Comparing Driver and Capacity Characteristics at Intersections With and Without Red Light Cameras

Abstract

The primary purpose of installing Red Light Cameras (RLCs) is to improve intersection safety by discouraging motorists to cross the intersection when the signal for approaching vehicles turns red. Due to the fear of being fined when crossing an RLC equipped intersection at the onset of the red signal, many approaching vehicles may have a tendency of stopping during the yellow phase. This tendency may impact intersection capacity, which can be significant in congested transportation networks during rush hours, especially when several intersections are equipped with RLCs along a sequence of traffic signals, resulting in a disruption of traffic progression. In order to examine the driver and capacity characteristics at intersections with RLCs and compare them with those without RLCs we develop a binary probit choice model to understand driver's stop and go behavior at the onset of yellow intervals, also known as dilemma zone. Further, in order to capture the impact to intersection capacity at intersections with RLCs we develop a probabilistic computational procedure using data from ten intersection pairs (with and without RLCs) in the Baltimore area. The results indicate that, in general, RLCs reduce the intersection capacity since driver's travel behavior is influenced by the presence of the cameras. Other contributory factors for the so-called capacity reduction, such as driver population (e.g., familiar vs. unfamiliar drivers) and traffic-mix (e.g., trucks vs. passenger cars) characteristics have been left for future works.