Methodology (present and Future) for the Implementation of Decision Support Systems (DSS) for Traffic Management.



Methodology (present and Future) for the Implementation of Decision Support Systems (DSS) for Traffic Management.

Authors

Jordi Casas, TSS-Traffic Simulation Systems And Vic University, Josep Maria Aymamí, TSS-Traffic Simulation Systems, Josep Perarnau, TSS-Traffic Simulation Systems

Description

This article presents the current framework of the Decision Support systems (DSS) in making traffic management decisions based on short and medium-term predictions.

Abstract

Real-time traffic prediction has become an indispensable requirement for traffic management, whether in urban or interurban areas. Real-time traffic prediction helps traffic control room operators to evaluate the effect of the different traffic management strategies available (ITS systems, driver information, traffic control systems, etc). Through the combination of short-term forecasts of the state of the network and evaluations of the impact of different traffic management strategies, the DSS permits operators to anticipate and mitigate the effects of traffic congestion.

This article presents the current framework of the DSS in making traffic management decisions based on short and medium-term predictions. The description of the current framework covers the following elements:
• Analytic methods based on the analysis of time series versus methods based on traffic simulation models (macroscopic, mesoscopic, microscopic):
o Restrictions in the use of each method
o Simulation outputs of each method
• Types and quality of data available
• Strategies design off-line and evaluation
• Examples of current systems
This article also presents some reflections on the likely evolution of traffic managment DSSs according to current scientific research and the availability of new types of data and associated methodologies. These reflections can be grouped under the following headings:
• New available data
• Strategies design in real time
• Improvements in analytical methods and methods based on traffic simulation models:
o Hybrid models (analytical models combined with methods based on traffic simulation models)
o Travel demand models
 Models based on aggregate demand
 Models based on disaggregate demand
o Prediction models based on hybrid traffic simulation models
• Information dissemination to stakeholders.

This paper describes the current methodology implemented in a 35km highway, recently completed.

Key words: Decision Support Systems (DSS), traffic management, traffic simulation models, Aimsun Online

Publisher

Association for European Transport