01658539

Component

Accurate and reliable traffic state estimations are extremely important for road operators and service providers, because they are the basis for decision making. Traffic is 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 are analyzed on link and route level. This paper contributes to existing literature by providing insight in the quality of the speed data of a floating car data(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.

This paper was sponsored by TRB committee ABJ35 Standing Committee on Highway Traffic Monitoring.

18-00609

English

15p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Accuracy; Applications; Floating car data; Physical distribution; Validation

Google

Highways; Operations and Traffic Management; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-00609

TRIS, TRB, ATRI

Jan 8 2018 10:09AM