Abstract:

This dissertation develops extensions to the kinematic wave theory of moving bottlenecks that allow the formulation of parsimonious traffic flow models that turn out to match field data with unprecedented accuracy. These "hybrid models" explicitly incorporate the effects of a stream of underperforming vehicles, whose trajectories are computed endogenously using realistic accelerations. Hybrid models exhibit important practical advantages stemming from their simplicity and mathematical stability. They do not amplify errors, they require few easily observable parameters and they can be validated by parts.

Two practical applications are included: the effects of heavy vehicles on uphill bottlenecks, and the effects of lane-changing maneuvers. In the first case, we found an important disagreement with the Highway Capacity Manual (HCM) formulas, possibly because the HCM formulas are based on microsimulation. Truck management schemes near bottlenecks caused by geometry can now be systematically devised; eg, truck-only lanes or truck metering. An approximate expression for the capacity of an upgrade is also developed, which matches simulation results accurately under all conditions.

The second application shows that the capacity losses imposed by the bounded accelerations of lane-changing vehicles is able to explain the relationship between the discharge rate of a moving bottleneck and its speed, as observed in the field. This is arguably the most important result of this dissertation, since it strongly suggests that lane-changing maneuvers may be the main cause for traffic instabilities on other bottleneck types (eg, merge, diverge, incidents).

The results of this dissertation allows for devising ITS solutions that maximize freeway capacity by controlling lane-changing and the arrival pattern of heavy vehicles to the bottleneck. The simulation of such strategies should be straightforward using hybrid models, and real-time applications should be possible for isolated bottlenecks.