Evaluating Traffic Flow Parameters on Signalized Links with the Introduction of Autonomous Vehicles

Abstract: Introduction of autonomous vehicles have started to receive much interest among researchers because they suggest a set of unique solutions to many of current problems in the transport network. Inclusion of autonomous vehicles in the traffic stream will affect distances, travel time and congestion. Research on evaluation of the impacts of autonomous vehicles on highway capacity and how the traffic flow parameters will change is rare. This research designs an analytical framework for the evaluation of impacts of autonomous vehicles on the capacity of signalized links and assess the variation in traffic flow parameters. The significance of this research is to evaluate the impacts of autonomous vehicles in a transport network on a mesoscopic level, which is able to investigate a system of small traffic engineering and traffic management interventions in a precise way. To achieve this goal, the behavior of autonomous vehicles is assessed in heterogeneous traffic environment with different penetration rates in traffic stream. There is a need to develop a model which will evaluate the relationship between capacity of signalized links and traffic flow parameters. To achieve this goal, this research first calibrated the transport data of conventional cars by real-time observed and calculated data with Budapest transport model. Contiguous links were selected on a small section of road network of Budapest transport network, and capacity assessed with the amalgamation of autonomous vehicles in the network. The impact of autonomous vehicles on macroscopic fundamental diagrams investigated through traffic real-time algorithm (TRE) method with dynamic assignment in AIMSUN Next. The results indicate how maximum lane capacity varies with different shares of autonomous vehicles in the transport network and respectively how traffic flow parameters will change in dynamic environment. The results of this research provide knowledge regarding the potential capacity benefits of autonomous vehicles with different penetration rates of autonomous vehicles in the transport system during the dynamic environment.