Date: Wednesday January 22, 2020

 

Time:  10:00am - 12:00pm

 

Location: Essex Hall, 109

 

 

Vehicles travelling and communicating with each other and infrastructure is the basis of the future of vehicular transportation. There are many possible applications of communication in a vehicular network. One of the more important applications is for safety. Safety messages exchanged between vehicles can possibly be life-saving. However, if such messages are not received in a timely or reliable manner, a safety application’s effectiveness could suffer.  As such, network congestion control is a popular topic in vehicular networks. Various methods of controlling the message transmission rate and power have been explored to-date. In this thesis we propose an algorithm which manipulates the transmission power based on a density estimation derived from the vehicle’s driving speed, and compare it to methods observing only speed, only density, or other factors. Analysis of the results was done through simulation software. Results showed that the proposed algorithm reduced symptoms of channel congestion at least as effectively as the related density-based algorithm, and much better than using no congestion control algorithm at all. This thesis also adds “relevance” as a new measurement of performance by observing the proportion of packets received from certain distances at each vehicle.

 

 

Internal Reader: Dr. C. Ezeife     

 

External Reader: Dr. W. Anderson           

 

Advisor: Dr. A. Jaekel

 

Chair: Dr. Lu