location-Based Deferred Broadcast for Ad-Hoc Named Data Networking".  Future Internet, 11 (6) 139, 2019.

Lee, Michael and Yang, Beichen and Atkison, Travis. (2019). 802.11ac and p in a Simulated VANET Environment. 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 23-27 December 2019, pp. 3797-3802.

 

William Alexander, Alexander Hainen, Xiaoyan Hong, “Vehicle Priority Scheduling Using Vehicle-to-Infrastructure Communications”. Transportation Research Board Annual Meeting, 2019, 2019-01-13.

Meng Kuai, Pawan Subedi, Xiaoyan Hong, Alexander Hainen, "Sustain Vehicle-Crowds via Traffic Signal Adjustments" in the proceedings of 2018 IEEE 88th Vehicular Technology Conference (VTC2018-Fall), 27–30 August 2018, Chicago, USA. [pdf]

 

Xiaoyan Hong, Yingyan Lou, Meng Kuai, Shuoping Wang, “Quantify Self-Organized Storage Capacity in Supporting Infrastructure-less Transportation Operation”, ACM MobiHoc 2015 workshops - The Second Workshop for Mobile Sensing, Computing and Communication (MSCC'15), June 22-25, 2015, Hangzhou, China. [pdf]

 Educational activities

PhD students:  Meng Kuai (graduated Aug 2018), Michael Lee (graduated May 2021), Beichen Yang, Xiaoming Guo, Shuai Dong.   

 

REU undergraduate students: Abigail Payne, Laura Malis, O'shea Woodruff, Lyle Stokes.

Presentations to classes: The project concepts were presented to multiple courses in Computer Science including CS300, CS438, CS606, CS618 in areas of operating systems, computer networking, wireless mobile network protocols, and distributed systems.

Dissemination/Outreach

 

 

Connected Vehicle Traffic Signal BSM SPaT CV2N,  https://youtu.be/u_CONSSkacY

 

The project concepts were disseminated to CS All-Graduate meeting in 2018; and to meetings with potential incoming high school students through out of the years; Detailed research results were also disseminated to professional venues and meetings with visitors from other universities and industry, also college-wide collaboration networking meetings, such as college Meet Your Neighbors Lunches, transportation seminar serious of Alabama Transportation Institute.

The project concepts are included in an article of "UA researchers turn Tuscaloosa into traffic laboratory to improve transportation" in UA Research magazine in June 2019,  here is the link.

Code Repositories

Preliminary research software: Rad-Ap (Radius Approximator), will post when ready...

 

 

* Any opinions, findings, and conclusions or recommendations expressed in this webpage are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.