An Energy-Saving Approach for Real-Time Highway Traffic Estimation Using GPS-Enabled Smartphones

This paper presents a microscopic traffic estimation algorithm for smartphones by employing their built-in probes (such as GPS and acceleration sensors) to increase the accuracy of estimating the real-time traffic condition without significantly increasing these smart phones' energy consumption. In this approach, real-time traffic data is collected through cooperating smartphone users traveling on urban roads. A new reporting algorithm is provided on smartphone users’ side to minimize smartphone probes’ connection with the server. Based on these probes’ data, realtime traffic condition is estimated on the server side by applying the Kalman Filtering algorithm. Also the real-time traffic level of service (LOS) is estimated on urban roads. Simulation results show that the proposed algorithm requires less energy usage than existing methods without sacrificing the accuracy of the real-time traffic estimation. Keywords— Real-Time Traffic Estimation; Energy Saving; Kalman-Filtering; GPS