Development and Evaluation of Enhanced IntelliDrive-Enabled Lane Changing Advisory Algorithm to Address Freeway Merge Conflict

Abstract

Freeway merge conflicts contribute significantly to freeway congestion. With the capabilities that will be available in an IntelliDrive environment, which enables vehicle-to-vehicle and vehicle-to-infrastructure communications, new approaches to managing freeway merges are possible. In this paper, an enhanced IntelliDrive enabled lane changing advisory algorithm was developed with a variable gap size concept. This algorithm first calculates anticipated lead–lag gap sizes with the equations of motion prepared for a car and a truck and for three vehicle dynamics (accelerating, maintaining current speed, and decelerating). The algorithm then provides lane changing advisories to freeway main-line vehicles (selected on the basis of the calculated variable gap sizes) to create more space within the ramp merging area. Evaluation conducted with a VISSIM microscopic traffic simulation model of a freeway network in Virginia showed that the proposed algorithm has the potential to address freeway merge conflicts. The maximum operational improvement observed was 6.4% higher average speed in the freeway main line within a merge area. Up to a 5.2% reduction in emissions was achieved. Further analysis conducted in terms of the sensitivity of algorithm performance to driver compliance rates suggested that a very high compliance rate (90% or higher) was necessary for the proposed algorithm to work as intended.