In-Car Advice to Reduce Negative Effects of Phantom Traffic Jams

Abstract

Congestion problems result in economic losses and also have serious implications for traffic safety. In the Netherlands, more than 20% of all congestion is recognized as shockwave jams, or so-called phantom traffic jams, and in other countries this type of jam has been recognized as a significant part of congestion. A phantom jam occurs without the existence of a physical bottleneck and is caused by the imperfect driving style of road users under metastable traffic conditions. To prevent phantom jams, the focus is on the cause of the perturbations or on the metastability of the traffic flow. Previous studies have shown that dynamic speed limits displayed by roadside equipment are successful in stabilizing traffic flow and resolving phantom jams. Several algorithms were developed to prevent or resolve phantom jams by giving in-car speed advice. For this purpose the data, typically detected by dual-loop detectors, were processed by fuzzy logic rules and clustering techniques to determine the spatiotemporal traffic conditions. The performance was tested in a microsimulation study using various compliance rates and speed advice on a two-lane facility. As expected, the occurrence of phantom jams showed a high correlation with high-intensity waves, platoons of traffic under metastable traffic conditions. The results of the algorithms showed that prevention-based algorithms could be successful in reducing phantom jam occurrence. Resolution-based algorithms were unsuccessful, with no significant improvements or deterioration.