The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1503-2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1503-2019
05 Jun 2019
 | 05 Jun 2019

ROAD NETWORK COMPARISON AND MATCHING TECHNIQUES. A WORKFLOW PROPOSAL FOR THE INTEGRATION OF TRAFFIC MESSAGE CHANNEL AND OPEN SOURCE NETWORK DATASETS

A. Ajmar, E. Arco, and P. Boccardo

Keywords: Road Network, Data Matching, Conflation, Integration, Real-Time Traffic Data

Abstract. The rapid growth of methods and techniques to acquire geospatial data has led to a wide availability of overlapping geographic datasets with different characteristics. Road network data sources are today a significant number, with high differences in level of detail and modelling schemas, depending on the main purpose. In addition, continuous information about people and freight movement is today available also in real-time. This type of data is today exchanged between traffic operators using referencing standards as Traffic Message Channel. Integrating these heterogeneous databases, in order to build an added value product, is a serious task in geographical data management. The paper is focus on techniques to conflate the Traffic message Channel logical network on Open Source road network dataset, in order to allow the precise visualisation of traffic data also in real-time.

A first step of the research was the quality assessment of available Open Source (OS) road network dataset, then, a specific procedure to conflate data was set up, using an iterative process in order to reduce at every step the number of possible matching features. A first application of the enhanced OTM dataset is shown for the city of Turin: real-time open data of traffic flows recorded by road network fixed sensors, made available by the metropolitan Traffic Operation Centre (5T) and based on the TMC location referencing, are matched on the OTM road network, allowing a detailed real-time visualisation of traffic state.