Quantifying the phantom jam externality: the case of an Autobahn section in Germany

Kathrin Goldmann,Gernot Sieg

doi:10.1186/s12544-020-00468-w

Abstract

If not restricted by tolls, private decisions to drive on a highway result in inefficiently high usage which leads to traffic jams. When traffic demand is high, traffic jams can occur simply because of the interaction of vehicle drivers on the road, a phenomenon called phantom jam. The probability of phantom jams occurring increases with traffic flow. Unpriced externalities lead to inefficiently high road usage. We offer a method for quantifying traffic jam externalities and identifying and isolating the phantom jam externality. We examine the method by applying it to a specific highway section in Germany. The maximal congestion externality for the analyzed highway section is about 38 cents per vehicle and kilometer. Congestion charges that are calculated ignoring phantom jam externalities, can only internalize two-thirds of the true externality.

Highlights

Traffic congestion during the rush hour remains an observable phenomenon worldwide
The results enable, for example, the evaluation of toll adjustments regarding their impact on changes in demand, length of peak periods or toll revenue. [25] show that macroscopic hypercongestion can occur as a purely emergent effect of dynamic equilibrium behaviour on a
Travel times increase significantly due to congestion, and the resulting additional time and environmental costs place a large burden on economies

Summary

Introduction

Traffic congestion during the rush hour remains an observable phenomenon worldwide. It results in significant travel time losses for commuters, additional external environmental costs and a loss of attractiveness of the affected areas. Reasons for congestion on highways can be on the demand side, (on-ramps with high inflows or fluctuations in demand) and on the supply side (traffic accidents, construction sites, tunnels, inhomogeneous road design or insufficient capacity). Besides these reasons, [1,2,3] show that traffic jams can occur randomly due to driving behavior.

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Discussion

Conclusion