Modeling Mode-Dependent Lane Discipline in Hybrid Traffic

Complex interactions can be observed in hybrid transportation systems, where cars share the same road space with other modes such as motorcycles, bicycles or even e-scooters. In this work we further built upon the concept of mode dependent lane discipline. Mode dependent lane discipline means that motorcycles do not necessarily follow the predefined lanes and may form emergent, virtual lanes in the available free spaces without any prior agreement in a self-organized manner. The other modes, such as cars, follow the lanes as given by the infrastructure. This is different than the traditional dualism between lane-based and lane-free traffic. Motivated from empirical findings, our modelling approach draws inspiration both from vehicular, as well as from pedestrian dynamics literature. At the same time, we recognize that motorcycles are neither pedestrians nor cars, as they have their own special features. Therefore, there is a need for dedicated methods that are not available off-the-shelf. Also, given that our detailed observations come from an urban context, even standard car-following models that have been mainly developed with freeways in mind, are not adequate for reproducing the observed phenomena and consequently we make a first step towards revisiting traffic flow dynamics in general. We utilize high accuracy trajectories from the congested city center of Athens that have been collected from a swarm of drones through the pNEUMA experiment.