The Logit lane assignment model: first results

TL;DR

This paper introduces the Logit lane assignment model for multi-lane traffic flow, exploring how traffic speed influences lane choice and evaluating various numerical schemes for discretizing the model.

Contribution

It presents the first application of the Logit lane assignment model to real data and compares different numerical discretization methods.

Findings

Traffic speed is a significant explanatory variable for lane choice.

Multiple numerical schemes are analyzed for their convergence properties.

The model's applicability is demonstrated on two data-sets.

Abstract

The Logit lane assignment model has been introduced recently in order to describe multi-lane traffic flow from a macroscopic point of view. The model is based on the idea that each available lane has a specific utility for each driver, who chooses the lane with the highest utility. The model is expressed by a system of conservation laws with a smooth but implicitly defined flux function. The first aim of the paper is to explore on two data-sets how traffic data supports the fact that traffic speed constitutes an explanatory variable of lane assignment. Second the paper addresses the problem of discretization of the model. Several numerical schemes are proposed: Lax-Friedrichs, Euler-lagrange remap, Lagrange, and their convergence properties are illustrated on the treatment of the Riemann problem. Directions for future research are outlined.