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Amin Rezaei

PhD Researcher, Centre for Transport Research (CTR)
Dept. of Civil, Structural & Environmental Engineering


Application of Autonomous Vehicles in Highway Transport: Optimisation and Modelling

Keywords: Autonomous Vehicles; Simulation; Optimisation; Traffic flow; Driving behaviours; User Acceptance.


Microscopic Traffic Simulation (MTS) has been widely used during the past decades to analyse the possible outcomes of changes in the current and future traffic conditions. Also, the advent of new sensor technologies specifically Artificial Intelligence (AI) in transport science and car industry has made the MTS a basic principle of any traffic studies where future traffic assessments would seem impossible without it. One of such new technologies is a new generation of Autonomous Vehicles (AVs) in highway transport, which are claimed to be capable of driving in complex traffic condition without intervention of a human driver. Aside from the impacts they may have on the car industry, they may also play an important role in transportation network. It is foreseen that they may have direct impacts on safety, traffic flow, and fuel consumption, the environment, and privacy of the road users, which may impact upon users and non-users in ways that are not yet fully known. On the other hand, simulation software does not provide the local driving behaviours per se, and thus requires model calibration for the better representation of actual traffic condition. Hence, understanding of different driving behaviours and their possible relationships in traffic modelling significantly impacts upon the improvement of model results and their conformity to the actual traffic.

This research is aiming to evaluate road users’ awareness and acceptance of AVs in the first step. Then, the study seeks to find out the relationship between the parameters of Wiedemann Car-following Model (WCFM) and calibrate them for AVs through a proposed method of sensitivity analysis of driving behaviours and a case study modelling of motorway M50 in Dublin city, Ireland on the microsimulation software PTV-Vissim. Furthermore, the level of impacts of each CC-parameter on the results will be evaluated to see which CC-parameter will have more impacts upon traffic parameters such as travel time, queue length, delay, and the level of service, and environmental parameters such as fuel consumption and emissions. Finally, the model adopts the calibrated parameters of WCFM to simulate AVs on the Vissim model of M50 in order to assess how effective can AVs interact with conventional vehicles on their network and how efficient could they behave in a highway which is fully occupied by autonomous vehicles.


Project Supervisor: Assoc Prof. Brian Caulfield