Biologically inspired modeling of vehicle to vehicle communication for intelligent transportation systems applications

In this study we developed a macroscopic model for simulating the vehicle to vehicle communication process. Real-time information propagation via vehicle-to-vehicle communication is part of the Vehicle Infrastructure Integration (VII) initiative, aimed atimproving the traffic conditions on existing roadways. In VII, Vehicles communicate among themselves using wireless technology. Each vehicle broadcasts any available information regarding the roadway (which might include time taken to travel a small stretch, any hazardous conditions, incidents etc) and other vehicles upstream, which might not be aware of the conditions ahead, receive the information. In this thesis, afraction of the vehicles traveling on the network are assumed to be equipped with the wireless technology and have the ability to communicate. These are called the “instrumented” vehicles. The proposed model is based on the Susceptible – Infected –Removed (SIR) model that is used to model the spread of epidemics in a region. We call the vehicles that have received a signal from another vehicle as ‘infected vehicles’, andthose instrumented vehicles that have not received a wireless message are called ‘susceptible vehicles’. The present model predicts the number of infected vehicles present on the roadway at every instant of time. The model is developed for a variety of traffic conditions including different volumes, speed limits and number of lanes. Finally, it is validated using simulation results obtained from Paramics, a microscopic traffic simulation software. Various observations related to the process of vehicle to vehicle communication were also made.