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In transportation modeling, after defining a road network and its origin-destination (OD) matrix, the next important question is how to assign traffic among OD-pairs. In our days, the technology of advanced traveler information systems (ATIS) makes it possible to realize the “user-optimal” solution. At the same time, with the advent of the Cooperative Intelligent Transport Systems (C-ITS) it is possible to solve the traffic assignment problem in “system-optimal” way. The difference in transportation performance between user-optimal and system-optimal principles is discussed in the paper. The main purpose of this research is to investigate what are the implications of the user and system optimal traffic assignment considering the autonomous vehicle fleets.

The paper presents a novel simulation concept for autonomous and highly automated road vehicles, called Scenario-in-the-Loop (SciL) testing. SciL can contribute to a more efficient development, testing and validation of driverless cars, which is a pressing question of our days. SciL based testing introduces a new approach capable to simulate and control realistic traffic scenarios around the autonomous vehicle under test realizing a Digital Twin technology for testing. For realistic traffic generation a high fidelity microscopic traffic simulator (SUMO) and for visualization the Unity 3D game engine are involved. The proposed testing methodology was proved with a real world autonomous car. As a test environment for SciL demonstration ZalaZONE Smart City Zone was used. Two different traffic scenarios (platooning and valet parking with pedestrian dummy) have been successfully tested and demonstrated.