We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. It is shown through the analysis of probability density functions characterising the CRI distribution that the reduction is not homogeneous across all indicator values, but depends on the penetration rate and the severity of the manoeuvre.Microscopic modeling of multi-lane highway traffic flow As a result, on average a 35% reduction of the cut-in risk manoeuvres in connected autonomous vehicles compared to non-connected autonomous vehicles is obtained. For this purpose, scenarios with penetration rates of autonomous vehicles from 20% to 100%, with step of 10%, both connected and non-connected autonomous vehicles were evaluated. In this work, the CRI was first used to assess the risk during the merging manoeuvre. The strategy then makes decisions on the target speeds/accelerations of both vehicles, possible lane changing, and a dynamic decision-making approach in order to reduce the risk during the cut-in manoeuvre. The new cooperation strategy considers a pair of vehicles approaching an on-ramp. In this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy.
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