_15_ diversion in favor of public transportation may result in an underestimate of demand. The behavior of bus services may also have a strong influence since they are quite an important feeder service. Increases in waiting time for bus services could hurt the demand for the commuter rail. All these assumptions can be quantified through relatively simple simulations and allow the regulator to better assess the risk and ... compensations if needed.

# _5.2_ **_Willingness for urban toll roads in France_**

Toll roads have been extensively developed in France, since the 60's. Their total length amounts to roughly 7000 km. But these toll roads are mainly intercity motorways for which traffic forecasting is a rather easy task as network effects are rather small in intercity roads; generally speaking there is just one competitive road and the main problem is to assess the split of the total traffic between the toll motorway and the competitive road. Furthermore, a long experience exists and traffic models for these situations are well calibrated and provide good fits with the reality. This is not the case for urban toll roads, which begin to appear in the largest agglomerations. There are few lessons from the past, and network effects are so large that it is not at all straightforward to estimate the sensitivity to competition or complementarity between routes. This is why the effects of the level of tolls on the traffic of the motorways have to be much more carefully studied than for other types of roads. Currently this is done in France by relying on rather large econometric models. One representative exemple is now in operation in Ile-de-France, the region which surrounds Paris and is almost full urbanized with about 11 Millions inhabitants.

The models used to forecast traffic on new infrastructures in this area are classically built on a four steps basis. Demand data are drawn from household surveys (16 000 households) updated every 5 years, and provide trip matrixes for several purposes of travel: job, non job, and for duty vehicles. The network supply is defined by nodes and arcs linking these nodes. Arcs represents the links between each modes; they are defined by technical characteristics such as their length, the cost and speed, safety, comfort ... While this is all quite reasonable and standard, the details of the modeling are not always relying on the frontiers of the applier theory. For instance, modal choice is taken into account through a very crude model. Also, for traffic generation and distribution, the O.D matrix is drawn from current data, and induced traffic is determined as a fraction of cost decrease of each O.D relation.

The traffic model is run first to reproduce the current situation, and its parameters are calibrated so as to minimize the sum of the square differences between present and reckoned traffic on each link. Then the model is run with the new planned infrastructure, and it is run several times, for different values of toll.

More precisely, traffic modelling is developped following the following steps<sup>21</sup> _Step 0, Before the study : Setting up the traffic modelling framework_ (the "Modele global de la Region Ile de France"). This step is done by the regional branch of the Department of Transport, which usually runs the model ; the underlying work includes gathering data on supply (network description and encoding), demand (socio-economic characteristics of the zones into which the total area of the study is divided) and traffic countings. The result is a 21 Drawn from "Etudes de trafic et de sensibilite au peage en Ile de France", internal document, Ministere de l'Equipement, France (1999)