In-car advisory system for lane-changing in a connected vehicle environment

Abstract

This thesis investigates the potential of in-car advisory systems to suggest location and timing where and when lane-changes should be executed, by evaluating traffic flow conditions with data that is available using vehicle-to-vehicle communication. After investigating existing literature regarding car-following and lane-changing models, as well as driving support assistance systems and vehicle communication applications and practice, a new lane-changing model is introduced, with the objective to serve as a basis for the development of the in-car advisory system. In particular, the model accounts for information about position and speed of vehicles that are downstream from the considered vehicle current position, namely, out of the sight of a driver. Based on the proposed model, a decision system to deliver lane-changing advices to the driver is implemented, with the goal of avoiding or reducing traffic congestion. A set of simulations using the microscopic traffic simulator AIMSUN are performed to test the effectiveness of the proposed system.