Modeling and Simulation of Vehicle to Vehicle and Infrastructure Communication in Realistic Large Scale Urban Area

Abstract

During the last decades, Intelligent Transportation System (ITS) has progressed at a rapid rate, which aim to improve transportation activities in terms of safety and efficiency. Car to Car or Vehicle-to-Vehicle (V2V) communications and Car/Vehicle-to-Infrastructure (I2V or V2I) communications are important components of the ITS architecture. Communication between cars is often referred to Vehicular Ad-Hoc Networks (VANET) and it has many advantages such as: reducing cars accidents, minimizing the traffic jam, reducing fuel consumption and emissions and etc. VANET architectures have been standardized in the IEEE-802.11p specification. For a closer look on V2V and V2I studies, the necessity of simulations is obvious. Network simulators can simulate the ad-hoc network but they cannot simulate the huge traffic of cities. In order to solve this problem, this thesis studies the Veins framework which is used to run a traffic (SUMO) and a network (OMNET++) simulator in parallel and simulates the realistic traffics of the city of Cologne, Germany, as an ad-hoc network. Several different simulations and performance analyses have been done to investigate the ability of different VANET applications. In the simulations, cars move in the real map of the city of Cologne and communicate with each other and also with RoadSideUnits with using IEEE 802.11p standard. Then, Probability of Beacons Delivery (PBD) in different area of a real city are calculated and also are compared with the analytical model. This study is the first research performed on calculating PBD of IEEE 802.11p in realistic large urban area. Then, the thesis focuses on modelling and analysis of the applications of the V2I in real city. In these sections, two different simulations of application of the VANET are done by developing the Veins framework and also by developing two new programs written in Python which are connected to SUMO and control the real traffic simulation. One program simulates a real city with intelligent traffic lights for decreasing response time of emergency vehicles by using V2I. The results show that using V2I communication based on 802.11p between emergency cars and traffic lights can decrease the response time of emergency cars up to 70%. Another program, simulates dynamic route planning in real traffic simulation which is used V2I and V2V communication. The result of this simulation show the capability of V2V and V2I to decrease the traveling time, fuel consumptions and emissions of the cars in the city