Bounded Acceleration and Capacity Drop at Merging Bottlenecks

The objective of this research is to prove the conjecture that bounded acceleration rates of vehicles can lead to capacity drop inside a merging area. Capacity drop is one of the most puzzling traffic phenomena occurring near such bottlenecks as lane-drop and merges. While it has been suspected that such a capacity drop is caused by drivers’ acceleration behaviors inside various bottleneck areas, there have been no systematic studies on the relationship between drivers’ acceleration process and the magnitude of capacity drop. In this research we aim to develop, calibrate, and validate a macroscopic model of acceleration behaviors inside a merging bottleneck and quantify their impacts on capacity drop. From observed vehicles’ trajectories, we will calibrate acceleration rates and distances inside such an acceleration zone and calculate the magnitude of capacity drop using the macroscopic acceleration behavior model. The result will be compared with the observed capacity drop from loop detector data. Such a research can improve our understanding of the mechanism and magnitude of capacity drops at freeway bottlenecks. The knowledge can then be employed towards improving ramp metering, variable speed limits, and other control strategies to reduce congestion and vehicle emissions in a road network.