A stochastic behaviour model of a personal mobility under heterogeneous low-carbon traffic flow

The study proposes a mathematical framework to explain the stochastic behavioural patterns of personal mobility (PM) devices under low-carbon heterogeneous traffic conditions in shared lanes. We create set anticipation factors PM behaviour model tackle sensitivities both space headway and relative speed against intra- inter-modes. proposed involves deterministic force. In force, are used an optimal velocity full difference model. Langevin equation is capture PMs’ characteristics movements other PMs, pedestrians, bicycles, effect lateral interactions. carried out real-world circular experiments mixed sustainable modes verify performance models. Five models’ performances compared four different conditions, including bike-mixed, pedestrian-mixed, low-speed, high-speed conditions. confirmed that newly created play significant role all models partially influence following devices’ from leading two modes. validation results illustrate excellence method. Consequently, uncertainty well captured by although it requires more parameters than method paves way for CF model’s applicability describe dynamics using factors. Besides, lays foundation stone lane construct effective regulations safety standards.