First order multi-lane traffic flow model – an incentive based macroscopic model to represent lane change dynamics

Unbalanced lane usage on motorways might lead to the reduction in capacity
of the motorway. Lane-level traffic management present new opportunities
to balance the lane-flow distribution and help reduce congestion.
In order to come up with efficient traffic management strategies on a
lane-level, there is a need for accurate lane-specific traffic state estimation
models. This paper presents a first-order lane-level traffic flow model. The
proposed model differs from the existing models in the following areas: (i)
incentive-based motivation for lane changes and consideration of downstream
conditions (ii) transfer of lateral flows among cells. The model is
tested against real-world data. It is observed that the model is able to capture
the lane-level dynamics in terms of the lane flow distribution. The
model results are compared to a linear regression model and results show
that the developed model performs better than the regression model on
the test sections.