An Empirical Data-Driven Macroscopic Lane Changing Model

This paper summarizes the development of a macroscopic lane-changing model for vehicle lane changes from a freeway through lane to an exit lane leading to another freeway. The relationships between the number of lane changes, the speed of the ramp lane (using video-tracked vehicle data), and the location upstream of the ramp split are examined. The number of lane changes is approximated by a non-homogeneous Poisson distribution, with parameters that are a function of ramp lane speed, and location. The relationship between the number of lane changes and target lane speed is parabolic, and the number of lane changes is gamma-distributed with respect to distance upstream of the ramp. The parameters of the gamma distribution are a function of ramp lane speed. Data were collected from a secondary site, and fit to the model to provide additional credence to the model’s potential transferability. A discussion regarding the role of how other access points may affect the shape of the model is opened, but not analyzed in detail yet due to lack of available data. The macroscopic lane changing model presented in this paper is best characterized as the development of generalized lane-changing relationships, and provides a starting point from which more complex corridor-level models can be developed.