Rising travel demand and the introduction of road pricing schemes are expected to cause increased peak spreading. Traditional travel demand models are generally not well equipped to predict these effects accurately. In this study, the authors show that shadow networks, requiring only a slight modification to existing models, are well suited to describing time-of-day- effects such as peak spreading. Essentially, the known concept of shadow networks entails the addition of one or more copies of the original network to the existing model. These copies represent the network and the associated traffic flows during different periods of the day. The authors illustrate the application of shadow networks by determining the effects of a toll scheme on the road network around the Belgian city of Antwerp. (A)
Abstract