Quantifying the Number of Lane Changes in Traffic

Abstract

Lane changes are an important aspect of freeway flow. Most models of lane change are microscopic. Lane change behavior of individual vehicles or drivers is described, and, therefore, models are calibrated microscopically. Macroscopic validation often is restricted to the distribution of vehicles across lanes. To the best of the authors' knowledge, no systematic analysis has been made of the number of lane changes as a function of the operational characteristics of the origin and target lane. This paper fills the gap in lane change literature with an analysis of the number of lane changes as a function of several incentives. On the basis of data availability, two “simple” sites were selected, that is, as close as possible to a straight continuous freeway. Statistical analysis at the selected sites revealed that drivers changed lanes on average once per 2 km driven. Furthermore, an analysis of the number of lane changes (per kilometer per hour) as a function of the density in the origin lane and in the target lane showed that the number of lane changes increased with the density in the origin lane for a fixed density in the target lane. The number of lane changes also increased with the density in the target lane for a fixed density in the origin lane. The underlying mechanism was therefore different from gap-acceptance theory. The analyses presented in this paper can be used to verify qualitatively (microscopic and macroscopic) lane change models and to propose better ones.

Traffic flow optimisation in presence of vehicle automation and communication systems – Part I: A first-order multi-lane model for motorway traffic

“…Other approaches are based on the gas-kinetic traffic flow model, such as Helbing (1997), where the author derived macroscopic traffic flow equations for interacting lanes taking explicitly into account queuing effects; and Hoogendoorn and Bovy (1999), where traffic is described as a collection of vehicle platoons governed by continuum (smooth changes in the traffic flow variables) and non-continuum processes (deceleration of vehicles and lane changing). Some recent works are treating the problem of modelling the lane flow distribution at specific locations of the network; Knoop et al (2010) studied a relation between the total density and the lane densities during free-flow and congested regime; Knoop et al (2012) examined the number of lane changes as function of several incentives, finding that the most critical are the densities in the origin and in the target lanes; whereas Duret et al (2012) analysed real data (in free-flow conditions) for a three-lanes motorway, deriving a simple linear model considering the lane distribution of traffic flow.…”

Modeling Lane-Changing Behavior in Freeway Off-Ramp Areas from the Shanghai Naturalistic Driving Study

“…This case may happen more in higher density situations where vehicles are waiting for a gap and use this as soon as it becomes available. For some unobserved reason rather than the immediate traffic situations, a driver may decide on a particular lane-changing action [35], where there might be a trade-off between mandatory and discretionary. So if the fast lane for some reason is more attractive for the drivers, more vehicles change towards this fast lane.…”

Simulating Lane-changing Dynamics towards Lane-flow Equilibrium Based on Multi-lane First Order Traffic Flow Model

“…From the empirical aspects, however, Knoop et al (2012) Thus, in this study, it is assumed that: (i) Drivers are motivated to change the lane to increase the driving speed, though it depends on their desired speed; that is, a driver with high desired speed would change the lane and one with low desired speed would not try to that. (ii) Basically, drivers would follow the keep-left principle.…”

“…Thus, in the model, lane-changes are represented as the dynamics towards lane-flow equilibrium. The utility function for a vehicle to choose each lane is defined by only two parameters on the basis of the investigation about lane-changing behaviour done by Knoop et al (2012) and Shiomi et al (2013): one is a constant value implying cost breaking the keep-left (or right) principle, and the other one is the average speed depending on the fundamental diagram and the density of the lane. Such parsimony representation will be able to online calibration by using the real time data from conventional loop detectors.…”