Decision Support in Dynamic Traffic Management

Real-time Scenario Evaluation

Abstract

To support operators in Regional Traffic Management Centers in their task to efficiently and safely manage traffic flows on the motorway and urban networks, a decision support system is being developed. An essential function of this system is its ability to predict the effects of a large number of candidate control scenarios, given the recurrent and non-recurrent conditions in the network. This article proposes such a prediction system referred to as BSES (Boss Scenario Evaluation System), which can evaluate control scenarios in real time, predicting their effects in terms of various measures of effectiveness, such as total travel times, vehicle loss times, average speeds, fuel consumption, etc. The main characteristics of the system are l) that it is case- based, i.e. it uses either synthetic or real-life examples of the effect of control scenarios under different circumstances; 2) that is determines the similarity of the current situation to different examples in the case-base using fuzzy logic, and 3) that it is agent-based, meaning that it predicts the effects of the different measures for small subnetworks and combines these predictions afterwards. In the article, synthetic data is used to set-up the case base. The test results described in the article illustrate the workings of the system, and shows that the system can provide the operator with real-time predictions. Furthermore, the predictions of the system are in comparable to the predictions from the simulation model used to fill the case-base, showing that the method is applicable to generalize the - in this case synthetic - data it uses.