Validation of Google floating car data for applications in traffic management
van den Haak, P.
van Katwijk, R.
Accurate and reliable traffic state estimations are extremely important for road operators and service providers, because they are the basis for decision making. Traffic movements are generally measured by different types of sensors that are placed in or along the road infrastructure. In this paper, aggregated and anonymized data from Google, originating from mobile devices and apps, is analyzed for its potential to be used for traffic management. These floating car data are speed time series at measurement locations. The traffic state estimations from Google’s data are validated by comparing them with data from over 2200 sensor locations on Dutch motorways for a period of 4 months. This dataset contains over 58 Million data points. On Dutch motorways congestion and incidents are recurrent at a daily basis and traffic management is essential. The coverage and accuracy is analyzed on link and route level by computing the MAPE, a reliability indicator and the Jaccard similarity index to detect the tails of jams. This paper contributes to existing literature by providing insight in the quality of the speed data of a FCD provider with one of the highest penetration rates worldwide and by not only showing the impact of replacing or fusing loop detector data with FCD on the quality of speed indicators, but by also providing insights in the potential costs savings. It is concluded that replacing some road sensors with Google data has limited and acceptable impact on quality and can lead to substantial cost reductions.
Floating car data
To reference this document use:
Mobility & Logistics
2015 Urban Mobility & Environment
SMb - Smart Mobility
ELSS - Earth, Life and Social Sciences
TRB 97th Annual Meeting Compendium of Papers. Washington DC, 1-15