The Effects Of ATIS On Transportation Systems: Theoretical Analysis And Numerical Applications
Free (open access)
G. N. Bifulco & F. Simonelli
In this paper some of the inconsistencies and limitations of other models in the simulation of the effects of ATIS (Advanced Traveller Information Systems) will be discussed, with particular regard to the impact of pre-trip information on the day-to-day dynamics of transportation systems. An innovative model will be proposed, where the compliance of travellers to ATIS will be considered to be elastic and explicitly modelled; it will be considered both variable within the whole dynamic process and dependent on the accuracy of the information. For the sake of simplicity, a fixed O/D demand will be considered and the effects of ATIS will be taken into account only on route choices. It will be shown that in most cases ATIS cannot be used to optimise the performances of the traffic network (system optimum); rather, travellers are compliant to information only if supplied according to user optimum. The main role of ATIS in recurrent traffic conditions will be shown to be the stabilisation of the transport systems. The first section will introduce the motivations of the proposed model and how they have been addressed in literature, moreover it will anticipate most of the innovative characteristic of the proposed model, as well as the expected accuracy of the results. In the second section the model will be formalised as a dynamic process, which includes explicit simulation of compliance. In the third section the result of some numerical experiments, related to different information strategies, will be presented; moreover, some theoretical analysis will be carried out by determining the stability domain for the dynamic process in presence of information. Keywords: dynamic traffic assignment (DTA), advanced traveller information systems (ATIS), day-to-day dynamics, user Optimum.
dynamic traffic assignment (DTA), advanced traveller information systems (ATIS), day-to-day dynamics, user Optimum.