Using Real Time Traffic Data to Support Intelligent Traffic Management: an Overview of the FREEFLOW Project

Using Real Time Traffic Data to Support Intelligent Traffic Management: an Overview of the FREEFLOW Project


J Polak, Imperial College London, UK



Traffic management authorities throughout Europe face increasing challenges in responding to new transport policy objectives, in a cash-constrained environment. In these circumstances, emphasis is placed on innovation in methods and practices that support the more efficient use of existing infrastructure and resources. In recent years there has been significant innovation in a number of relevant areas including transport data sources, network modelling tools, decision support technologies and the channels of communication with individual travellers. These developments provide enormous scope for improvements in network management and traveller information. But existing strategies and tools for network management do not fully exploit these capabilities, and remain largely reactive.

The aim of this paper is to provide a technical overview of a major research project, FREEFLOW, which has developed a new platform for traffic management and traveller information services that integrates latest developments in data, models, decision support and dissemination technologies, is driven by an explicit analysis of user requirements and which builds on, rather than duplicates, existing investments e.g., in the UK's UTMC architecture. FREEFLOW in a collaboration between 3 Universities (Imperial College London, University of York and Loughborough University, 3 major UK network management authorities (Transport for London, Kent County Council and York City Council) and 5 (Qinetiq, ACIS, Trakmo, Kizoom and Mindsheet) and is jointly funded by the UK Engineering and Physical Sciences Research Council, the UK Technology Strategy Board and the UK Department for Transport.

The paper is divided into a number of sections. The first section provides a brief summary of the context and motivation of the work and sets out the main objectives of the FREEFLOW project. The second section presents the overall architecture and briefly discusses the key areas of research and innovation undertaken in the project. These include work in:

1. Low level sensor processing (to extra new information from CCTV and inductive loop sensor sources)

2. Data warehouse (data sharing and dissemination using open standard interfaces with real-time capability)

3. Sensor data fusion (combining ILD, GPS, ANPR data for network performance estimation)

4. Network state estimation and prediction (identifying and predicting the development of incidents and queues)

5. Strategy development and selection (drawing on past operational experience and off-line modelling to develop and refine effective intervention strategies)

6. Enhanced traveller information for users as well as system managers (e.g., personalised travel alerts)

7. Integration, visualisation and decision support tools (providing improved user interfaces to link new data and modelling capabilities to evolving traffic control centre workflows)

The third section focuses in more detail on one of the key components of the FREEFLOW architecture ? the Intelligent Decision Support (IDS) layer. The role of the IDS layer is to monitor traffic sensor data in near-real-time, fuse data from different sensor sources and identify traffic problems such as congestion and incidents using a combination of traffic flow theory, flow profiles and incident detection concepts. IDS also generates advice on how to respond to network incidents and events by identifying similar problems in the past and determining which intervention actions were effective, using advanced pattern match techniques. The fourth section describes the demonstration and evaluation activity undertaken in the project, which has involved implementing customised versions of the FREEFLOW system in London, York and Kent. We discuss the lessons learnt during implementation and present an overview of the evaluation results. The final section presents some overall conclusions from the project and discusses some of the future directions for research and practice.


Association for European Transport