Evaluation of Factors Influencing Ramp Metering Compliance Using Controller Event–Based Data

Abstract

Ramp metering enhances traffic mobility and safety by optimizing the flow of vehicles onto freeways. A complete realization of ramp metering benefits on freeway networks partially depends on the drivers’ compliance with the ramp meter signals. Noncompliance could lead to excessive volumes entering the mainline freeway, increasing congestion, delays, and merging location safety risks. Understanding the factors influencing compliance can help design ramp metering locations and develop metering algorithms that enhance driver adherence to ensure effective operations of the ramp metering system. This study used data collected from the freeway system in Phoenix, Arizona to identify factors influencing ramp metering compliance. The measures of compliance: compliance rates and violation counts were estimated using the controller event–based (CEB) data. Linear regression models were used to examine the impacts of factors, including the number of lanes on a ramp, ramp volumes, and metering rates. A spatial transferability analysis was performed to assess the applicability of the model when used to uncover route-specific factors influencing drivers’ compliance to ramp metering signals. Results revealed that mainline volume, upstream average annual daily traffic (AADT), percentage of time a ramp experienced queueing, ramp volume, ratio of ramp volume to metering rate, number of lanes, ramp length, route, peak hours, ramp speed, mainline speed, and metering rate significantly contributed to drivers’ compliance with ramp metering signals. These results could be used by transportation departments to optimize the existing ramp metering strategies and plan for future deployments of ramp metering signals.