• WP 3.1 Joint database of route choice and flows
This WP develops a database comprising observed path choices (from GPS data) as well as level of service (LoS) data concerning the network. This step involves substantial data processing. The main challenge is to make LoS data dynamic, reflecting flow variation over time.
• WP 3.2 Optimal paths in space-time networks
The basis for most route choice models is the repeated use of a shortest path algorithm. In a static network, the optimal route from an origin to a given node in the network is independent of the path further on. This is not the case in dynamic networks, where conditions change over time. This substantially complicates the choice problem and the solution algorithm. This WP will develop heuristics that can solve the path search problem in dynamic route choice models that include complex utility functions including time and road user charging.
• WP 3.3 Estimation of travellers route choices in congested networks
By using GPS-data where car users are followed over several weeks, it is possible to estimate individual preferences and variation of these.
• WP 3.4 Dynamic route choice model
The work package will develop a dynamic route choice model that considers how queues evolve and disappear over the rush hours. The model includes the optimal path algorithm (WP3.2), estimated choice functions (WP3.3) – allowing for individual heterogeneity - as well as the new empirical evidence on supply from WP 2. The equilibrium concept is stochastic user equilibrium. This WP takes previous WPs as input and is therefore affected by risk affecting these. If necessary, it is possible to scale down the level of ambition of this WP and achieving the objective of the WP remains feasible. The work package is expected to run in parallel with a project funded by the Danish Road Directorate, where the IRUC project develops the methodological basis and the RD project funds the software programming and empirical testing (and subsequent implementation and use in the national transport model).
• WP3.5 Development of stylised congestion models
The existing models of congestion are conceptually fairly simple, which contrasts with the complexity of reality. There is a range of phenomena that could be very important for determining the policy response to congestion which have not yet been incorporated in models. This WP uses either bottleneck or flow congestion technologies to develop dynamic models of congestion to account for a range of phenomena. 1. Behavioural response to random capacity variation and incidents. While it has been recognised that a large part of congestion delays is actually due to random delays with incidents of various kinds being a main driver, there has so far been limited progress on this issue. 2. So far, Nash equilibrium is almost uniformly assumed. However, this requires that all individuals are capable of choosing the optimum strategy. This is a very stringent assumption, even taking into account that it does not require that individuals undertake complex information processing in any conscious sense. Recent developments in game theory relax the information processing requirements on individuals and rely instead on learning mechanisms, for example using minimum regret. This WP extends these theories to the case of congestion with a large number (continuum) of players as is assumed in dynamic models of congestion. 3. Development of robust RUC schemes. This corresponds to the previous point in that it seeks to relax the informational requirements. The point here is to devise ways of designing RUC schemes that do not require planners to know the preferences of travellers but only assumes information that can readily be collected. The resulting RUC schemes will hence be less than perfect but they will have the advantage of being more robust in the sense that the schemes will be welfare improving under a wider range of circumstances. 4. Development of normative (axiomatic) approaches to pricing traffic in road network models: fairness and incentive-compatibility issues. There exists a small literature that seeks to design pricing schemes to have some desirable features, notably fairness, simplicity, decentralisation, non-manipulability and incentive compatibility. This theory has not yet been developed in the context of congestion externalities.