Cost-effective ubiquitous method for motor vehicle speed estimation using smartphones

Estimating longitudinal vehicle speed is required in a wide range of applications from road safety to vehicular emissions modelling. Each vehicle speed estimation method has specific challenges including the high cost of measurement equipment, the small range of vehicle models accessible for performing tests and the low resolution of data in time and space. Thus, the goals of this study are (a) to investigate the use of smartphones' integrated sensors as a convenient, reliable and powerful means of vehicle speed data collection which would mitigate the issues observed in previous methods, and (b) to propose a post-processing pipeline for generating vehicles' speed profiles based on the raw data captured by the proposed data collection method. Accordingly, a smartphone application is developed to facilitate the collection of vehicles' movement data, particularly inside tunnels and high-density urban areas, where state-of-the-art global positioning system (GPS) applications fail to record the desired data. Moreover, a post-processing pipeline is proposed for calculating vehicles' speed profiles and emissions from the raw smartphone acceleration data, and the full system is evaluated through a series of controlled experiments as well as simulations