Dynamic Cooperative Route Choice


(Multiclass) Dynamic Traffic Assignment For Vehicle Route Guidance.

Scientific challenges

Dynamic traffic assignment models are primarily concerned with final equilibrium states of networks. Solution schemes tend to overlook the system’s evolution to equilibrium and the stability of its path flows. While the uniqueness of Dynamic User Equilibrium (DUE) and Dynamic System Optimal (DSO) solutions have been extensively studied in the literature, that of the multiclass and mixed objective problems is yet to be well understood. Current dynamic assignment solutions are obtained through a series of heuristic iterations. Their underlying solution methods are (relatively) computationally slow and are therefore not well suited for real-time vehicle route guidance. In particular, they do not allow for on-route change flexibility and mixed equilibria, in which separate user classes have different objectives.

In this project, we develop a new class of dynamic traffic assignment models that is suited for cooperative vehicle route guidance. We re-define the Dynamic Traffic Assignment problem from the perspective of a Dynamical System. We establish a dynamic traffic controller that steers traffic either to UE or SO or CO (Cooperative Optimal). Cooperation amongst drivers is explicitly considered as a means to achieve System Optimality. Critical to this project are the computational efficiency of vehicle routing algorithm, the properties of its stability, the ratio of user-acceptance (UE / SO) and near-equilibrium attractive sets.

Societal relevance

Several millions of euros can be saved if drivers were provided with suited route guidance assistance. Optimal route choices and associated departure times help reduce time travel losses and related negative environmental impacts. These benefits drastically increase when network disruptions are taken into consideration (road works, accidents,  traffic incidents, etc.). Cooperative route guidance systems increase the user’s experience when they receive and share real-time traffic information.

Kapko Adoko

Start/end date: 2014 -2017/18
Daily supervisor: Rob van Nes
Promotor: Bart van Arem